<!-- README.md is generated from README.Rmd. Please edit that file -->
# simulateDCE
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The goal of simulateDCE is to make it easy to simulate choice experiment
datasets using designs from NGENE, `idefix` or `spdesign`. You have to
store the design file(s) in a subfolder and need to specify certain
parameters and the utility functions for the data generating process.
The package is useful for:
1. Test different designs in terms of statistical power, efficiency and
unbiasedness
2. To test the effects of deviations from RUM, e.g. heuristics, on
model performance for different designs.
3. In teaching, using simulated data is useful, if you want to know the
data generating process. It helps to demonstrate Maximum likelihood
and choice models, knowing exactly what you should expect.
4. You can use simulation in pre-registration to justify your sample
size and design choice.
5. Before data collection, you can use simulated data to estimate the
models you plan to use in the actual analysis. You can thus make
sure, you can estimate all effects for given sample sizes.
## Installation
You can install simulateDCE from github. You need to install the
`devtools` package first. The current version is alpha and there is no
version on cran:
``` r
install.packages("devtools")
devtools::install_git('https://github.com/sagebiej/simulateDCE', ref = "main")
```
For the latest development version use this:
``` r
install.packages("devtools")
devtools::install_git('https://github.com/sagebiej/simulateDCE', ref = "devel")
```
## Example
This is a basic example for a simulation:
``` r
rm(list=ls())
library(simulateDCE)
library(rlang)
library(formula.tools)
#>
#> Attaching package: 'formula.tools'
#> The following object is masked from 'package:rlang':
#>
#> env
designpath<- system.file("extdata","SE_DRIVE" ,package = "simulateDCE")
resps =120 # number of respondents
nosim= 400 # number of simulations to run (about 500 is minimum)
# bcoeff <- list(
# bpreis = -0.036,
# blade = -0.034,
# bwarte = -0.049)
decisiongroups=c(0,0.7,1)
# wrong parameters
# place b coefficients into an r list:
bcoeff = list(
bpreis = -0.01,
blade = -0.07,
bwarte = 0.02)
manipulations = list(alt1.x2= expr(alt1.x2/10),
alt1.x3= expr(alt1.x3/10),
alt2.x2= expr(alt2.x2/10),
alt2.x3= expr(alt2.x3/10)
)
#place your utility functions here
ul<-list( u1 =
list(
v1 =V.1~ bpreis * alt1.x1 + blade*alt1.x2 + bwarte*alt1.x3 ,
v2 =V.2~ bpreis * alt2.x1 + blade*alt2.x2 + bwarte*alt2.x3
)
,
u2 = list( v1 =V.1~ bpreis * alt1.x1 ,
v2 =V.2~ bpreis * alt2.x1)
)
destype="ngene"
sedrive <- sim_all(nosim = nosim, resps=resps, destype = destype,
designpath = designpath, u=ul, bcoeff = bcoeff, decisiongroups = decisiongroups)
#> 'simple' is deprecated and will be removed in the future. Use 'exact' instead.
#> bcoeff_lookup already exists; skipping modification.
#> Utility function used in simulation, ie the true utility:
#>
#> $u1
#> $u1$v1
#> V.1 ~ bpreis * alt1.x1 + blade * alt1.x2 + bwarte * alt1.x3
#> <environment: 0x5cc5fbecc2e0>
#>
#> $u1$v2
#> V.2 ~ bpreis * alt2.x1 + blade * alt2.x2 + bwarte * alt2.x3
#> <environment: 0x5cc5fbf0ffd8>
#>
#>
#> $u2
#> $u2$v1
#> V.1 ~ bpreis * alt1.x1
#> <environment: 0x5cc5fbf32890>
#>
#> $u2$v2
#> V.2 ~ bpreis * alt2.x1
#> <environment: 0x5cc5fbf54428>
#> 'destype' is deprecated. Please use 'designtype' instead.
#> New names:
#> • `Choice situation` -> `Choice.situation`
#> • `` -> `...10`
#>
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.5346621 0.7318508 -1.0846621 -11.868149 1
#> 2 1 -0.95 -2.35 0.5773936 -0.7811993 -0.3726064 -3.131199 1
#> 3 1 -6.20 -2.30 1.3382771 0.1158697 -4.8617229 -2.184130 2
#> 4 1 -13.90 -2.55 1.0026198 0.9662150 -12.8973802 -1.583785 2
#> 5 1 -14.40 -5.80 0.4685361 -0.4860094 -13.9314639 -6.286009 2
#> 6 1 -3.60 -1.70 2.5243715 0.6438044 -1.0756285 -1.056196 2
#>
#>
#> Transformed utility function (type: simple ):
#> [1] "U_1 = @bpreis * $alt1_x1 + @blade * $alt1_x2 + @bwarte * $alt1_x3 ;U_2 = @bpreis * $alt2_x1 + @blade * $alt2_x2 + @bwarte * $alt2_x3 ;"
#> This is Run number 1
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.0480412 1.0658687 1.4980412 -11.5341313 1
#> 2 1 -0.95 -2.35 1.6458423 3.0029775 0.6958423 0.6529775 1
#> 3 1 -6.20 -2.30 0.8064037 1.7156233 -5.3935963 -0.5843767 2
#> 4 1 -13.90 -2.55 -0.9656518 0.7281514 -14.8656518 -1.8218486 2
#> 5 1 -14.40 -5.80 -0.8679570 3.8650136 -15.2679570 -1.9349864 2
#> 6 1 -3.60 -1.70 0.7468481 1.9040151 -2.8531519 0.2040151 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6900 -38650 7050
#> initial value 998.131940
#> iter 2 value 814.051264
#> iter 3 value 803.513852
#> iter 4 value 803.277976
#> iter 5 value 766.362532
#> iter 6 value 757.804164
#> iter 7 value 756.391651
#> iter 8 value 756.360304
#> iter 9 value 756.360241
#> iter 10 value 756.360224
#> iter 10 value 756.360214
#> iter 10 value 756.360206
#> final value 756.360206
#> converged
#> This is Run number 2
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.95903510 1.7469021 -1.5090351 -10.8530979 1
#> 2 1 -0.95 -2.35 0.48567293 1.3550837 -0.4643271 -0.9949163 1
#> 3 1 -6.20 -2.30 -0.07062326 -0.3819651 -6.2706233 -2.6819651 2
#> 4 1 -13.90 -2.55 -0.27359542 1.7458482 -14.1735954 -0.8041518 2
#> 5 1 -14.40 -5.80 0.62747982 1.1230906 -13.7725202 -4.6769094 2
#> 6 1 -3.60 -1.70 5.51924738 0.5975311 1.9192474 -1.1024689 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7320 -40200 5325
#> initial value 998.131940
#> iter 2 value 798.413557
#> iter 3 value 790.367792
#> iter 4 value 788.829313
#> iter 5 value 756.684783
#> iter 6 value 747.942494
#> iter 7 value 746.186623
#> iter 8 value 746.134114
#> iter 9 value 746.133922
#> iter 10 value 746.133904
#> iter 10 value 746.133904
#> iter 10 value 746.133894
#> final value 746.133894
#> converged
#> This is Run number 3
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.3494364 -1.2638437 -0.8994364 -13.8638437 1
#> 2 1 -0.95 -2.35 -1.0591545 -0.3654889 -2.0091545 -2.7154889 1
#> 3 1 -6.20 -2.30 -0.6391097 -1.0715919 -6.8391097 -3.3715919 2
#> 4 1 -13.90 -2.55 1.9630398 -0.7375982 -11.9369602 -3.2875982 2
#> 5 1 -14.40 -5.80 -0.7461610 0.5740361 -15.1461610 -5.2259639 2
#> 6 1 -3.60 -1.70 1.1724058 0.9519715 -2.4275942 -0.7480285 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6360 -38275 7025
#> initial value 998.131940
#> iter 2 value 820.132002
#> iter 3 value 808.671749
#> iter 4 value 807.589000
#> iter 5 value 769.808211
#> iter 6 value 761.347358
#> iter 7 value 759.964884
#> iter 8 value 759.935731
#> iter 9 value 759.935680
#> iter 10 value 759.935667
#> iter 10 value 759.935656
#> iter 10 value 759.935656
#> final value 759.935656
#> converged
#> This is Run number 4
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.1651308 0.04473541 -0.38486924 -12.555265 1
#> 2 1 -0.95 -2.35 1.0457067 -0.56572294 0.09570666 -2.915723 1
#> 3 1 -6.20 -2.30 0.2653277 0.21907004 -5.93467227 -2.080930 2
#> 4 1 -13.90 -2.55 -0.4685129 0.47136596 -14.36851288 -2.078634 2
#> 5 1 -14.40 -5.80 1.5752600 2.73346135 -12.82473995 -3.066539 2
#> 6 1 -3.60 -1.70 -0.3584104 0.55026311 -3.95841043 -1.149737 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6460 -39625 8000
#> initial value 998.131940
#> iter 2 value 794.188083
#> iter 3 value 778.031063
#> iter 4 value 777.087469
#> iter 5 value 743.540679
#> iter 6 value 734.976004
#> iter 7 value 733.845920
#> iter 8 value 733.827251
#> iter 9 value 733.827233
#> iter 9 value 733.827230
#> iter 9 value 733.827220
#> final value 733.827220
#> converged
#> This is Run number 5
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.5668505 1.9385048 -1.116850 -10.6614952 1
#> 2 1 -0.95 -2.35 -1.0846610 0.5273078 -2.034661 -1.8226922 2
#> 3 1 -6.20 -2.30 -1.1667192 -0.3741714 -7.366719 -2.6741714 2
#> 4 1 -13.90 -2.55 -0.1146248 1.0349357 -14.014625 -1.5150643 2
#> 5 1 -14.40 -5.80 -0.4668516 2.2256308 -14.866852 -3.5743692 2
#> 6 1 -3.60 -1.70 0.2743071 2.4364835 -3.325693 0.7364835 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6460 -36600 5775
#> initial value 998.131940
#> iter 2 value 849.190980
#> iter 3 value 842.712950
#> iter 4 value 841.936546
#> iter 5 value 799.442275
#> iter 6 value 791.541423
#> iter 7 value 789.904678
#> iter 8 value 789.870085
#> iter 9 value 789.869999
#> iter 9 value 789.869999
#> iter 9 value 789.869999
#> final value 789.869999
#> converged
#> This is Run number 6
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.1867229 -1.3282405 -0.3632771 -13.92824045 1
#> 2 1 -0.95 -2.35 -0.7120267 0.4058905 -1.6620267 -1.94410949 1
#> 3 1 -6.20 -2.30 0.9499792 1.3408087 -5.2500208 -0.95919130 2
#> 4 1 -13.90 -2.55 -0.6068414 -0.2863894 -14.5068414 -2.83638939 2
#> 5 1 -14.40 -5.80 0.2791787 0.1775473 -14.1208213 -5.62245268 2
#> 6 1 -3.60 -1.70 -0.4503255 1.6392219 -4.0503255 -0.06077805 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6480 -40050 6300
#> initial value 998.131940
#> iter 2 value 797.254783
#> iter 3 value 784.067854
#> iter 4 value 781.033483
#> iter 5 value 748.988742
#> iter 6 value 740.229226
#> iter 7 value 738.865229
#> iter 8 value 738.831723
#> iter 9 value 738.831657
#> iter 9 value 738.831649
#> iter 9 value 738.831643
#> final value 738.831643
#> converged
#> This is Run number 7
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.21350661 -0.0899883 -0.3364934 -12.689988 1
#> 2 1 -0.95 -2.35 2.12381588 -0.2254029 1.1738159 -2.575403 1
#> 3 1 -6.20 -2.30 4.10025765 0.4750744 -2.0997424 -1.824926 2
#> 4 1 -13.90 -2.55 -0.41310328 -0.6352374 -14.3131033 -3.185237 2
#> 5 1 -14.40 -5.80 0.05799517 -1.3854798 -14.3420048 -7.185480 2
#> 6 1 -3.60 -1.70 2.15245815 0.5629682 -1.4475418 -1.137032 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5760 -37400 6900
#> initial value 998.131940
#> iter 2 value 833.324198
#> iter 3 value 821.238217
#> iter 4 value 819.048965
#> iter 5 value 779.096282
#> iter 6 value 770.853182
#> iter 7 value 769.477617
#> iter 8 value 769.450544
#> iter 9 value 769.450502
#> iter 9 value 769.450491
#> iter 9 value 769.450486
#> final value 769.450486
#> converged
#> This is Run number 8
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.5798834 -0.3211425 0.02988338 -12.9211425 1
#> 2 1 -0.95 -2.35 -0.6568726 2.9615102 -1.60687260 0.6115102 2
#> 3 1 -6.20 -2.30 1.0462290 -0.8025417 -5.15377097 -3.1025417 2
#> 4 1 -13.90 -2.55 1.9432565 -0.5925105 -11.95674349 -3.1425105 2
#> 5 1 -14.40 -5.80 -0.2125311 -0.5395650 -14.61253107 -6.3395650 2
#> 6 1 -3.60 -1.70 0.5850380 0.8600823 -3.01496199 -0.8399177 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6760 -39500 7725
#> initial value 998.131940
#> iter 2 value 797.555745
#> iter 3 value 783.435479
#> iter 4 value 783.002682
#> iter 5 value 748.858861
#> iter 6 value 740.221327
#> iter 7 value 739.023456
#> iter 8 value 739.001304
#> iter 9 value 739.001293
#> iter 9 value 739.001288
#> iter 10 value 739.001265
#> iter 11 value 739.001253
#> iter 11 value 739.001253
#> iter 11 value 739.001250
#> final value 739.001250
#> converged
#> This is Run number 9
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.69241378 -0.027102867 -1.242414 -12.6271029 1
#> 2 1 -0.95 -2.35 -0.33240342 0.957319274 -1.282403 -1.3926807 1
#> 3 1 -6.20 -2.30 -0.02159452 0.523861864 -6.221595 -1.7761381 2
#> 4 1 -13.90 -2.55 -0.43976792 2.255627590 -14.339768 -0.2943724 2
#> 5 1 -14.40 -5.80 1.59548064 0.005022084 -12.804519 -5.7949779 2
#> 6 1 -3.60 -1.70 0.36964385 -0.070284512 -3.230356 -1.7702845 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6140 -38925 7375
#> initial value 998.131940
#> iter 2 value 808.805881
#> iter 3 value 794.383536
#> iter 4 value 792.492764
#> iter 5 value 756.940395
#> iter 6 value 748.397803
#> iter 7 value 747.136101
#> iter 8 value 747.111451
#> iter 9 value 747.111422
#> iter 9 value 747.111412
#> iter 9 value 747.111406
#> final value 747.111406
#> converged
#> This is Run number 10
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.55377101 -0.06400035 -1.1037710 -12.664000 1
#> 2 1 -0.95 -2.35 0.65046709 1.31960333 -0.2995329 -1.030397 1
#> 3 1 -6.20 -2.30 -0.08514854 -0.35122632 -6.2851485 -2.651226 2
#> 4 1 -13.90 -2.55 -0.24910236 0.41807233 -14.1491024 -2.131928 2
#> 5 1 -14.40 -5.80 1.44398692 0.61195541 -12.9560131 -5.188045 2
#> 6 1 -3.60 -1.70 1.29566396 0.41997169 -2.3043360 -1.280028 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7240 -39850 6400
#> initial value 998.131940
#> iter 2 value 799.047238
#> iter 3 value 789.288368
#> iter 4 value 788.745320
#> iter 5 value 755.304582
#> iter 6 value 746.556906
#> iter 7 value 745.070645
#> iter 8 value 745.032618
#> iter 9 value 745.032529
#> iter 10 value 745.032514
#> iter 10 value 745.032507
#> iter 10 value 745.032499
#> final value 745.032499
#> converged
#> This is Run number 11
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.8302687 0.6367215 0.2802687 -11.963278 1
#> 2 1 -0.95 -2.35 0.1713546 -0.6215377 -0.7786454 -2.971538 1
#> 3 1 -6.20 -2.30 0.2922556 0.0418291 -5.9077444 -2.258171 2
#> 4 1 -13.90 -2.55 1.1815540 0.6897143 -12.7184460 -1.860286 2
#> 5 1 -14.40 -5.80 -0.2580984 1.6449478 -14.6580984 -4.155052 2
#> 6 1 -3.60 -1.70 2.0032401 0.0826559 -1.5967599 -1.617344 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5560 -39250 7150
#> initial value 998.131940
#> iter 2 value 805.365550
#> iter 3 value 787.032465
#> iter 4 value 782.361624
#> iter 5 value 748.443105
#> iter 6 value 739.857615
#> iter 7 value 738.659548
#> iter 8 value 738.636756
#> iter 9 value 738.636736
#> iter 9 value 738.636731
#> iter 9 value 738.636727
#> final value 738.636727
#> converged
#> This is Run number 12
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.9803801 -0.26153559 -1.5303801 -12.8615356 1
#> 2 1 -0.95 -2.35 1.7419333 0.07796661 0.7919333 -2.2720334 1
#> 3 1 -6.20 -2.30 1.4003382 -0.88584325 -4.7996618 -3.1858432 2
#> 4 1 -13.90 -2.55 -1.4346036 -0.76433179 -15.3346036 -3.3143318 2
#> 5 1 -14.40 -5.80 -0.6871762 -1.84393126 -15.0871762 -7.6439313 2
#> 6 1 -3.60 -1.70 3.1893690 1.48324819 -0.4106310 -0.2167518 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6700 -38575 6775
#> initial value 998.131940
#> iter 2 value 816.882836
#> iter 3 value 806.574919
#> iter 4 value 805.890778
#> iter 5 value 768.813677
#> iter 6 value 760.282612
#> iter 7 value 758.832693
#> iter 8 value 758.799819
#> iter 9 value 758.799752
#> iter 10 value 758.799736
#> iter 10 value 758.799726
#> iter 10 value 758.799725
#> final value 758.799725
#> converged
#> This is Run number 13
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.1991772 1.1511615 -0.74917718 -11.448838 1
#> 2 1 -0.95 -2.35 0.9329473 0.3775952 -0.01705267 -1.972405 1
#> 3 1 -6.20 -2.30 1.8494722 -0.5189996 -4.35052776 -2.819000 2
#> 4 1 -13.90 -2.55 0.1553253 0.6869012 -13.74467470 -1.863099 2
#> 5 1 -14.40 -5.80 2.9140428 2.1088163 -11.48595724 -3.691184 2
#> 6 1 -3.60 -1.70 0.9493834 -0.4533498 -2.65061659 -2.153350 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5720 -38225 7225
#> initial value 998.131940
#> iter 2 value 819.997689
#> iter 3 value 805.307244
#> iter 4 value 802.513743
#> iter 5 value 765.124055
#> iter 6 value 756.700421
#> iter 7 value 755.405431
#> iter 8 value 755.380579
#> iter 9 value 755.380550
#> iter 9 value 755.380540
#> iter 9 value 755.380535
#> final value 755.380535
#> converged
#> This is Run number 14
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.0226271 1.8022229 -1.5726271 -10.7977771 1
#> 2 1 -0.95 -2.35 0.2449677 -0.7119570 -0.7050323 -3.0619570 1
#> 3 1 -6.20 -2.30 -0.3483096 -0.8870686 -6.5483096 -3.1870686 2
#> 4 1 -13.90 -2.55 -0.3558228 1.8516659 -14.2558228 -0.6983341 2
#> 5 1 -14.40 -5.80 1.9414634 3.9030741 -12.4585366 -1.8969259 2
#> 6 1 -3.60 -1.70 0.8671413 2.5681117 -2.7328587 0.8681117 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6060 -38125 7250
#> initial value 998.131940
#> iter 2 value 821.172714
#> iter 3 value 808.367696
#> iter 4 value 806.782637
#> iter 5 value 768.753533
#> iter 6 value 760.339769
#> iter 7 value 759.013804
#> iter 8 value 758.987644
#> iter 9 value 758.987607
#> iter 10 value 758.987595
#> iter 10 value 758.987585
#> iter 10 value 758.987580
#> final value 758.987580
#> converged
#> This is Run number 15
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.6697426 -0.2212345 -1.2197426 -12.821234 1
#> 2 1 -0.95 -2.35 0.1329135 -0.1484477 -0.8170865 -2.498448 1
#> 3 1 -6.20 -2.30 1.8040782 -1.1926918 -4.3959218 -3.492692 2
#> 4 1 -13.90 -2.55 -0.2969303 0.4498545 -14.1969303 -2.100146 2
#> 5 1 -14.40 -5.80 -0.8939682 0.1640928 -15.2939682 -5.635907 2
#> 6 1 -3.60 -1.70 -0.9939891 0.3689768 -4.5939891 -1.331023 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6240 -37875 6650
#> initial value 998.131940
#> iter 2 value 827.899993
#> iter 3 value 817.382899
#> iter 4 value 815.958442
#> iter 5 value 777.095544
#> iter 6 value 768.734927
#> iter 7 value 767.282448
#> iter 8 value 767.251137
#> iter 9 value 767.251077
#> iter 9 value 767.251076
#> iter 9 value 767.251076
#> final value 767.251076
#> converged
#> This is Run number 16
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.4430095 -0.5300688 -0.9930095 -13.1300688 1
#> 2 1 -0.95 -2.35 3.5029252 -1.1477896 2.5529252 -3.4977896 1
#> 3 1 -6.20 -2.30 1.2878364 1.4547887 -4.9121636 -0.8452113 2
#> 4 1 -13.90 -2.55 2.0919139 -1.2793114 -11.8080861 -3.8293114 2
#> 5 1 -14.40 -5.80 -0.3452620 -0.5455779 -14.7452620 -6.3455779 2
#> 6 1 -3.60 -1.70 -1.0382948 -0.3328220 -4.6382948 -2.0328220 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5680 -38700 8425
#> initial value 998.131940
#> iter 2 value 805.632321
#> iter 3 value 787.126143
#> iter 4 value 784.943829
#> iter 5 value 749.005847
#> iter 6 value 740.652192
#> iter 7 value 739.522359
#> iter 8 value 739.506073
#> iter 9 value 739.506060
#> iter 9 value 739.506055
#> iter 9 value 739.506052
#> final value 739.506052
#> converged
#> This is Run number 17
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.10726253 0.1562533 0.5572625 -12.4437467 1
#> 2 1 -0.95 -2.35 -1.03723690 2.4601367 -1.9872369 0.1101367 2
#> 3 1 -6.20 -2.30 0.33340273 0.2966318 -5.8665973 -2.0033682 2
#> 4 1 -13.90 -2.55 0.47342490 1.1619897 -13.4265751 -1.3880103 2
#> 5 1 -14.40 -5.80 -0.04790816 -0.9262372 -14.4479082 -6.7262372 2
#> 6 1 -3.60 -1.70 -0.25237807 0.6792071 -3.8523781 -1.0207929 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6060 -39525 8600
#> initial value 998.131940
#> iter 2 value 791.960827
#> iter 3 value 772.617019
#> iter 4 value 771.139777
#> iter 5 value 737.594100
#> iter 6 value 729.207147
#> iter 7 value 728.147911
#> iter 8 value 728.133621
#> iter 9 value 728.133602
#> iter 9 value 728.133596
#> iter 9 value 728.133596
#> final value 728.133596
#> converged
#> This is Run number 18
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.7412233 0.62578691 0.1912233 -11.974213 1
#> 2 1 -0.95 -2.35 0.3224486 0.83719236 -0.6275514 -1.512808 1
#> 3 1 -6.20 -2.30 -1.0891595 -0.07786002 -7.2891595 -2.377860 2
#> 4 1 -13.90 -2.55 -0.6999784 0.43833581 -14.5999784 -2.111664 2
#> 5 1 -14.40 -5.80 -0.9937733 0.84542868 -15.3937733 -4.954571 2
#> 6 1 -3.60 -1.70 0.4503231 -0.52201593 -3.1496769 -2.222016 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7360 -40025 5825
#> initial value 998.131940
#> iter 2 value 798.921328
#> iter 3 value 790.485091
#> iter 4 value 789.657678
#> iter 5 value 756.737560
#> iter 6 value 747.986793
#> iter 7 value 746.352573
#> iter 8 value 746.307171
#> iter 9 value 746.307041
#> iter 10 value 746.307026
#> iter 10 value 746.307026
#> iter 10 value 746.307019
#> final value 746.307019
#> converged
#> This is Run number 19
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.5742353 0.2599047 -1.12423532 -12.340095 1
#> 2 1 -0.95 -2.35 0.8716942 1.0253969 -0.07830585 -1.324603 1
#> 3 1 -6.20 -2.30 0.4024112 -0.1901571 -5.79758884 -2.490157 2
#> 4 1 -13.90 -2.55 1.1478203 -0.7324204 -12.75217966 -3.282420 2
#> 5 1 -14.40 -5.80 0.5179299 1.2628388 -13.88207015 -4.537161 2
#> 6 1 -3.60 -1.70 0.2990833 -0.4118175 -3.30091671 -2.111818 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5800 -40250 8050
#> initial value 998.131940
#> iter 2 value 784.410953
#> iter 3 value 763.207399
#> iter 4 value 759.363723
#> iter 5 value 728.629462
#> iter 6 value 720.229731
#> iter 7 value 719.188904
#> iter 8 value 719.172593
#> iter 8 value 719.172586
#> final value 719.172586
#> converged
#> This is Run number 20
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.54093200 0.9146525 0.99093200 -11.6853475 1
#> 2 1 -0.95 -2.35 0.99359644 0.8103119 0.04359644 -1.5396881 1
#> 3 1 -6.20 -2.30 -0.05574717 3.6530462 -6.25574717 1.3530462 2
#> 4 1 -13.90 -2.55 1.14689252 0.3959909 -12.75310748 -2.1540091 2
#> 5 1 -14.40 -5.80 -0.29085079 0.6199654 -14.69085079 -5.1800346 2
#> 6 1 -3.60 -1.70 -0.57138927 1.2125393 -4.17138927 -0.4874607 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5940 -38500 6550
#> initial value 998.131940
#> iter 2 value 819.663167
#> iter 3 value 806.484485
#> iter 4 value 803.481753
#> iter 5 value 766.853816
#> iter 6 value 758.331166
#> iter 7 value 756.931409
#> iter 8 value 756.900884
#> iter 9 value 756.900831
#> iter 9 value 756.900822
#> iter 9 value 756.900817
#> final value 756.900817
#> converged
#> This is Run number 21
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 3.1726579 -1.3164440 2.622657902 -13.9164440 1
#> 2 1 -0.95 -2.35 0.9532956 3.6710337 0.003295594 1.3210337 2
#> 3 1 -6.20 -2.30 0.6409443 0.4491905 -5.559055733 -1.8508095 2
#> 4 1 -13.90 -2.55 -0.3810352 2.1951681 -14.281035155 -0.3548319 2
#> 5 1 -14.40 -5.80 1.5795551 -0.3248330 -12.820444855 -6.1248330 2
#> 6 1 -3.60 -1.70 -0.4157202 -0.5185339 -4.015720176 -2.2185339 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6420 -39550 7375
#> initial value 998.131940
#> iter 2 value 799.220577
#> iter 3 value 784.729741
#> iter 4 value 783.181163
#> iter 5 value 749.406678
#> iter 6 value 740.779257
#> iter 7 value 739.551151
#> iter 8 value 739.526731
#> iter 9 value 739.526702
#> iter 9 value 739.526693
#> iter 9 value 739.526686
#> final value 739.526686
#> converged
#> This is Run number 22
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.8175021 -0.35435672 -1.367502 -12.954357 1
#> 2 1 -0.95 -2.35 -0.1995796 -0.61567055 -1.149580 -2.965671 1
#> 3 1 -6.20 -2.30 0.7204438 0.23624759 -5.479556 -2.063752 2
#> 4 1 -13.90 -2.55 1.8926614 -0.02072729 -12.007339 -2.570727 2
#> 5 1 -14.40 -5.80 -0.2718300 0.18629880 -14.671830 -5.613701 2
#> 6 1 -3.60 -1.70 -0.6245241 0.21125305 -4.224524 -1.488747 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5600 -37200 7575
#> initial value 998.131940
#> iter 2 value 832.190865
#> iter 3 value 818.820408
#> iter 4 value 816.918318
#> iter 5 value 776.346371
#> iter 6 value 768.166574
#> iter 7 value 766.883717
#> iter 8 value 766.861318
#> iter 9 value 766.861291
#> iter 9 value 766.861281
#> iter 9 value 766.861276
#> final value 766.861276
#> converged
#> This is Run number 23
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.23997973 1.6529340 -0.3100203 -10.947066 1
#> 2 1 -0.95 -2.35 -0.35775476 -1.0901106 -1.3077548 -3.440111 1
#> 3 1 -6.20 -2.30 0.05300973 -1.1033464 -6.1469903 -3.403346 2
#> 4 1 -13.90 -2.55 1.55715428 1.0464371 -12.3428457 -1.503563 2
#> 5 1 -14.40 -5.80 1.06540419 0.6167304 -13.3345958 -5.183270 2
#> 6 1 -3.60 -1.70 -0.29567605 0.3535731 -3.8956761 -1.346427 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5880 -39025 6950
#> initial value 998.131940
#> iter 2 value 809.832251
#> iter 3 value 794.516541
#> iter 4 value 791.150581
#> iter 5 value 756.230383
#> iter 6 value 747.646775
#> iter 7 value 746.359738
#> iter 8 value 746.333251
#> iter 9 value 746.333218
#> iter 9 value 746.333210
#> iter 9 value 746.333205
#> final value 746.333205
#> converged
#> This is Run number 24
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.5811512 -0.6668047 -1.131151 -13.2668047 1
#> 2 1 -0.95 -2.35 2.3536173 -1.0546874 1.403617 -3.4046874 1
#> 3 1 -6.20 -2.30 -1.0869926 -0.5082091 -7.286993 -2.8082091 2
#> 4 1 -13.90 -2.55 0.5573746 2.3065882 -13.342625 -0.2434118 2
#> 5 1 -14.40 -5.80 -0.5445224 0.0458446 -14.944522 -5.7541554 2
#> 6 1 -3.60 -1.70 -0.3383747 -0.7048156 -3.938375 -2.4048156 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6380 -38900 6875
#> initial value 998.131940
#> iter 2 value 811.861737
#> iter 3 value 799.578196
#> iter 4 value 797.953502
#> iter 5 value 762.142990
#> iter 6 value 753.563423
#> iter 7 value 752.195332
#> iter 8 value 752.165387
#> iter 9 value 752.165337
#> iter 10 value 752.165325
#> iter 10 value 752.165317
#> iter 10 value 752.165317
#> final value 752.165317
#> converged
#> This is Run number 25
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.79506340 2.9684872 0.2450634 -9.6315128 1
#> 2 1 -0.95 -2.35 0.02059948 4.0962295 -0.9294005 1.7462295 2
#> 3 1 -6.20 -2.30 -0.89827309 -0.2988247 -7.0982731 -2.5988247 2
#> 4 1 -13.90 -2.55 1.85670394 -0.5479160 -12.0432961 -3.0979160 2
#> 5 1 -14.40 -5.80 0.33733135 0.2319431 -14.0626686 -5.5680569 2
#> 6 1 -3.60 -1.70 1.80807202 2.1504539 -1.7919280 0.4504539 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5800 -38200 6400
#> initial value 998.131940
#> iter 2 value 824.772414
#> iter 3 value 811.610414
#> iter 4 value 808.317614
#> iter 5 value 770.861084
#> iter 6 value 762.384077
#> iter 7 value 760.960246
#> iter 8 value 760.929323
#> iter 9 value 760.929266
#> iter 9 value 760.929257
#> iter 9 value 760.929252
#> final value 760.929252
#> converged
#> This is Run number 26
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.61494977 0.7730959 0.06494977 -11.826904 1
#> 2 1 -0.95 -2.35 1.88643832 0.6808709 0.93643832 -1.669129 1
#> 3 1 -6.20 -2.30 -0.86961688 -0.1904128 -7.06961688 -2.490413 2
#> 4 1 -13.90 -2.55 -0.05374765 0.7616439 -13.95374765 -1.788356 2
#> 5 1 -14.40 -5.80 3.47362298 1.5059658 -10.92637702 -4.294034 2
#> 6 1 -3.60 -1.70 0.28917639 -1.3190910 -3.31082361 -3.019091 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6200 -38275 5925
#> initial value 998.131940
#> iter 2 value 825.848063
#> iter 3 value 815.246076
#> iter 4 value 812.696404
#> iter 5 value 775.260391
#> iter 6 value 766.794316
#> iter 7 value 765.220969
#> iter 8 value 765.183547
#> iter 9 value 765.183455
#> iter 10 value 765.183442
#> iter 10 value 765.183442
#> iter 10 value 765.183438
#> final value 765.183438
#> converged
#> This is Run number 27
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.17428232 -0.5063131 -0.3757177 -13.1063131 1
#> 2 1 -0.95 -2.35 0.59503521 0.4532163 -0.3549648 -1.8967837 1
#> 3 1 -6.20 -2.30 -0.80878323 2.8184548 -7.0087832 0.5184548 2
#> 4 1 -13.90 -2.55 1.16638698 -1.1685989 -12.7336130 -3.7185989 2
#> 5 1 -14.40 -5.80 3.87828296 -0.5075608 -10.5217170 -6.3075608 2
#> 6 1 -3.60 -1.70 0.05482436 1.8947469 -3.5451756 0.1947469 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6540 -37525 6375
#> initial value 998.131940
#> iter 2 value 833.922833
#> iter 3 value 825.513174
#> iter 4 value 824.798810
#> iter 5 value 784.717063
#> iter 6 value 776.469774
#> iter 7 value 774.919701
#> iter 8 value 774.885346
#> iter 9 value 774.885266
#> iter 9 value 774.885264
#> iter 9 value 774.885264
#> final value 774.885264
#> converged
#> This is Run number 28
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.009285943 0.99401803 -0.5592859 -11.6059820 1
#> 2 1 -0.95 -2.35 0.292396581 0.18369436 -0.6576034 -2.1663056 1
#> 3 1 -6.20 -2.30 -1.115241992 0.01880581 -7.3152420 -2.2811942 2
#> 4 1 -13.90 -2.55 2.386206195 2.16271800 -11.5137938 -0.3872820 2
#> 5 1 -14.40 -5.80 0.733583378 0.96497297 -13.6664166 -4.8350270 2
#> 6 1 -3.60 -1.70 0.401342416 0.96390485 -3.1986576 -0.7360952 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6080 -38750 8175
#> initial value 998.131940
#> iter 2 value 806.438136
#> iter 3 value 790.250129
#> iter 4 value 789.046565
#> iter 5 value 752.928739
#> iter 6 value 744.477324
#> iter 7 value 743.317181
#> iter 8 value 743.298959
#> iter 9 value 743.298945
#> iter 9 value 743.298942
#> iter 10 value 743.298931
#> iter 10 value 743.298923
#> iter 10 value 743.298922
#> final value 743.298922
#> converged
#> This is Run number 29
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.7471286 -0.3855214 1.1971286 -12.9855214 1
#> 2 1 -0.95 -2.35 0.1612026 1.2885028 -0.7887974 -1.0614972 1
#> 3 1 -6.20 -2.30 3.1399183 0.7451406 -3.0600817 -1.5548594 2
#> 4 1 -13.90 -2.55 1.1562691 1.1418581 -12.7437309 -1.4081419 2
#> 5 1 -14.40 -5.80 -0.2553048 -0.4954830 -14.6553048 -6.2954830 2
#> 6 1 -3.60 -1.70 1.7257312 0.8319119 -1.8742688 -0.8680881 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5680 -36675 6825
#> initial value 998.131940
#> iter 2 value 843.431492
#> iter 3 value 832.639176
#> iter 4 value 830.764674
#> iter 5 value 788.737420
#> iter 6 value 780.709120
#> iter 7 value 779.326526
#> iter 8 value 779.300299
#> iter 9 value 779.300257
#> iter 9 value 779.300256
#> iter 9 value 779.300256
#> final value 779.300256
#> converged
#> This is Run number 30
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.4583561 -0.4276330 -1.008356 -13.027633 1
#> 2 1 -0.95 -2.35 -0.9055229 -0.1672029 -1.855523 -2.517203 1
#> 3 1 -6.20 -2.30 1.7038551 0.7256820 -4.496145 -1.574318 2
#> 4 1 -13.90 -2.55 -0.7621098 -0.4771581 -14.662110 -3.027158 2
#> 5 1 -14.40 -5.80 -0.3998774 -1.0933774 -14.799877 -6.893377 2
#> 6 1 -3.60 -1.70 1.6273573 0.1763657 -1.972643 -1.523634 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6180 -38075 6375
#> initial value 998.131940
#> iter 2 value 826.535088
#> iter 3 value 815.752278
#> iter 4 value 813.745311
#> iter 5 value 775.608465
#> iter 6 value 767.196971
#> iter 7 value 765.709509
#> iter 8 value 765.676337
#> iter 9 value 765.676270
#> iter 9 value 765.676260
#> iter 9 value 765.676254
#> final value 765.676254
#> converged
#> This is Run number 31
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.0695231 0.2012381 -1.619523 -12.3987619 1
#> 2 1 -0.95 -2.35 -0.3692137 1.7454102 -1.319214 -0.6045898 2
#> 3 1 -6.20 -2.30 0.9046795 1.4778487 -5.295320 -0.8221513 2
#> 4 1 -13.90 -2.55 -0.2933849 0.7417986 -14.193385 -1.8082014 2
#> 5 1 -14.40 -5.80 -0.6282223 1.8206628 -15.028222 -3.9793372 2
#> 6 1 -3.60 -1.70 0.7008495 -0.9524986 -2.899151 -2.6524986 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6320 -37975 6875
#> initial value 998.131940
#> iter 2 value 825.239839
#> iter 3 value 814.469941
#> iter 4 value 813.367835
#> iter 5 value 774.710702
#> iter 6 value 766.320084
#> iter 7 value 764.901373
#> iter 8 value 764.871231
#> iter 9 value 764.871175
#> iter 10 value 764.871161
#> iter 10 value 764.871151
#> iter 10 value 764.871146
#> final value 764.871146
#> converged
#> This is Run number 32
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.2923237 -0.34185310 -0.2576763 -12.94185310 1
#> 2 1 -0.95 -2.35 0.1778100 2.28439972 -0.7721900 -0.06560028 2
#> 3 1 -6.20 -2.30 4.6585126 0.50816742 -1.5414874 -1.79183258 1
#> 4 1 -13.90 -2.55 2.6096463 0.06879165 -11.2903537 -2.48120835 2
#> 5 1 -14.40 -5.80 -0.2451368 -0.42604177 -14.6451368 -6.22604177 2
#> 6 1 -3.60 -1.70 1.2610084 -0.99274356 -2.3389916 -2.69274356 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6520 -38150 5800
#> initial value 998.131940
#> iter 2 value 827.981080
#> iter 3 value 819.282063
#> iter 4 value 817.639860
#> iter 5 value 779.580434
#> iter 6 value 771.185328
#> iter 7 value 769.529829
#> iter 8 value 769.489814
#> iter 9 value 769.489708
#> iter 10 value 769.489695
#> iter 10 value 769.489693
#> iter 10 value 769.489692
#> final value 769.489692
#> converged
#> This is Run number 33
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.7820398 -0.3618176 -1.332040 -12.9618176 1
#> 2 1 -0.95 -2.35 -0.2823878 0.4905537 -1.232388 -1.8594463 1
#> 3 1 -6.20 -2.30 0.6124959 0.2771269 -5.587504 -2.0228731 2
#> 4 1 -13.90 -2.55 1.1618612 0.4721477 -12.738139 -2.0778523 2
#> 5 1 -14.40 -5.80 2.9320682 -0.3157078 -11.467932 -6.1157078 2
#> 6 1 -3.60 -1.70 -0.5046445 2.4571157 -4.104644 0.7571157 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5980 -37900 6850
#> initial value 998.131940
#> iter 2 value 826.616061
#> iter 3 value 814.587727
#> iter 4 value 812.582007
#> iter 5 value 773.985393
#> iter 6 value 765.615980
#> iter 7 value 764.226528
#> iter 8 value 764.197877
#> iter 9 value 764.197830
#> iter 9 value 764.197819
#> iter 9 value 764.197813
#> final value 764.197813
#> converged
#> This is Run number 34
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.35318374 1.71399735 0.8031837 -10.88600265 1
#> 2 1 -0.95 -2.35 -0.05992435 -0.10723221 -1.0099244 -2.45723221 1
#> 3 1 -6.20 -2.30 0.09335095 -1.19775312 -6.1066491 -3.49775312 2
#> 4 1 -13.90 -2.55 -0.59008289 0.74789339 -14.4900829 -1.80210661 2
#> 5 1 -14.40 -5.80 1.81945873 0.01755771 -12.5805413 -5.78244229 2
#> 6 1 -3.60 -1.70 -0.12606651 1.78929845 -3.7260665 0.08929845 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5920 -38325 7575
#> initial value 998.131940
#> iter 2 value 816.457874
#> iter 3 value 801.948179
#> iter 4 value 800.077130
#> iter 5 value 762.770038
#> iter 6 value 754.342467
#> iter 7 value 753.083401
#> iter 8 value 753.060307
#> iter 9 value 753.060281
#> iter 9 value 753.060272
#> iter 9 value 753.060266
#> final value 753.060266
#> converged
#> This is Run number 35
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.14043048 1.39313651 -0.4095695 -11.2068635 1
#> 2 1 -0.95 -2.35 -0.73092421 2.68732915 -1.6809242 0.3373292 2
#> 3 1 -6.20 -2.30 -0.15294274 1.21610800 -6.3529427 -1.0838920 2
#> 4 1 -13.90 -2.55 -0.04897067 1.62698452 -13.9489707 -0.9230155 2
#> 5 1 -14.40 -5.80 1.84091168 0.11293400 -12.5590883 -5.6870660 2
#> 6 1 -3.60 -1.70 -0.72173644 -0.04155647 -4.3217364 -1.7415565 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5960 -38675 7275
#> initial value 998.131940
#> iter 2 value 813.146036
#> iter 3 value 798.593452
#> iter 4 value 796.234509
#> iter 5 value 760.058109
#> iter 6 value 751.554155
#> iter 7 value 750.274208
#> iter 8 value 750.249141
#> iter 9 value 750.249111
#> iter 9 value 750.249101
#> iter 9 value 750.249096
#> final value 750.249096
#> converged
#> This is Run number 36
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.54236870 1.37120574 -1.092369 -11.228794 1
#> 2 1 -0.95 -2.35 -0.13553929 -1.50755110 -1.085539 -3.857551 1
#> 3 1 -6.20 -2.30 -0.46534926 -0.08382678 -6.665349 -2.383827 2
#> 4 1 -13.90 -2.55 -0.07478104 0.78998504 -13.974781 -1.760015 2
#> 5 1 -14.40 -5.80 0.62893248 0.12093493 -13.771068 -5.679065 2
#> 6 1 -3.60 -1.70 -0.47623471 -0.68165571 -4.076235 -2.381656 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6000 -37200 6375
#> initial value 998.131940
#> iter 2 value 838.701786
#> iter 3 value 828.804108
#> iter 4 value 827.012125
#> iter 5 value 786.387129
#> iter 6 value 778.216387
#> iter 7 value 776.731959
#> iter 8 value 776.700938
#> iter 9 value 776.700877
#> iter 9 value 776.700876
#> iter 9 value 776.700876
#> final value 776.700876
#> converged
#> This is Run number 37
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.7042745 1.71020923 1.1542745 -10.8897908 1
#> 2 1 -0.95 -2.35 0.8188401 1.73055549 -0.1311599 -0.6194445 1
#> 3 1 -6.20 -2.30 0.8142049 0.61972236 -5.3857951 -1.6802776 2
#> 4 1 -13.90 -2.55 1.5539823 2.02942975 -12.3460177 -0.5205703 2
#> 5 1 -14.40 -5.80 0.2413219 -0.01021182 -14.1586781 -5.8102118 2
#> 6 1 -3.60 -1.70 -1.1351223 1.98439698 -4.7351223 0.2843970 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6460 -38300 5875
#> initial value 998.131940
#> iter 2 value 825.550793
#> iter 3 value 816.241328
#> iter 4 value 814.381273
#> iter 5 value 776.815424
#> iter 6 value 768.371424
#> iter 7 value 766.748122
#> iter 8 value 766.708831
#> iter 9 value 766.708730
#> iter 10 value 766.708718
#> iter 10 value 766.708715
#> iter 10 value 766.708711
#> final value 766.708711
#> converged
#> This is Run number 38
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.7138098 -0.6272689 0.1638098 -13.227269 1
#> 2 1 -0.95 -2.35 1.1214789 -0.3768925 0.1714789 -2.726892 1
#> 3 1 -6.20 -2.30 -0.7095841 0.6286292 -6.9095841 -1.671371 2
#> 4 1 -13.90 -2.55 0.6902177 -1.0113477 -13.2097823 -3.561348 2
#> 5 1 -14.40 -5.80 1.0391582 -0.3155666 -13.3608418 -6.115567 2
#> 6 1 -3.60 -1.70 4.6394236 0.6673716 1.0394236 -1.032628 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6240 -38325 6650
#> initial value 998.131940
#> iter 2 value 821.529415
#> iter 3 value 810.144082
#> iter 4 value 808.364363
#> iter 5 value 770.894356
#> iter 6 value 762.425153
#> iter 7 value 760.993309
#> iter 8 value 760.961861
#> iter 9 value 760.961803
#> iter 9 value 760.961803
#> iter 9 value 760.961803
#> final value 760.961803
#> converged
#> This is Run number 39
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.78675832 0.06521298 -1.33675832 -12.5347870 1
#> 2 1 -0.95 -2.35 0.96785957 2.19000495 0.01785957 -0.1599950 1
#> 3 1 -6.20 -2.30 -1.04345527 0.19961485 -7.24345527 -2.1003852 2
#> 4 1 -13.90 -2.55 -0.04306056 -0.68188404 -13.94306056 -3.2318840 2
#> 5 1 -14.40 -5.80 3.13787860 -0.01945734 -11.26212140 -5.8194573 2
#> 6 1 -3.60 -1.70 0.29463320 1.46263966 -3.30536680 -0.2373603 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6580 -37625 7150
#> initial value 998.131940
#> iter 2 value 828.350273
#> iter 3 value 818.368201
#> iter 4 value 818.098898
#> iter 5 value 778.265521
#> iter 6 value 769.940285
#> iter 7 value 768.529884
#> iter 8 value 768.500721
#> iter 9 value 768.500664
#> iter 10 value 768.500647
#> iter 10 value 768.500637
#> iter 10 value 768.500631
#> final value 768.500631
#> converged
#> This is Run number 40
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 5.64420497 -0.3499432 5.094205 -12.9499432 1
#> 2 1 -0.95 -2.35 -0.87913942 -0.1768537 -1.829139 -2.5268537 1
#> 3 1 -6.20 -2.30 0.18467297 1.7994440 -6.015327 -0.5005560 2
#> 4 1 -13.90 -2.55 0.55369332 1.8287463 -13.346307 -0.7212537 2
#> 5 1 -14.40 -5.80 0.40074217 0.1881833 -13.999258 -5.6118167 2
#> 6 1 -3.60 -1.70 -0.05689137 -0.7171636 -3.656891 -2.4171636 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5780 -37300 7100
#> initial value 998.131940
#> iter 2 value 833.572147
#> iter 3 value 821.535543
#> iter 4 value 819.669924
#> iter 5 value 779.354791
#> iter 6 value 771.141273
#> iter 7 value 769.789226
#> iter 8 value 769.763318
#> iter 9 value 769.763279
#> iter 9 value 769.763268
#> iter 9 value 769.763262
#> final value 769.763262
#> converged
#> This is Run number 41
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.71344109 -0.61904602 0.1634411 -13.2190460 1
#> 2 1 -0.95 -2.35 -0.77153748 2.68346729 -1.7215375 0.3334673 2
#> 3 1 -6.20 -2.30 0.77589563 1.10408139 -5.4241044 -1.1959186 2
#> 4 1 -13.90 -2.55 2.34094934 1.97225981 -11.5590507 -0.5777402 2
#> 5 1 -14.40 -5.80 -1.14422438 1.35972356 -15.5442244 -4.4402764 2
#> 6 1 -3.60 -1.70 0.06537586 0.04048977 -3.5346241 -1.6595102 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6540 -38450 6950
#> initial value 998.131940
#> iter 2 value 817.889984
#> iter 3 value 806.904123
#> iter 4 value 806.075294
#> iter 5 value 768.711924
#> iter 6 value 760.208173
#> iter 7 value 758.803017
#> iter 8 value 758.772441
#> iter 9 value 758.772384
#> iter 10 value 758.772369
#> iter 10 value 758.772359
#> iter 10 value 758.772359
#> final value 758.772359
#> converged
#> This is Run number 42
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.66879038 0.4249742 0.1187904 -12.1750258 1
#> 2 1 -0.95 -2.35 1.27022437 -0.3186559 0.3202244 -2.6686559 1
#> 3 1 -6.20 -2.30 3.49196275 0.4859582 -2.7080373 -1.8140418 2
#> 4 1 -13.90 -2.55 0.06579049 0.8237347 -13.8342095 -1.7262653 2
#> 5 1 -14.40 -5.80 -0.35180520 -0.9315576 -14.7518052 -6.7315576 2
#> 6 1 -3.60 -1.70 -0.10000316 1.5322635 -3.7000032 -0.1677365 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6320 -39650 7725
#> initial value 998.131940
#> iter 2 value 795.642293
#> iter 3 value 779.625121
#> iter 4 value 778.030535
#> iter 5 value 744.673312
#> iter 6 value 736.094145
#> iter 7 value 734.934048
#> iter 8 value 734.913266
#> iter 8 value 734.913257
#> final value 734.913257
#> converged
#> This is Run number 43
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.79728459 0.6615376 1.2472846 -11.9384624 1
#> 2 1 -0.95 -2.35 0.69384936 0.7528065 -0.2561506 -1.5971935 1
#> 3 1 -6.20 -2.30 0.09488667 -0.2946189 -6.1051133 -2.5946189 2
#> 4 1 -13.90 -2.55 -0.17879059 0.2140843 -14.0787906 -2.3359157 2
#> 5 1 -14.40 -5.80 0.20991343 2.4000887 -14.1900866 -3.3999113 2
#> 6 1 -3.60 -1.70 0.80539326 0.9928431 -2.7946067 -0.7071569 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6240 -39925 6900
#> initial value 998.131940
#> iter 2 value 796.234974
#> iter 3 value 780.987785
#> iter 4 value 777.914120
#> iter 5 value 745.620412
#> iter 6 value 736.936690
#> iter 7 value 735.696435
#> iter 8 value 735.669800
#> iter 9 value 735.669767
#> iter 9 value 735.669760
#> iter 9 value 735.669756
#> final value 735.669756
#> converged
#> This is Run number 44
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.15137793 -0.2996835 1.601378 -12.8996835 1
#> 2 1 -0.95 -2.35 2.20135275 2.6315006 1.251353 0.2815006 1
#> 3 1 -6.20 -2.30 -0.44624093 1.2011576 -6.646241 -1.0988424 2
#> 4 1 -13.90 -2.55 -0.92385415 0.3782121 -14.823854 -2.1717879 2
#> 5 1 -14.40 -5.80 0.75980472 -0.1540351 -13.640195 -5.9540351 2
#> 6 1 -3.60 -1.70 -0.01342134 0.6343489 -3.613421 -1.0656511 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5800 -39325 7200
#> initial value 998.131940
#> iter 2 value 803.937680
#> iter 3 value 786.970750
#> iter 4 value 783.227340
#> iter 5 value 749.361634
#> iter 6 value 740.778429
#> iter 7 value 739.562344
#> iter 8 value 739.538702
#> iter 9 value 739.538679
#> iter 9 value 739.538673
#> iter 9 value 739.538669
#> final value 739.538669
#> converged
#> This is Run number 45
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.2268981 0.52156093 1.6768981 -12.078439 1
#> 2 1 -0.95 -2.35 1.1853668 0.57665505 0.2353668 -1.773345 1
#> 3 1 -6.20 -2.30 1.8662031 -1.16877987 -4.3337969 -3.468780 2
#> 4 1 -13.90 -2.55 1.8871877 0.26783324 -12.0128123 -2.282167 2
#> 5 1 -14.40 -5.80 2.1544772 -0.06336121 -12.2455228 -5.863361 2
#> 6 1 -3.60 -1.70 -0.8812035 -0.01736191 -4.4812035 -1.717362 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6740 -38750 6250
#> initial value 998.131940
#> iter 2 value 816.998406
#> iter 3 value 807.551852
#> iter 4 value 806.444364
#> iter 5 value 769.928505
#> iter 6 value 761.376496
#> iter 7 value 759.822928
#> iter 8 value 759.785233
#> iter 9 value 759.785144
#> iter 10 value 759.785131
#> iter 10 value 759.785124
#> iter 10 value 759.785122
#> final value 759.785122
#> converged
#> This is Run number 46
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.0752339 3.5760596 1.5252339 -9.0239404 1
#> 2 1 -0.95 -2.35 0.8326241 -0.7056624 -0.1173759 -3.0556624 1
#> 3 1 -6.20 -2.30 -1.2166153 1.7291134 -7.4166153 -0.5708866 2
#> 4 1 -13.90 -2.55 0.6362095 1.3768847 -13.2637905 -1.1731153 2
#> 5 1 -14.40 -5.80 -0.9054315 0.3000937 -15.3054315 -5.4999063 2
#> 6 1 -3.60 -1.70 0.2473169 1.1548039 -3.3526831 -0.5451961 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6280 -38300 7300
#> initial value 998.131940
#> iter 2 value 818.263020
#> iter 3 value 805.890818
#> iter 4 value 804.812583
#> iter 5 value 767.149205
#> iter 6 value 758.688534
#> iter 7 value 757.361049
#> iter 8 value 757.334486
#> iter 9 value 757.334446
#> iter 10 value 757.334433
#> iter 10 value 757.334423
#> iter 10 value 757.334416
#> final value 757.334416
#> converged
#> This is Run number 47
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.002738357 -0.10609074 -0.5527384 -12.70609074 1
#> 2 1 -0.95 -2.35 -1.106705668 2.26787135 -2.0567057 -0.08212865 2
#> 3 1 -6.20 -2.30 0.866482793 0.07076876 -5.3335172 -2.22923124 2
#> 4 1 -13.90 -2.55 -0.515772589 5.44155689 -14.4157726 2.89155689 2
#> 5 1 -14.40 -5.80 2.332070612 -0.22660395 -12.0679294 -6.02660395 2
#> 6 1 -3.60 -1.70 -0.294911813 3.35509553 -3.8949118 1.65509553 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7060 -40100 6825
#> initial value 998.131940
#> iter 2 value 793.158459
#> iter 3 value 781.454262
#> iter 4 value 780.714280
#> iter 5 value 748.201439
#> iter 6 value 739.441585
#> iter 7 value 738.110261
#> iter 8 value 738.078954
#> iter 9 value 738.078898
#> iter 10 value 738.078885
#> iter 10 value 738.078877
#> iter 10 value 738.078870
#> final value 738.078870
#> converged
#> This is Run number 48
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.9371712 -0.49542166 2.387171 -13.0954217 1
#> 2 1 -0.95 -2.35 -0.1214152 0.74815949 -1.071415 -1.6018405 1
#> 3 1 -6.20 -2.30 -0.1583219 -0.15883663 -6.358322 -2.4588366 2
#> 4 1 -13.90 -2.55 2.1187215 0.02039968 -11.781279 -2.5296003 2
#> 5 1 -14.40 -5.80 -1.4620323 2.24545905 -15.862032 -3.5545409 2
#> 6 1 -3.60 -1.70 0.5090615 1.32945124 -3.090938 -0.3705488 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5960 -37900 6725
#> initial value 998.131940
#> iter 2 value 827.293699
#> iter 3 value 815.341660
#> iter 4 value 813.156383
#> iter 5 value 774.601331
#> iter 6 value 766.229112
#> iter 7 value 764.822091
#> iter 8 value 764.792688
#> iter 9 value 764.792638
#> iter 9 value 764.792628
#> iter 9 value 764.792622
#> final value 764.792622
#> converged
#> This is Run number 49
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.8564031 0.7850111 0.3064031 -11.814989 1
#> 2 1 -0.95 -2.35 0.6465253 -0.2390917 -0.3034747 -2.589092 1
#> 3 1 -6.20 -2.30 0.0358460 3.6958055 -6.1641540 1.395806 2
#> 4 1 -13.90 -2.55 -0.8363841 1.3921845 -14.7363841 -1.157815 2
#> 5 1 -14.40 -5.80 1.3140880 0.0114584 -13.0859120 -5.788542 2
#> 6 1 -3.60 -1.70 0.8793345 -0.8890097 -2.7206655 -2.589010 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5920 -38175 7275
#> initial value 998.131940
#> iter 2 value 820.374861
#> iter 3 value 806.770309
#> iter 4 value 804.742841
#> iter 5 value 766.995619
#> iter 6 value 758.579463
#> iter 7 value 757.271294
#> iter 8 value 757.245909
#> iter 9 value 757.245876
#> iter 9 value 757.245865
#> iter 9 value 757.245859
#> final value 757.245859
#> converged
#> This is Run number 50
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.0705900 5.1100053 -1.620590 -7.4899947 1
#> 2 1 -0.95 -2.35 -1.1243438 2.1529982 -2.074344 -0.1970018 2
#> 3 1 -6.20 -2.30 -0.4195396 0.3477998 -6.619540 -1.9522002 2
#> 4 1 -13.90 -2.55 0.3434726 1.9679806 -13.556527 -0.5820194 2
#> 5 1 -14.40 -5.80 -0.1494952 -0.4306518 -14.549495 -6.2306518 2
#> 6 1 -3.60 -1.70 0.6583265 1.2582679 -2.941673 -0.4417321 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6420 -38975 6775
#> initial value 998.131940
#> iter 2 value 811.262900
#> iter 3 value 799.195027
#> iter 4 value 797.529397
#> iter 5 value 761.935076
#> iter 6 value 753.338990
#> iter 7 value 751.954330
#> iter 8 value 751.923408
#> iter 9 value 751.923355
#> iter 10 value 751.923343
#> iter 10 value 751.923335
#> iter 10 value 751.923335
#> final value 751.923335
#> converged
#> This is Run number 51
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.1734721 4.0768734 -0.7234721 -8.523127 1
#> 2 1 -0.95 -2.35 -0.5763385 1.2462055 -1.5263385 -1.103794 2
#> 3 1 -6.20 -2.30 0.2401681 -0.1925522 -5.9598319 -2.492552 2
#> 4 1 -13.90 -2.55 -1.0784556 -0.4946384 -14.9784556 -3.044638 2
#> 5 1 -14.40 -5.80 0.9013395 0.6825405 -13.4986605 -5.117459 2
#> 6 1 -3.60 -1.70 2.3287621 -0.6088609 -1.2712379 -2.308861 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5940 -38350 6625
#> initial value 998.131940
#> iter 2 value 821.439197
#> iter 3 value 808.514081
#> iter 4 value 805.738817
#> iter 5 value 768.627081
#> iter 6 value 760.142531
#> iter 7 value 758.744908
#> iter 8 value 758.714885
#> iter 9 value 758.714834
#> iter 9 value 758.714825
#> iter 9 value 758.714820
#> final value 758.714820
#> converged
#> This is Run number 52
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.21332141 0.6115616 -0.7633214 -11.988438 1
#> 2 1 -0.95 -2.35 -0.06550073 -0.2540718 -1.0155007 -2.604072 1
#> 3 1 -6.20 -2.30 -0.47778568 0.6458479 -6.6777857 -1.654152 2
#> 4 1 -13.90 -2.55 0.26206233 -0.5363866 -13.6379377 -3.086387 2
#> 5 1 -14.40 -5.80 -1.28305421 -0.9505438 -15.6830542 -6.750544 2
#> 6 1 -3.60 -1.70 -0.03367503 3.4157704 -3.6336750 1.715770 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5600 -37700 6850
#> initial value 998.131940
#> iter 2 value 829.488034
#> iter 3 value 815.880643
#> iter 4 value 812.851747
#> iter 5 value 773.954597
#> iter 6 value 765.620054
#> iter 7 value 764.262927
#> iter 8 value 764.236153
#> iter 9 value 764.236115
#> iter 9 value 764.236106
#> iter 9 value 764.236102
#> final value 764.236102
#> converged
#> This is Run number 53
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.5840847 -0.53130286 1.03408467 -13.1313029 1
#> 2 1 -0.95 -2.35 0.9671002 0.57240380 0.01710017 -1.7775962 1
#> 3 1 -6.20 -2.30 1.1787649 -0.04038893 -5.02123513 -2.3403889 2
#> 4 1 -13.90 -2.55 0.5168136 0.74795404 -13.38318641 -1.8020460 2
#> 5 1 -14.40 -5.80 0.0269467 2.70764331 -14.37305330 -3.0923567 2
#> 6 1 -3.60 -1.70 2.1059306 0.91435411 -1.49406938 -0.7856459 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5860 -38500 7325
#> initial value 998.131940
#> iter 2 value 815.434675
#> iter 3 value 800.680455
#> iter 4 value 798.200804
#> iter 5 value 761.549803
#> iter 6 value 753.081569
#> iter 7 value 751.804646
#> iter 8 value 751.780141
#> iter 9 value 751.780113
#> iter 9 value 751.780103
#> iter 9 value 751.780098
#> final value 751.780098
#> converged
#> This is Run number 54
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.1226000 0.48452969 -1.6726000 -12.115470 1
#> 2 1 -0.95 -2.35 0.5041335 -0.51810840 -0.4458665 -2.868108 1
#> 3 1 -6.20 -2.30 0.2347791 1.99681704 -5.9652209 -0.303183 2
#> 4 1 -13.90 -2.55 0.4909746 -0.08782500 -13.4090254 -2.637825 2
#> 5 1 -14.40 -5.80 -1.0817428 0.09356892 -15.4817428 -5.706431 2
#> 6 1 -3.60 -1.70 -0.1716076 0.47813314 -3.7716076 -1.221867 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6640 -38100 7375
#> initial value 998.131940
#> iter 2 value 820.359070
#> iter 3 value 809.234542
#> iter 4 value 808.981016
#> iter 5 value 770.540398
#> iter 6 value 762.092484
#> iter 7 value 760.737481
#> iter 8 value 760.710046
#> iter 9 value 760.709998
#> iter 10 value 760.709983
#> iter 10 value 760.709974
#> iter 10 value 760.709966
#> final value 760.709966
#> converged
#> This is Run number 55
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.9081562 2.42970564 2.3581562 -10.170294 1
#> 2 1 -0.95 -2.35 0.3418053 -0.02434984 -0.6081947 -2.374350 1
#> 3 1 -6.20 -2.30 -0.5075199 -0.67135129 -6.7075199 -2.971351 2
#> 4 1 -13.90 -2.55 0.3120520 -0.21792546 -13.5879480 -2.767925 2
#> 5 1 -14.40 -5.80 0.2889016 0.88446951 -14.1110984 -4.915530 2
#> 6 1 -3.60 -1.70 0.3922307 0.33060741 -3.2077693 -1.369393 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5660 -36700 7575
#> initial value 998.131940
#> iter 2 value 838.829533
#> iter 3 value 826.877525
#> iter 4 value 825.526432
#> iter 5 value 783.392655
#> iter 6 value 775.339955
#> iter 7 value 774.050023
#> iter 8 value 774.027792
#> iter 9 value 774.027762
#> iter 9 value 774.027751
#> iter 9 value 774.027745
#> final value 774.027745
#> converged
#> This is Run number 56
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.002726308 -0.4310971 -0.5472737 -13.03109715 1
#> 2 1 -0.95 -2.35 0.029817228 0.1321433 -0.9201828 -2.21785665 1
#> 3 1 -6.20 -2.30 0.852524470 2.2600634 -5.3474755 -0.03993665 2
#> 4 1 -13.90 -2.55 -0.387014032 0.1709590 -14.2870140 -2.37904103 2
#> 5 1 -14.40 -5.80 -1.619565647 1.4339483 -16.0195656 -4.36605167 2
#> 6 1 -3.60 -1.70 -0.864710967 3.0335322 -4.4647110 1.33353222 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7200 -40600 6275
#> initial value 998.131940
#> iter 2 value 787.877907
#> iter 3 value 777.147900
#> iter 4 value 775.935444
#> iter 5 value 744.967575
#> iter 6 value 736.153199
#> iter 7 value 734.751407
#> iter 8 value 734.714794
#> iter 9 value 734.714716
#> iter 9 value 734.714705
#> iter 9 value 734.714697
#> final value 734.714697
#> converged
#> This is Run number 57
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.9945020 0.520600487 0.444502 -12.079400 1
#> 2 1 -0.95 -2.35 -0.1858918 0.007004588 -1.135892 -2.342995 1
#> 3 1 -6.20 -2.30 -0.2102867 -0.641286324 -6.410287 -2.941286 2
#> 4 1 -13.90 -2.55 3.7337388 -0.089307883 -10.166261 -2.639308 2
#> 5 1 -14.40 -5.80 0.2335292 -0.627732068 -14.166471 -6.427732 2
#> 6 1 -3.60 -1.70 -0.3792656 1.148182025 -3.979266 -0.551818 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6760 -40025 7000
#> initial value 998.131940
#> iter 2 value 793.717902
#> iter 3 value 780.617740
#> iter 4 value 779.324508
#> iter 5 value 746.808653
#> iter 6 value 738.088269
#> iter 7 value 736.817074
#> iter 8 value 736.788971
#> iter 9 value 736.788931
#> iter 9 value 736.788920
#> iter 9 value 736.788913
#> final value 736.788913
#> converged
#> This is Run number 58
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.4571985 1.3058410927 -0.09280151 -11.294159 1
#> 2 1 -0.95 -2.35 -0.1937811 -1.0521658995 -1.14378108 -3.402166 1
#> 3 1 -6.20 -2.30 -0.9002293 -0.3171285445 -7.10022930 -2.617129 2
#> 4 1 -13.90 -2.55 2.0540424 -0.0008984213 -11.84595755 -2.550898 2
#> 5 1 -14.40 -5.80 1.2539520 0.2071496298 -13.14604797 -5.592850 2
#> 6 1 -3.60 -1.70 0.1663033 -0.2220928603 -3.43369670 -1.922093 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6520 -38425 6300
#> initial value 998.131940
#> iter 2 value 821.677556
#> iter 3 value 811.847539
#> iter 4 value 810.449793
#> iter 5 value 773.105717
#> iter 6 value 764.621464
#> iter 7 value 763.090220
#> iter 8 value 763.054354
#> iter 9 value 763.054274
#> iter 10 value 763.054262
#> iter 10 value 763.054255
#> iter 10 value 763.054252
#> final value 763.054252
#> converged
#> This is Run number 59
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.43597779 1.56527902 -0.9859778 -11.034721 1
#> 2 1 -0.95 -2.35 3.85699231 0.06030084 2.9069923 -2.289699 1
#> 3 1 -6.20 -2.30 0.28358072 0.33147899 -5.9164193 -1.968521 2
#> 4 1 -13.90 -2.55 -0.23075292 0.17126672 -14.1307529 -2.378733 2
#> 5 1 -14.40 -5.80 0.09154495 1.70106369 -14.3084551 -4.098936 2
#> 6 1 -3.60 -1.70 1.08872305 -0.50416569 -2.5112770 -2.204166 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6380 -38125 6675
#> initial value 998.131940
#> iter 2 value 824.153085
#> iter 3 value 813.691828
#> iter 4 value 812.473636
#> iter 5 value 774.255517
#> iter 6 value 765.832548
#> iter 7 value 764.377969
#> iter 8 value 764.345990
#> iter 9 value 764.345928
#> iter 9 value 764.345928
#> iter 9 value 764.345928
#> final value 764.345928
#> converged
#> This is Run number 60
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.2508201 -0.3734890 -0.2991799 -12.973489 1
#> 2 1 -0.95 -2.35 -1.3414033 -0.5180348 -2.2914033 -2.868035 1
#> 3 1 -6.20 -2.30 4.8701170 0.1663493 -1.3298830 -2.133651 1
#> 4 1 -13.90 -2.55 2.8363642 2.9052270 -11.0636358 0.355227 2
#> 5 1 -14.40 -5.80 -0.1019067 1.4269929 -14.5019067 -4.373007 2
#> 6 1 -3.60 -1.70 -0.2679252 0.5507058 -3.8679252 -1.149294 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5680 -38625 6500
#> initial value 998.131940
#> iter 2 value 818.145445
#> iter 3 value 803.059787
#> iter 4 value 798.995026
#> iter 5 value 762.916691
#> iter 6 value 754.331446
#> iter 7 value 752.976540
#> iter 8 value 752.947464
#> iter 9 value 752.947416
#> iter 9 value 752.947407
#> iter 9 value 752.947403
#> final value 752.947403
#> converged
#> This is Run number 61
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.14092514 1.0831714 -0.6909251 -11.516829 1
#> 2 1 -0.95 -2.35 -0.08381742 -1.7439245 -1.0338174 -4.093924 1
#> 3 1 -6.20 -2.30 -0.42034058 0.8241373 -6.6203406 -1.475863 2
#> 4 1 -13.90 -2.55 3.81712748 -0.3536398 -10.0828725 -2.903640 2
#> 5 1 -14.40 -5.80 0.08110513 1.2564924 -14.3188949 -4.543508 2
#> 6 1 -3.60 -1.70 2.12373749 -0.3276367 -1.4762625 -2.027637 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6140 -38550 7450
#> initial value 998.131940
#> iter 2 value 813.862286
#> iter 3 value 800.098676
#> iter 4 value 798.591095
#> iter 5 value 761.819604
#> iter 6 value 753.332299
#> iter 7 value 752.054468
#> iter 8 value 752.029896
#> iter 9 value 752.029865
#> iter 9 value 752.029854
#> iter 9 value 752.029847
#> final value 752.029847
#> converged
#> This is Run number 62
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.3758963 -0.43300879 -0.1741037 -13.0330088 1
#> 2 1 -0.95 -2.35 0.6072881 -0.06120956 -0.3427119 -2.4112096 1
#> 3 1 -6.20 -2.30 1.9644980 0.88644384 -4.2355020 -1.4135562 2
#> 4 1 -13.90 -2.55 -0.8964901 1.33120664 -14.7964901 -1.2187934 2
#> 5 1 -14.40 -5.80 -0.9474455 1.23384735 -15.3474455 -4.5661526 2
#> 6 1 -3.60 -1.70 -0.3889098 2.14841735 -3.9889098 0.4484173 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7160 -40725 6900
#> initial value 998.131940
#> iter 2 value 782.639395
#> iter 3 value 770.073151
#> iter 4 value 769.243252
#> iter 5 value 738.689303
#> iter 6 value 729.908723
#> iter 7 value 728.669815
#> iter 8 value 728.641377
#> iter 9 value 728.641335
#> iter 9 value 728.641324
#> iter 9 value 728.641316
#> final value 728.641316
#> converged
#> This is Run number 63
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.09708567 0.22972358 -0.4529143 -12.3702764 1
#> 2 1 -0.95 -2.35 -0.28340339 0.90102124 -1.2334034 -1.4489788 1
#> 3 1 -6.20 -2.30 -0.72245935 1.42273912 -6.9224594 -0.8772609 2
#> 4 1 -13.90 -2.55 -0.26040919 -0.55923959 -14.1604092 -3.1092396 2
#> 5 1 -14.40 -5.80 5.96485406 -0.04564194 -8.4351459 -5.8456419 2
#> 6 1 -3.60 -1.70 0.77720827 1.06356686 -2.8227917 -0.6364331 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5540 -37050 6825
#> initial value 998.131940
#> iter 2 value 838.484488
#> iter 3 value 826.128444
#> iter 4 value 823.520020
#> iter 5 value 782.698589
#> iter 6 value 774.543489
#> iter 7 value 773.173324
#> iter 8 value 773.147130
#> iter 9 value 773.147091
#> iter 9 value 773.147082
#> iter 9 value 773.147078
#> final value 773.147078
#> converged
#> This is Run number 64
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.9645116 0.66883180 -1.5145116 -11.9311682 1
#> 2 1 -0.95 -2.35 1.3703464 0.50142487 0.4203464 -1.8485751 1
#> 3 1 -6.20 -2.30 2.4423214 -0.55877465 -3.7576786 -2.8587746 2
#> 4 1 -13.90 -2.55 0.9106932 -0.06069489 -12.9893068 -2.6106949 2
#> 5 1 -14.40 -5.80 0.7759955 5.06427833 -13.6240045 -0.7357217 2
#> 6 1 -3.60 -1.70 1.5890401 1.53529954 -2.0109599 -0.1647005 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6400 -38375 6575
#> initial value 998.131940
#> iter 2 value 821.095508
#> iter 3 value 810.427510
#> iter 4 value 808.992492
#> iter 5 value 771.547059
#> iter 6 value 763.067506
#> iter 7 value 761.604698
#> iter 8 value 761.571795
#> iter 9 value 761.571730
#> iter 9 value 761.571729
#> iter 9 value 761.571729
#> final value 761.571729
#> converged
#> This is Run number 65
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.2704263 3.37310339 0.7204263 -9.226897 1
#> 2 1 -0.95 -2.35 -0.3886616 0.08641257 -1.3386616 -2.263587 1
#> 3 1 -6.20 -2.30 0.9599140 0.79382039 -5.2400860 -1.506180 2
#> 4 1 -13.90 -2.55 0.1436504 1.29666697 -13.7563496 -1.253333 2
#> 5 1 -14.40 -5.80 1.0584448 0.70018071 -13.3415552 -5.099819 2
#> 6 1 -3.60 -1.70 -0.9948526 3.43193013 -4.5948526 1.731930 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7500 -39325 5525
#> initial value 998.131940
#> iter 2 value 810.778554
#> iter 3 value 804.127351
#> iter 4 value 803.725034
#> iter 5 value 768.530008
#> iter 6 value 759.937831
#> iter 7 value 758.112106
#> iter 8 value 758.061529
#> iter 9 value 758.061358
#> iter 10 value 758.061342
#> iter 10 value 758.061342
#> iter 10 value 758.061336
#> final value 758.061336
#> converged
#> This is Run number 66
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.94274035 1.0587750 -1.492740 -11.5412250 1
#> 2 1 -0.95 -2.35 -0.50325596 0.5223148 -1.453256 -1.8276852 1
#> 3 1 -6.20 -2.30 0.85593397 1.1380797 -5.344066 -1.1619203 2
#> 4 1 -13.90 -2.55 0.90895125 0.5227077 -12.991049 -2.0272923 2
#> 5 1 -14.40 -5.80 0.05103792 1.1640035 -14.348962 -4.6359965 2
#> 6 1 -3.60 -1.70 -0.97035454 1.5549439 -4.570355 -0.1450561 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6340 -40375 7175
#> initial value 998.131940
#> iter 2 value 787.535400
#> iter 3 value 771.277229
#> iter 4 value 768.428218
#> iter 5 value 737.516024
#> iter 6 value 728.858032
#> iter 7 value 727.703811
#> iter 8 value 727.680519
#> iter 9 value 727.680498
#> iter 9 value 727.680492
#> iter 9 value 727.680488
#> final value 727.680488
#> converged
#> This is Run number 67
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.2173684 -0.3451926 1.667368 -12.945193 1
#> 2 1 -0.95 -2.35 -0.4137732 -0.3473576 -1.363773 -2.697358 1
#> 3 1 -6.20 -2.30 -1.0058077 0.3302565 -7.205808 -1.969743 2
#> 4 1 -13.90 -2.55 -0.2291413 -0.4238604 -14.129141 -2.973860 2
#> 5 1 -14.40 -5.80 -0.1175618 1.4433230 -14.517562 -4.356677 2
#> 6 1 -3.60 -1.70 2.3114642 0.6781493 -1.288536 -1.021851 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6300 -40450 6625
#> initial value 998.131940
#> iter 2 value 789.365128
#> iter 3 value 773.698035
#> iter 4 value 769.900117
#> iter 5 value 739.331998
#> iter 6 value 730.592069
#> iter 7 value 729.375716
#> iter 8 value 729.348246
#> iter 9 value 729.348207
#> iter 9 value 729.348202
#> iter 9 value 729.348197
#> final value 729.348197
#> converged
#> This is Run number 68
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.9237850 0.3464801 1.373785 -12.253520 1
#> 2 1 -0.95 -2.35 2.1097690 0.8237414 1.159769 -1.526259 1
#> 3 1 -6.20 -2.30 0.6987535 0.4687134 -5.501246 -1.831287 2
#> 4 1 -13.90 -2.55 2.0057769 0.9240380 -11.894223 -1.625962 2
#> 5 1 -14.40 -5.80 -0.9823895 -0.8427107 -15.382389 -6.642711 2
#> 6 1 -3.60 -1.70 1.4806043 -0.5814357 -2.119396 -2.281436 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5980 -37975 7475
#> initial value 998.131940
#> iter 2 value 822.009027
#> iter 3 value 808.751339
#> iter 4 value 807.252887
#> iter 5 value 768.791592
#> iter 6 value 760.417338
#> iter 7 value 759.122939
#> iter 8 value 759.098674
#> iter 9 value 759.098642
#> iter 10 value 759.098630
#> iter 10 value 759.098621
#> iter 10 value 759.098615
#> final value 759.098615
#> converged
#> This is Run number 69
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.2831594 -0.1999130 -0.2668406 -12.7999130 1
#> 2 1 -0.95 -2.35 0.4834013 -0.2763667 -0.4665987 -2.6263667 1
#> 3 1 -6.20 -2.30 1.1292655 1.5569049 -5.0707345 -0.7430951 2
#> 4 1 -13.90 -2.55 1.0461758 0.6917944 -12.8538242 -1.8582056 2
#> 5 1 -14.40 -5.80 1.4374732 -1.6730457 -12.9625268 -7.4730457 2
#> 6 1 -3.60 -1.70 1.0482825 4.2943994 -2.5517175 2.5943994 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7280 -40550 6250
#> initial value 998.131940
#> iter 2 value 788.693308
#> iter 3 value 778.388955
#> iter 4 value 777.399561
#> iter 5 value 746.195610
#> iter 6 value 737.380478
#> iter 7 value 735.951866
#> iter 8 value 735.914177
#> iter 9 value 735.914093
#> iter 10 value 735.914081
#> iter 10 value 735.914076
#> iter 10 value 735.914069
#> final value 735.914069
#> converged
#> This is Run number 70
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.98806493 1.14983111 2.4380649 -11.4501689 1
#> 2 1 -0.95 -2.35 1.31764356 0.70060328 0.3676436 -1.6493967 1
#> 3 1 -6.20 -2.30 0.27133930 2.84941387 -5.9286607 0.5494139 2
#> 4 1 -13.90 -2.55 -0.38386691 0.09670359 -14.2838669 -2.4532964 2
#> 5 1 -14.40 -5.80 -0.19966443 0.67225741 -14.5996644 -5.1277426 2
#> 6 1 -3.60 -1.70 0.05103394 0.68438236 -3.5489661 -1.0156176 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7360 -40125 5975
#> initial value 998.131940
#> iter 2 value 796.656315
#> iter 3 value 787.797068
#> iter 4 value 787.032502
#> iter 5 value 754.410469
#> iter 6 value 745.639165
#> iter 7 value 744.060553
#> iter 8 value 744.017332
#> iter 9 value 744.017216
#> iter 10 value 744.017202
#> iter 10 value 744.017197
#> iter 10 value 744.017190
#> final value 744.017190
#> converged
#> This is Run number 71
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.9558678 -0.28590425 1.40586777 -12.8859043 1
#> 2 1 -0.95 -2.35 0.9939595 -0.47121844 0.04395947 -2.8212184 1
#> 3 1 -6.20 -2.30 1.3622489 2.04312783 -4.83775108 -0.2568722 2
#> 4 1 -13.90 -2.55 0.8113508 6.91967651 -13.08864923 4.3696765 2
#> 5 1 -14.40 -5.80 1.3510047 0.06870411 -13.04899526 -5.7312959 2
#> 6 1 -3.60 -1.70 -2.0749149 -0.35809217 -5.67491489 -2.0580922 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5840 -38800 7350
#> initial value 998.131940
#> iter 2 value 810.909720
#> iter 3 value 795.271293
#> iter 4 value 792.441926
#> iter 5 value 756.788568
#> iter 6 value 748.279850
#> iter 7 value 747.029721
#> iter 8 value 747.005883
#> iter 9 value 747.005858
#> iter 9 value 747.005849
#> iter 9 value 747.005844
#> final value 747.005844
#> converged
#> This is Run number 72
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.68005206 0.51367898 -1.230052 -12.086321 1
#> 2 1 -0.95 -2.35 3.89628108 -0.02885329 2.946281 -2.378853 1
#> 3 1 -6.20 -2.30 0.62907324 -1.11398545 -5.570927 -3.413985 2
#> 4 1 -13.90 -2.55 -1.17330829 -0.17502990 -15.073308 -2.725030 2
#> 5 1 -14.40 -5.80 1.83859271 -0.29812469 -12.561407 -6.098125 2
#> 6 1 -3.60 -1.70 -0.08773535 -0.55055796 -3.687735 -2.250558 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5640 -38375 7200
#> initial value 998.131940
#> iter 2 value 817.996336
#> iter 3 value 802.495944
#> iter 4 value 799.232143
#> iter 5 value 762.401709
#> iter 6 value 753.947707
#> iter 7 value 752.666703
#> iter 8 value 752.642195
#> iter 9 value 752.642168
#> iter 9 value 752.642159
#> iter 9 value 752.642155
#> final value 752.642155
#> converged
#> This is Run number 73
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.0637934 0.8624431 0.5137934 -11.7375569 1
#> 2 1 -0.95 -2.35 0.6601374 -0.7218626 -0.2898626 -3.0718626 1
#> 3 1 -6.20 -2.30 -0.8427415 0.5771343 -7.0427415 -1.7228657 2
#> 4 1 -13.90 -2.55 1.6078021 0.4439846 -12.2921979 -2.1060154 2
#> 5 1 -14.40 -5.80 0.1739378 -0.2364939 -14.2260622 -6.0364939 2
#> 6 1 -3.60 -1.70 1.1675201 1.0402617 -2.4324799 -0.6597383 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6780 -38900 6825
#> initial value 998.131940
#> iter 2 value 811.772035
#> iter 3 value 801.083775
#> iter 4 value 800.422025
#> iter 5 value 764.297307
#> iter 6 value 755.700620
#> iter 7 value 754.275055
#> iter 8 value 754.242478
#> iter 9 value 754.242413
#> iter 10 value 754.242398
#> iter 10 value 754.242388
#> iter 10 value 754.242381
#> final value 754.242381
#> converged
#> This is Run number 74
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.2924840 0.8739020 1.7424840 -11.726098 1
#> 2 1 -0.95 -2.35 0.1284661 -0.1764717 -0.8215339 -2.526472 1
#> 3 1 -6.20 -2.30 1.0086759 0.4222885 -5.1913241 -1.877712 2
#> 4 1 -13.90 -2.55 2.2127638 0.3745331 -11.6872362 -2.175467 2
#> 5 1 -14.40 -5.80 -0.2433684 4.5157374 -14.6433684 -1.284263 2
#> 6 1 -3.60 -1.70 1.1963571 -0.6265572 -2.4036429 -2.326557 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6820 -40325 5425
#> initial value 998.131940
#> iter 2 value 796.625937
#> iter 3 value 785.810638
#> iter 4 value 782.689526
#> iter 5 value 751.417583
#> iter 6 value 742.606890
#> iter 7 value 741.008584
#> iter 8 value 740.961345
#> iter 9 value 740.961168
#> iter 10 value 740.961150
#> iter 10 value 740.961150
#> iter 11 value 740.961138
#> iter 11 value 740.961135
#> iter 11 value 740.961133
#> final value 740.961133
#> converged
#> This is Run number 75
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.7526788 0.7104879 -1.3026788 -11.889512 1
#> 2 1 -0.95 -2.35 1.0967658 1.1902048 0.1467658 -1.159795 1
#> 3 1 -6.20 -2.30 1.2696449 -0.8296046 -4.9303551 -3.129605 2
#> 4 1 -13.90 -2.55 0.4102497 2.8696700 -13.4897503 0.319670 2
#> 5 1 -14.40 -5.80 0.9725670 0.9143179 -13.4274330 -4.885682 2
#> 6 1 -3.60 -1.70 1.5803217 -0.8893010 -2.0196783 -2.589301 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6600 -39500 7300
#> initial value 998.131940
#> iter 2 value 800.275257
#> iter 3 value 786.800005
#> iter 4 value 785.724964
#> iter 5 value 751.632452
#> iter 6 value 742.982749
#> iter 7 value 741.721943
#> iter 8 value 741.695990
#> iter 9 value 741.695955
#> iter 10 value 741.695944
#> iter 10 value 741.695935
#> iter 10 value 741.695928
#> final value 741.695928
#> converged
#> This is Run number 76
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.002203018 1.84932479 -0.5522030 -10.750675 1
#> 2 1 -0.95 -2.35 0.055219473 0.35429777 -0.8947805 -1.995702 1
#> 3 1 -6.20 -2.30 -0.688342460 -0.02749961 -6.8883425 -2.327500 2
#> 4 1 -13.90 -2.55 1.096123941 0.52721483 -12.8038761 -2.022785 2
#> 5 1 -14.40 -5.80 0.887343077 1.54773004 -13.5126569 -4.252270 2
#> 6 1 -3.60 -1.70 0.093306994 0.19990133 -3.5066930 -1.500099 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7380 -39075 6425
#> initial value 998.131940
#> iter 2 value 810.468861
#> iter 3 value 801.910484
#> iter 4 value 801.830183
#> iter 5 value 765.949678
#> iter 6 value 757.354382
#> iter 7 value 755.771362
#> iter 8 value 755.731368
#> iter 9 value 755.731260
#> iter 10 value 755.731242
#> iter 10 value 755.731234
#> iter 10 value 755.731226
#> final value 755.731226
#> converged
#> This is Run number 77
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.1461190 -0.1267509 -0.696119 -12.7267509 1
#> 2 1 -0.95 -2.35 -0.1065639 1.4266081 -1.056564 -0.9233919 2
#> 3 1 -6.20 -2.30 0.8214025 -0.2072795 -5.378598 -2.5072795 2
#> 4 1 -13.90 -2.55 -1.3949348 -1.2271316 -15.294935 -3.7771316 2
#> 5 1 -14.40 -5.80 1.0483308 0.9607808 -13.351669 -4.8392192 2
#> 6 1 -3.60 -1.70 1.4301829 0.2960541 -2.169817 -1.4039459 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6020 -38075 7150
#> initial value 998.131940
#> iter 2 value 822.471399
#> iter 3 value 809.775560
#> iter 4 value 808.022519
#> iter 5 value 769.885747
#> iter 6 value 761.481827
#> iter 7 value 760.141959
#> iter 8 value 760.115221
#> iter 9 value 760.115181
#> iter 10 value 760.115169
#> iter 10 value 760.115160
#> iter 10 value 760.115160
#> final value 760.115160
#> converged
#> This is Run number 78
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.8893032 1.9656623 -1.43930316 -10.634338 1
#> 2 1 -0.95 -2.35 3.3472836 0.4352147 2.39728364 -1.914785 1
#> 3 1 -6.20 -2.30 -0.4710426 -0.6388205 -6.67104263 -2.938821 2
#> 4 1 -13.90 -2.55 0.6830566 -0.3580751 -13.21694344 -2.908075 2
#> 5 1 -14.40 -5.80 -0.1114782 1.2884228 -14.51147819 -4.511577 2
#> 6 1 -3.60 -1.70 3.5861732 0.1459608 -0.01382677 -1.554039 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6520 -40625 6975
#> initial value 998.131940
#> iter 2 value 784.520677
#> iter 3 value 769.116361
#> iter 4 value 766.435370
#> iter 5 value 736.184360
#> iter 6 value 727.483128
#> iter 7 value 726.315096
#> iter 8 value 726.290190
#> iter 9 value 726.290163
#> iter 9 value 726.290163
#> iter 9 value 726.290163
#> final value 726.290163
#> converged
#> This is Run number 79
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.1567705 -0.1169315 -0.7067705 -12.7169315 1
#> 2 1 -0.95 -2.35 1.3874137 0.1202300 0.4374137 -2.2297700 1
#> 3 1 -6.20 -2.30 1.0389011 4.0860144 -5.1610989 1.7860144 2
#> 4 1 -13.90 -2.55 0.9800581 -1.1122798 -12.9199419 -3.6622798 2
#> 5 1 -14.40 -5.80 2.8822508 1.6856565 -11.5177492 -4.1143435 2
#> 6 1 -3.60 -1.70 -0.4873458 2.0758497 -4.0873458 0.3758497 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6280 -39675 6425
#> initial value 998.131940
#> iter 2 value 802.589947
#> iter 3 value 788.890342
#> iter 4 value 785.685694
#> iter 5 value 752.574239
#> iter 6 value 743.859365
#> iter 7 value 742.502476
#> iter 8 value 742.470541
#> iter 9 value 742.470483
#> iter 9 value 742.470475
#> iter 9 value 742.470469
#> final value 742.470469
#> converged
#> This is Run number 80
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.6986578 0.84202093 1.148658 -11.757979 1
#> 2 1 -0.95 -2.35 0.6242290 -0.78962108 -0.325771 -3.139621 1
#> 3 1 -6.20 -2.30 0.4635686 1.13209145 -5.736431 -1.167909 2
#> 4 1 -13.90 -2.55 -0.5302197 0.16731670 -14.430220 -2.382683 2
#> 5 1 -14.40 -5.80 1.3253005 1.37522472 -13.074700 -4.424775 2
#> 6 1 -3.60 -1.70 0.4165892 0.03988974 -3.183411 -1.660110 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6360 -41325 6975
#> initial value 998.131940
#> iter 2 value 773.106087
#> iter 3 value 755.069418
#> iter 4 value 750.865562
#> iter 5 value 723.186784
#> iter 6 value 714.574958
#> iter 7 value 713.534303
#> iter 8 value 713.513225
#> iter 9 value 713.513212
#> iter 9 value 713.513209
#> iter 9 value 713.513206
#> final value 713.513206
#> converged
#> This is Run number 81
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.8857455 0.69194360 2.335746 -11.908056 1
#> 2 1 -0.95 -2.35 -0.4785646 0.15365553 -1.428565 -2.196344 1
#> 3 1 -6.20 -2.30 0.6992334 0.85319884 -5.500767 -1.446801 2
#> 4 1 -13.90 -2.55 0.5870290 0.08244343 -13.312971 -2.467557 2
#> 5 1 -14.40 -5.80 -1.5699970 1.28708053 -15.969997 -4.512919 2
#> 6 1 -3.60 -1.70 -0.4917272 -0.33048189 -4.091727 -2.030482 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6000 -39275 7600
#> initial value 998.131940
#> iter 2 value 802.288107
#> iter 3 value 785.872757
#> iter 4 value 783.411391
#> iter 5 value 749.140416
#> iter 6 value 740.601795
#> iter 7 value 739.410538
#> iter 8 value 739.388807
#> iter 9 value 739.388788
#> iter 9 value 739.388781
#> iter 9 value 739.388780
#> final value 739.388780
#> converged
#> This is Run number 82
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.6815306 -0.4990454 0.1315306 -13.09904539 1
#> 2 1 -0.95 -2.35 -0.2967441 2.4164207 -1.2467441 0.06642072 2
#> 3 1 -6.20 -2.30 0.1689444 0.7661130 -6.0310556 -1.53388699 2
#> 4 1 -13.90 -2.55 0.4964737 1.8496352 -13.4035263 -0.70036480 2
#> 5 1 -14.40 -5.80 0.8407347 1.0421646 -13.5592653 -4.75783541 2
#> 6 1 -3.60 -1.70 -1.2571612 1.8605432 -4.8571612 0.16054320 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6900 -39150 6800
#> initial value 998.131940
#> iter 2 value 808.056514
#> iter 3 value 797.396430
#> iter 4 value 796.824326
#> iter 5 value 761.404299
#> iter 6 value 752.761342
#> iter 7 value 751.337283
#> iter 8 value 751.304138
#> iter 9 value 751.304071
#> iter 10 value 751.304056
#> iter 10 value 751.304046
#> iter 10 value 751.304039
#> final value 751.304039
#> converged
#> This is Run number 83
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.5597245 -1.0562157 -1.109724 -13.6562157 1
#> 2 1 -0.95 -2.35 2.2426874 1.4630482 1.292687 -0.8869518 1
#> 3 1 -6.20 -2.30 -0.1302133 1.6207747 -6.330213 -0.6792253 2
#> 4 1 -13.90 -2.55 2.7377421 0.7494584 -11.162258 -1.8005416 2
#> 5 1 -14.40 -5.80 -0.6496455 -0.6952994 -15.049646 -6.4952994 2
#> 6 1 -3.60 -1.70 -0.4470218 0.6057720 -4.047022 -1.0942280 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6280 -38400 7275
#> initial value 998.131940
#> iter 2 value 816.973242
#> iter 3 value 804.458518
#> iter 4 value 803.292750
#> iter 5 value 765.943703
#> iter 6 value 757.464569
#> iter 7 value 756.138870
#> iter 8 value 756.112181
#> iter 9 value 756.112140
#> iter 10 value 756.112128
#> iter 10 value 756.112118
#> iter 10 value 756.112112
#> final value 756.112112
#> converged
#> This is Run number 84
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.00565409 1.4715000 -0.5556541 -11.1285000 1
#> 2 1 -0.95 -2.35 -0.86209904 -0.8104365 -1.8120990 -3.1604365 1
#> 3 1 -6.20 -2.30 -1.23565575 0.4038228 -7.4356557 -1.8961772 2
#> 4 1 -13.90 -2.55 -0.13403324 4.4855720 -14.0340332 1.9355720 2
#> 5 1 -14.40 -5.80 0.02812253 2.0297037 -14.3718775 -3.7702963 2
#> 6 1 -3.60 -1.70 -0.09737891 2.2596579 -3.6973789 0.5596579 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6620 -39675 6475
#> initial value 998.131940
#> iter 2 value 802.092574
#> iter 3 value 790.123337
#> iter 4 value 788.155126
#> iter 5 value 754.686635
#> iter 6 value 745.975887
#> iter 7 value 744.577068
#> iter 8 value 744.543447
#> iter 9 value 744.543383
#> iter 9 value 744.543373
#> iter 9 value 744.543366
#> final value 744.543366
#> converged
#> This is Run number 85
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.23782935 1.22338909 -0.7878293 -11.3766109 1
#> 2 1 -0.95 -2.35 -0.89027730 0.14954986 -1.8402773 -2.2004501 1
#> 3 1 -6.20 -2.30 0.01225359 2.07308943 -6.1877464 -0.2269106 2
#> 4 1 -13.90 -2.55 -0.56036504 -0.07918101 -14.4603650 -2.6291810 2
#> 5 1 -14.40 -5.80 -0.50471200 -1.03424789 -14.9047120 -6.8342479 2
#> 6 1 -3.60 -1.70 1.39182076 4.74249936 -2.2081792 3.0424994 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6500 -39125 5950
#> initial value 998.131940
#> iter 2 value 813.102193
#> iter 3 value 802.363339
#> iter 4 value 799.959552
#> iter 5 value 764.939601
#> iter 6 value 756.303575
#> iter 7 value 754.747740
#> iter 8 value 754.708418
#> iter 9 value 754.708319
#> iter 10 value 754.708306
#> iter 10 value 754.708306
#> iter 10 value 754.708301
#> final value 754.708301
#> converged
#> This is Run number 86
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.71164782 -0.0003000682 -1.2616478 -12.600300 1
#> 2 1 -0.95 -2.35 0.02092574 1.2677891730 -0.9290743 -1.082211 1
#> 3 1 -6.20 -2.30 0.07405645 -0.9306325511 -6.1259435 -3.230633 2
#> 4 1 -13.90 -2.55 -0.46904329 0.5459137931 -14.3690433 -2.004086 2
#> 5 1 -14.40 -5.80 0.26722338 -0.1514355147 -14.1327766 -5.951436 2
#> 6 1 -3.60 -1.70 -0.10558449 0.0898571504 -3.7055845 -1.610143 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5500 -37025 8075
#> initial value 998.131940
#> iter 2 value 831.429429
#> iter 3 value 817.182107
#> iter 4 value 815.542847
#> iter 5 value 774.386792
#> iter 6 value 766.259396
#> iter 7 value 765.033427
#> iter 8 value 765.014414
#> iter 8 value 765.014405
#> final value 765.014405
#> converged
#> This is Run number 87
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.7188451 0.2618778 -1.268845 -12.3381222 1
#> 2 1 -0.95 -2.35 2.2075609 1.6493675 1.257561 -0.7006325 1
#> 3 1 -6.20 -2.30 -0.8432090 2.0008099 -7.043209 -0.2991901 2
#> 4 1 -13.90 -2.55 -0.6457151 0.1147588 -14.545715 -2.4352412 2
#> 5 1 -14.40 -5.80 0.9222172 3.6196986 -13.477783 -2.1803014 2
#> 6 1 -3.60 -1.70 -1.2049979 -0.9766591 -4.804998 -2.6766591 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6140 -39850 7650
#> initial value 998.131940
#> iter 2 value 793.110813
#> iter 3 value 775.933356
#> iter 4 value 773.456835
#> iter 5 value 740.961570
#> iter 6 value 732.397012
#> iter 7 value 731.258090
#> iter 8 value 731.237662
#> iter 8 value 731.237660
#> final value 731.237660
#> converged
#> This is Run number 88
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.744638159 1.03020721 1.194638 -11.569793 1
#> 2 1 -0.95 -2.35 -0.793194933 -1.07851091 -1.743195 -3.428511 1
#> 3 1 -6.20 -2.30 -0.007010485 0.61980791 -6.207010 -1.680192 2
#> 4 1 -13.90 -2.55 1.177290376 0.86976812 -12.722710 -1.680232 2
#> 5 1 -14.40 -5.80 -1.132210133 0.72612006 -15.532210 -5.073880 2
#> 6 1 -3.60 -1.70 -0.072517801 -0.06271019 -3.672518 -1.762710 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6580 -38175 6300
#> initial value 998.131940
#> iter 2 value 825.198873
#> iter 3 value 816.019724
#> iter 4 value 814.950279
#> iter 5 value 776.785208
#> iter 6 value 768.364234
#> iter 7 value 766.812165
#> iter 8 value 766.776137
#> iter 9 value 766.776054
#> iter 9 value 766.776054
#> iter 9 value 766.776054
#> final value 766.776054
#> converged
#> This is Run number 89
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.4232817 2.07696403 0.8732817 -10.523036 1
#> 2 1 -0.95 -2.35 2.7080865 0.94286474 1.7580865 -1.407135 1
#> 3 1 -6.20 -2.30 3.0254708 0.89297547 -3.1745292 -1.407025 2
#> 4 1 -13.90 -2.55 -1.0799164 0.61342594 -14.9799164 -1.936574 2
#> 5 1 -14.40 -5.80 0.8685468 0.70204311 -13.5314532 -5.097957 2
#> 6 1 -3.60 -1.70 -0.2552806 -0.03218343 -3.8552806 -1.732183 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6500 -39800 6050
#> initial value 998.131940
#> iter 2 value 802.352330
#> iter 3 value 790.135954
#> iter 4 value 787.157110
#> iter 5 value 754.310293
#> iter 6 value 745.562416
#> iter 7 value 744.107272
#> iter 8 value 744.070061
#> iter 9 value 744.069972
#> iter 9 value 744.069962
#> iter 9 value 744.069955
#> final value 744.069955
#> converged
#> This is Run number 90
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.44094030 -0.32883801 -0.9909403 -12.928838 1
#> 2 1 -0.95 -2.35 0.87180930 0.39872858 -0.0781907 -1.951271 1
#> 3 1 -6.20 -2.30 0.53070026 -0.31913791 -5.6692997 -2.619138 2
#> 4 1 -13.90 -2.55 1.50135707 -0.31045543 -12.3986429 -2.860455 2
#> 5 1 -14.40 -5.80 -0.06862105 -0.07179713 -14.4686210 -5.871797 2
#> 6 1 -3.60 -1.70 0.23052304 5.12983842 -3.3694770 3.429838 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6140 -37325 7500
#> initial value 998.131940
#> iter 2 value 830.755377
#> iter 3 value 819.355764
#> iter 4 value 818.675097
#> iter 5 value 778.120094
#> iter 6 value 769.875666
#> iter 7 value 768.553430
#> iter 8 value 768.528831
#> iter 9 value 768.528793
#> iter 10 value 768.528780
#> iter 10 value 768.528771
#> iter 10 value 768.528764
#> final value 768.528764
#> converged
#> This is Run number 91
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.8172137 2.77756144 0.2672137 -9.8224386 1
#> 2 1 -0.95 -2.35 4.8469756 0.09810341 3.8969756 -2.2518966 1
#> 3 1 -6.20 -2.30 0.4007139 0.84027400 -5.7992861 -1.4597260 2
#> 4 1 -13.90 -2.55 -0.1725408 1.84094520 -14.0725408 -0.7090548 2
#> 5 1 -14.40 -5.80 0.8811397 2.08972692 -13.5188603 -3.7102731 2
#> 6 1 -3.60 -1.70 0.1976318 -1.13201925 -3.4023682 -2.8320192 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6400 -37850 6275
#> initial value 998.131940
#> iter 2 value 830.048550
#> iter 3 value 820.774742
#> iter 4 value 819.462971
#> iter 5 value 780.467786
#> iter 6 value 772.128770
#> iter 7 value 770.585173
#> iter 8 value 770.550348
#> iter 9 value 770.550270
#> iter 9 value 770.550270
#> iter 9 value 770.550270
#> final value 770.550270
#> converged
#> This is Run number 92
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.3782552 0.5277570 -0.9282552 -12.0722430 1
#> 2 1 -0.95 -2.35 0.3848940 1.7450431 -0.5651060 -0.6049569 1
#> 3 1 -6.20 -2.30 1.2760597 0.1427823 -4.9239403 -2.1572177 2
#> 4 1 -13.90 -2.55 0.2774260 -0.8705159 -13.6225740 -3.4205159 2
#> 5 1 -14.40 -5.80 -0.6837159 0.7658291 -15.0837159 -5.0341709 2
#> 6 1 -3.60 -1.70 -0.5557368 1.8227113 -4.1557368 0.1227113 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6760 -40900 8025
#> initial value 998.131940
#> iter 2 value 773.525140
#> iter 3 value 755.780727
#> iter 4 value 754.784495
#> iter 5 value 725.218662
#> iter 6 value 716.705448
#> iter 7 value 715.693984
#> iter 8 value 715.678378
#> iter 9 value 715.678363
#> iter 9 value 715.678358
#> iter 9 value 715.678358
#> final value 715.678358
#> converged
#> This is Run number 93
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.42406469 -0.45506422 -0.1259353 -13.0550642 1
#> 2 1 -0.95 -2.35 0.26999715 1.10979980 -0.6800028 -1.2402002 1
#> 3 1 -6.20 -2.30 -0.53698555 -1.93636105 -6.7369856 -4.2363611 2
#> 4 1 -13.90 -2.55 0.42871830 0.02752338 -13.4712817 -2.5224766 2
#> 5 1 -14.40 -5.80 0.02837421 0.17888129 -14.3716258 -5.6211187 2
#> 6 1 -3.60 -1.70 3.16162656 0.87174521 -0.4383734 -0.8282548 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7340 -40575 5175
#> initial value 998.131940
#> iter 2 value 793.018991
#> iter 3 value 784.664339
#> iter 4 value 782.695933
#> iter 5 value 751.848644
#> iter 6 value 743.072806
#> iter 7 value 741.320183
#> iter 8 value 741.265254
#> iter 9 value 741.265030
#> iter 10 value 741.265009
#> iter 10 value 741.265009
#> iter 11 value 741.264996
#> iter 11 value 741.264993
#> iter 11 value 741.264990
#> final value 741.264990
#> converged
#> This is Run number 94
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.7860526 0.2175871 0.2360526 -12.382413 1
#> 2 1 -0.95 -2.35 1.4269285 -0.3319648 0.4769285 -2.681965 1
#> 3 1 -6.20 -2.30 1.6028516 -0.7671012 -4.5971484 -3.067101 2
#> 4 1 -13.90 -2.55 -0.5500101 -0.6169612 -14.4500101 -3.166961 2
#> 5 1 -14.40 -5.80 0.6854648 -0.7490042 -13.7145352 -6.549004 2
#> 6 1 -3.60 -1.70 -1.0744341 0.6171008 -4.6744341 -1.082899 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7040 -37875 6500
#> initial value 998.131940
#> iter 2 value 827.873844
#> iter 3 value 819.910406
#> iter 4 value 819.823583
#> iter 5 value 780.536525
#> iter 6 value 772.212288
#> iter 7 value 770.626266
#> iter 8 value 770.589427
#> iter 9 value 770.589330
#> iter 10 value 770.589313
#> iter 10 value 770.589304
#> iter 10 value 770.589297
#> final value 770.589297
#> converged
#> This is Run number 95
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.52030281 -1.0448761 -1.0703028 -13.644876 1
#> 2 1 -0.95 -2.35 0.50106016 0.1937960 -0.4489398 -2.156204 1
#> 3 1 -6.20 -2.30 1.13885214 5.1724104 -5.0611479 2.872410 2
#> 4 1 -13.90 -2.55 0.07858258 0.4218970 -13.8214174 -2.128103 2
#> 5 1 -14.40 -5.80 2.27074668 -0.1716853 -12.1292533 -5.971685 2
#> 6 1 -3.60 -1.70 -1.19075772 -0.2243023 -4.7907577 -1.924302 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5840 -37925 6300
#> initial value 998.131940
#> iter 2 value 829.153988
#> iter 3 value 816.959339
#> iter 4 value 813.984339
#> iter 5 value 775.667894
#> iter 6 value 767.263657
#> iter 7 value 765.802217
#> iter 8 value 765.770403
#> iter 9 value 765.770341
#> iter 9 value 765.770331
#> iter 9 value 765.770326
#> final value 765.770326
#> converged
#> This is Run number 96
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.4619269 0.1830388 -0.08807309 -12.416961 1
#> 2 1 -0.95 -2.35 -1.1055677 1.2947104 -2.05556768 -1.055290 2
#> 3 1 -6.20 -2.30 -0.9920002 0.7381641 -7.19200015 -1.561836 2
#> 4 1 -13.90 -2.55 1.2400074 -1.8832944 -12.65999258 -4.433294 2
#> 5 1 -14.40 -5.80 -0.8096838 1.3550804 -15.20968378 -4.444920 2
#> 6 1 -3.60 -1.70 1.3494219 4.5936374 -2.25057807 2.893637 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5540 -36625 7350
#> initial value 998.131940
#> iter 2 value 841.160825
#> iter 3 value 829.191831
#> iter 4 value 827.394110
#> iter 5 value 785.186479
#> iter 6 value 777.164053
#> iter 7 value 775.854991
#> iter 8 value 775.831950
#> iter 9 value 775.831919
#> iter 9 value 775.831908
#> iter 9 value 775.831903
#> final value 775.831903
#> converged
#> This is Run number 97
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.001834528 0.1211372 -0.5481655 -12.47886279 1
#> 2 1 -0.95 -2.35 -0.364888939 1.0070213 -1.3148889 -1.34297872 1
#> 3 1 -6.20 -2.30 -1.023418534 2.2813831 -7.2234185 -0.01861692 2
#> 4 1 -13.90 -2.55 0.084338947 -0.5288091 -13.8156611 -3.07880910 2
#> 5 1 -14.40 -5.80 1.765133967 -1.6300936 -12.6348660 -7.43009358 2
#> 6 1 -3.60 -1.70 0.401290546 1.9348229 -3.1987095 0.23482287 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6160 -37975 6400
#> initial value 998.131940
#> iter 2 value 827.830640
#> iter 3 value 817.119439
#> iter 4 value 815.163047
#> iter 5 value 776.729990
#> iter 6 value 768.343618
#> iter 7 value 766.859410
#> iter 8 value 766.826619
#> iter 9 value 766.826554
#> iter 9 value 766.826543
#> iter 9 value 766.826537
#> final value 766.826537
#> converged
#> This is Run number 98
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.2214239 0.23385145 -0.7714239 -12.3661486 1
#> 2 1 -0.95 -2.35 0.1485121 2.05537818 -0.8014879 -0.2946218 2
#> 3 1 -6.20 -2.30 -0.5975881 -0.08669776 -6.7975881 -2.3866978 2
#> 4 1 -13.90 -2.55 -0.5028826 0.77572753 -14.4028826 -1.7742725 2
#> 5 1 -14.40 -5.80 -1.0752891 -0.56008177 -15.4752891 -6.3600818 2
#> 6 1 -3.60 -1.70 1.7581633 -0.53301247 -1.8418367 -2.2330125 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6760 -39125 7225
#> initial value 998.131940
#> iter 2 value 806.211272
#> iter 3 value 794.130963
#> iter 4 value 793.577324
#> iter 5 value 758.186887
#> iter 6 value 749.557951
#> iter 7 value 748.233117
#> iter 8 value 748.204899
#> iter 9 value 748.204853
#> iter 10 value 748.204839
#> iter 10 value 748.204830
#> iter 10 value 748.204822
#> final value 748.204822
#> converged
#> This is Run number 99
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.06519970 0.2946808 0.5151997 -12.3053192 1
#> 2 1 -0.95 -2.35 0.36221651 0.2169767 -0.5877835 -2.1330233 1
#> 3 1 -6.20 -2.30 -0.15168121 2.4710551 -6.3516812 0.1710551 2
#> 4 1 -13.90 -2.55 2.97693647 1.4339706 -10.9230635 -1.1160294 2
#> 5 1 -14.40 -5.80 0.00316157 0.9153798 -14.3968384 -4.8846202 2
#> 6 1 -3.60 -1.70 1.30588506 1.3028120 -2.2941149 -0.3971880 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5540 -37725 7425
#> initial value 998.131940
#> iter 2 value 825.897094
#> iter 3 value 811.151912
#> iter 4 value 808.437890
#> iter 5 value 769.592293
#> iter 6 value 761.286919
#> iter 7 value 760.005446
#> iter 8 value 759.982305
#> iter 9 value 759.982279
#> iter 9 value 759.982270
#> iter 9 value 759.982265
#> final value 759.982265
#> converged
#> This is Run number 100
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.5424929 0.8393994 -0.007507102 -11.760601 1
#> 2 1 -0.95 -2.35 1.3364321 -0.5358660 0.386432058 -2.885866 1
#> 3 1 -6.20 -2.30 3.2140910 -0.3558320 -2.985909045 -2.655832 2
#> 4 1 -13.90 -2.55 -1.1102428 1.6823350 -15.010242773 -0.867665 2
#> 5 1 -14.40 -5.80 -0.8430685 1.5801660 -15.243068486 -4.219834 2
#> 6 1 -3.60 -1.70 -0.3074278 0.3142555 -3.907427819 -1.385744 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5860 -37450 6825
#> initial value 998.131940
#> iter 2 value 833.021894
#> iter 3 value 821.415000
#> iter 4 value 819.414169
#> iter 5 value 779.545122
#> iter 6 value 771.290314
#> iter 7 value 769.895365
#> iter 8 value 769.867357
#> iter 9 value 769.867311
#> iter 9 value 769.867300
#> iter 9 value 769.867295
#> final value 769.867295
#> converged
#> This is Run number 101
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.4177567 1.1234849 -0.9677567 -11.476515 1
#> 2 1 -0.95 -2.35 -0.8108214 0.2932045 -1.7608214 -2.056796 1
#> 3 1 -6.20 -2.30 -0.7437990 1.1748935 -6.9437990 -1.125107 2
#> 4 1 -13.90 -2.55 -0.2841491 -0.5240037 -14.1841491 -3.074004 2
#> 5 1 -14.40 -5.80 2.0962448 1.6465735 -12.3037552 -4.153427 2
#> 6 1 -3.60 -1.70 0.5646285 0.9756100 -3.0353715 -0.724390 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6180 -40125 7000
#> initial value 998.131940
#> iter 2 value 792.574507
#> iter 3 value 776.314691
#> iter 4 value 772.897455
#> iter 5 value 741.332557
#> iter 6 value 732.660217
#> iter 7 value 731.467736
#> iter 8 value 731.442932
#> iter 9 value 731.442906
#> iter 9 value 731.442900
#> iter 9 value 731.442896
#> final value 731.442896
#> converged
#> This is Run number 102
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.1628389 -1.1173058 -0.3871611 -13.717306 1
#> 2 1 -0.95 -2.35 0.4535009 1.3115566 -0.4964991 -1.038443 1
#> 3 1 -6.20 -2.30 1.8628134 -0.1766261 -4.3371866 -2.476626 2
#> 4 1 -13.90 -2.55 -0.3649576 0.4817129 -14.2649576 -2.068287 2
#> 5 1 -14.40 -5.80 2.8226493 -0.7196365 -11.5773507 -6.519637 2
#> 6 1 -3.60 -1.70 0.9927357 0.1253296 -2.6072643 -1.574670 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5440 -37450 8125
#> initial value 998.131940
#> iter 2 value 825.356584
#> iter 3 value 809.639500
#> iter 4 value 807.503829
#> iter 5 value 767.735343
#> iter 6 value 759.529343
#> iter 7 value 758.317293
#> iter 8 value 758.298615
#> iter 9 value 758.298600
#> iter 9 value 758.298598
#> iter 10 value 758.298587
#> iter 10 value 758.298579
#> iter 10 value 758.298579
#> final value 758.298579
#> converged
#> This is Run number 103
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.07796849 1.3753498 -0.4720315 -11.224650 1
#> 2 1 -0.95 -2.35 -0.06360688 0.9425686 -1.0136069 -1.407431 1
#> 3 1 -6.20 -2.30 0.08685488 -0.6554985 -6.1131451 -2.955499 2
#> 4 1 -13.90 -2.55 -0.66296248 1.3728537 -14.5629625 -1.177146 2
#> 5 1 -14.40 -5.80 1.67964597 2.4150648 -12.7203540 -3.384935 2
#> 6 1 -3.60 -1.70 0.09866260 0.5150201 -3.5013374 -1.184980 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7180 -40400 6400
#> initial value 998.131940
#> iter 2 value 790.484082
#> iter 3 value 779.725808
#> iter 4 value 778.723689
#> iter 5 value 747.099805
#> iter 6 value 738.300139
#> iter 7 value 736.900041
#> iter 8 value 736.864265
#> iter 9 value 736.864191
#> iter 10 value 736.864179
#> iter 10 value 736.864173
#> iter 10 value 736.864166
#> final value 736.864166
#> converged
#> This is Run number 104
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.5828111 -0.53231778 1.032811 -13.132318 1
#> 2 1 -0.95 -2.35 -0.2370028 0.52920908 -1.187003 -1.820791 1
#> 3 1 -6.20 -2.30 0.5973776 3.61496297 -5.602622 1.314963 2
#> 4 1 -13.90 -2.55 -0.1884095 -0.31090653 -14.088409 -2.860907 2
#> 5 1 -14.40 -5.80 1.1612007 -0.06128768 -13.238799 -5.861288 2
#> 6 1 -3.60 -1.70 0.6454892 -0.80832087 -2.954511 -2.508321 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5620 -38275 7525
#> initial value 998.131940
#> iter 2 value 817.536131
#> iter 3 value 801.675184
#> iter 4 value 798.781680
#> iter 5 value 761.613672
#> iter 6 value 753.209023
#> iter 7 value 751.960521
#> iter 8 value 751.938043
#> iter 9 value 751.938021
#> iter 9 value 751.938013
#> iter 9 value 751.938008
#> final value 751.938008
#> converged
#> This is Run number 105
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.40524442 -0.5430965 0.8552444 -13.143097 1
#> 2 1 -0.95 -2.35 0.06301837 -0.4978175 -0.8869816 -2.847817 1
#> 3 1 -6.20 -2.30 -0.27339252 -0.8589458 -6.4733925 -3.158946 2
#> 4 1 -13.90 -2.55 0.40597044 -0.3665527 -13.4940296 -2.916553 2
#> 5 1 -14.40 -5.80 0.99030336 -1.0762871 -13.4096966 -6.876287 2
#> 6 1 -3.60 -1.70 0.14650550 -0.7617994 -3.4534945 -2.461799 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6960 -40425 5050
#> initial value 998.131940
#> iter 2 value 796.402308
#> iter 3 value 786.462839
#> iter 4 value 783.330902
#> iter 5 value 752.354794
#> iter 6 value 743.546725
#> iter 7 value 741.822076
#> iter 8 value 741.766938
#> iter 9 value 741.766669
#> iter 10 value 741.766643
#> iter 10 value 741.766642
#> iter 11 value 741.766625
#> iter 11 value 741.766619
#> iter 11 value 741.766616
#> final value 741.766616
#> converged
#> This is Run number 106
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.3706653 -0.6501890 -0.1793347 -13.25018899 1
#> 2 1 -0.95 -2.35 -0.1868625 2.7003048 -1.1368625 0.35030479 2
#> 3 1 -6.20 -2.30 2.2690864 4.4052166 -3.9309136 2.10521657 2
#> 4 1 -13.90 -2.55 4.6366917 2.5933194 -9.2633083 0.04331944 2
#> 5 1 -14.40 -5.80 -0.2063270 0.5632061 -14.6063270 -5.23679388 2
#> 6 1 -3.60 -1.70 0.1576100 -0.2597351 -3.4423900 -1.95973514 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5960 -38625 7950
#> initial value 998.131940
#> iter 2 value 809.775970
#> iter 3 value 793.933928
#> iter 4 value 792.285217
#> iter 5 value 755.875833
#> iter 6 value 747.431923
#> iter 7 value 746.237832
#> iter 8 value 746.217828
#> iter 9 value 746.217812
#> iter 9 value 746.217809
#> iter 10 value 746.217797
#> iter 10 value 746.217788
#> iter 10 value 746.217786
#> final value 746.217786
#> converged
#> This is Run number 107
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.4762951 -0.6836320 0.9262951 -13.2836320 1
#> 2 1 -0.95 -2.35 -0.4807399 1.0827014 -1.4307399 -1.2672986 2
#> 3 1 -6.20 -2.30 0.6813360 1.5812004 -5.5186640 -0.7187996 2
#> 4 1 -13.90 -2.55 1.7734735 2.1870237 -12.1265265 -0.3629763 2
#> 5 1 -14.40 -5.80 -0.9053541 0.3587707 -15.3053541 -5.4412293 2
#> 6 1 -3.60 -1.70 1.4485602 4.7696816 -2.1514398 3.0696816 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6580 -38575 7450
#> initial value 998.131940
#> iter 2 value 813.171740
#> iter 3 value 800.922688
#> iter 4 value 800.432948
#> iter 5 value 763.447755
#> iter 6 value 754.915769
#> iter 7 value 753.606315
#> iter 8 value 753.580189
#> iter 9 value 753.580148
#> iter 10 value 753.580135
#> iter 10 value 753.580126
#> iter 10 value 753.580118
#> final value 753.580118
#> converged
#> This is Run number 108
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.2464269 2.4212451 0.6964269 -10.178755 1
#> 2 1 -0.95 -2.35 4.4072346 -1.4690220 3.4572346 -3.819022 1
#> 3 1 -6.20 -2.30 1.2752983 0.6047428 -4.9247017 -1.695257 2
#> 4 1 -13.90 -2.55 1.0704427 -0.1757256 -12.8295573 -2.725726 2
#> 5 1 -14.40 -5.80 1.0463270 -0.1008591 -13.3536730 -5.900859 2
#> 6 1 -3.60 -1.70 0.2063991 7.3843605 -3.3936009 5.684360 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6380 -39800 6925
#> initial value 998.131940
#> iter 2 value 797.959726
#> iter 3 value 783.718605
#> iter 4 value 781.325700
#> iter 5 value 748.458307
#> iter 6 value 739.776260
#> iter 7 value 738.507520
#> iter 8 value 738.479953
#> iter 9 value 738.479915
#> iter 9 value 738.479907
#> iter 9 value 738.479901
#> final value 738.479901
#> converged
#> This is Run number 109
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.39172647 -0.05203641 -0.1582735 -12.6520364 1
#> 2 1 -0.95 -2.35 0.35006235 0.18508616 -0.5999376 -2.1649138 1
#> 3 1 -6.20 -2.30 -0.10029407 2.41787591 -6.3002941 0.1178759 2
#> 4 1 -13.90 -2.55 1.26744572 3.91574939 -12.6325543 1.3657494 2
#> 5 1 -14.40 -5.80 -1.26637011 -0.98797537 -15.6663701 -6.7879754 2
#> 6 1 -3.60 -1.70 0.03827256 1.82511702 -3.5617274 0.1251170 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6040 -39400 6775
#> initial value 998.131940
#> iter 2 value 805.087619
#> iter 3 value 790.091283
#> iter 4 value 786.704589
#> iter 5 value 752.878187
#> iter 6 value 744.227483
#> iter 7 value 742.932781
#> iter 8 value 742.904817
#> iter 9 value 742.904778
#> iter 9 value 742.904770
#> iter 9 value 742.904766
#> final value 742.904766
#> converged
#> This is Run number 110
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.0910901 0.90853720 -1.6410901 -11.6914628 1
#> 2 1 -0.95 -2.35 1.3017514 -1.00060731 0.3517514 -3.3506073 1
#> 3 1 -6.20 -2.30 1.2648228 -0.05677941 -4.9351772 -2.3567794 2
#> 4 1 -13.90 -2.55 0.3140348 1.90530349 -13.5859652 -0.6446965 2
#> 5 1 -14.40 -5.80 0.2810206 0.57483531 -14.1189794 -5.2251647 2
#> 6 1 -3.60 -1.70 0.7601856 0.34027990 -2.8398144 -1.3597201 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5940 -38125 6575
#> initial value 998.131940
#> iter 2 value 824.912812
#> iter 3 value 812.553499
#> iter 4 value 809.950878
#> iter 5 value 772.140296
#> iter 6 value 763.706414
#> iter 7 value 762.287589
#> iter 8 value 762.257174
#> iter 9 value 762.257121
#> iter 9 value 762.257111
#> iter 9 value 762.257106
#> final value 762.257106
#> converged
#> This is Run number 111
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.8058212 0.5478766 -2.35582117 -12.052123 1
#> 2 1 -0.95 -2.35 0.8956382 3.9970831 -0.05436175 1.647083 2
#> 3 1 -6.20 -2.30 -1.0416625 1.2273396 -7.24166246 -1.072660 2
#> 4 1 -13.90 -2.55 1.2373552 0.3883678 -12.66264480 -2.161632 2
#> 5 1 -14.40 -5.80 2.2001644 1.0020730 -12.19983560 -4.797927 2
#> 6 1 -3.60 -1.70 0.3534812 0.4687166 -3.24651883 -1.231283 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6680 -39400 6700
#> initial value 998.131940
#> iter 2 value 805.065551
#> iter 3 value 793.444220
#> iter 4 value 792.117019
#> iter 5 value 757.657785
#> iter 6 value 748.986708
#> iter 7 value 747.595235
#> iter 8 value 747.562878
#> iter 9 value 747.562819
#> iter 10 value 747.562807
#> iter 10 value 747.562799
#> iter 10 value 747.562793
#> final value 747.562793
#> converged
#> This is Run number 112
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.3826689 -1.24161744 0.8326689 -13.8416174 1
#> 2 1 -0.95 -2.35 0.3772576 3.33768768 -0.5727424 0.9876877 2
#> 3 1 -6.20 -2.30 0.2983948 -0.67344002 -5.9016052 -2.9734400 2
#> 4 1 -13.90 -2.55 -0.0890675 3.88421060 -13.9890675 1.3342106 2
#> 5 1 -14.40 -5.80 3.0158876 -0.62171061 -11.3841124 -6.4217106 2
#> 6 1 -3.60 -1.70 0.9935424 -0.08074774 -2.6064576 -1.7807477 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6260 -39875 7375
#> initial value 998.131940
#> iter 2 value 794.308919
#> iter 3 value 778.338280
#> iter 4 value 775.959628
#> iter 5 value 743.431949
#> iter 6 value 734.810346
#> iter 7 value 733.630021
#> iter 8 value 733.607087
#> iter 9 value 733.607066
#> iter 9 value 733.607059
#> iter 9 value 733.607058
#> final value 733.607058
#> converged
#> This is Run number 113
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.3519052 -0.22087558 -0.1980948 -12.8208756 1
#> 2 1 -0.95 -2.35 1.2378199 -0.07860796 0.2878199 -2.4286080 1
#> 3 1 -6.20 -2.30 0.4250086 2.64291920 -5.7749914 0.3429192 2
#> 4 1 -13.90 -2.55 0.6505979 -0.56735223 -13.2494021 -3.1173522 2
#> 5 1 -14.40 -5.80 0.8804580 -0.51777450 -13.5195420 -6.3177745 2
#> 6 1 -3.60 -1.70 0.2589436 -0.02692288 -3.3410564 -1.7269229 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6620 -39150 6775
#> initial value 998.131940
#> iter 2 value 808.487918
#> iter 3 value 796.925104
#> iter 4 value 795.689517
#> iter 5 value 760.472944
#> iter 6 value 751.841719
#> iter 7 value 750.448134
#> iter 8 value 750.416367
#> iter 9 value 750.416309
#> iter 10 value 750.416297
#> iter 10 value 750.416288
#> iter 10 value 750.416282
#> final value 750.416282
#> converged
#> This is Run number 114
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.603536490 4.4812340 -1.1535365 -8.11876598 1
#> 2 1 -0.95 -2.35 1.290789430 2.2773126 0.3407894 -0.07268735 1
#> 3 1 -6.20 -2.30 0.003402257 5.9140531 -6.1965977 3.61405310 2
#> 4 1 -13.90 -2.55 2.397009249 0.9084427 -11.5029908 -1.64155726 2
#> 5 1 -14.40 -5.80 0.742565603 -0.4794452 -13.6574344 -6.27944515 2
#> 6 1 -3.60 -1.70 1.486062314 -0.2661207 -2.1139377 -1.96612070 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6500 -37400 6925
#> initial value 998.131940
#> iter 2 value 832.765736
#> iter 3 value 823.424745
#> iter 4 value 823.020686
#> iter 5 value 782.559148
#> iter 6 value 774.309776
#> iter 7 value 772.861929
#> iter 8 value 772.831602
#> iter 9 value 772.831539
#> iter 10 value 772.831523
#> iter 10 value 772.831513
#> iter 10 value 772.831508
#> final value 772.831508
#> converged
#> This is Run number 115
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.5331682 1.3911256 -0.0168318 -11.208874 1
#> 2 1 -0.95 -2.35 -1.3483805 1.1460807 -2.2983805 -1.203919 2
#> 3 1 -6.20 -2.30 -0.6134916 0.0323085 -6.8134916 -2.267692 2
#> 4 1 -13.90 -2.55 1.9731837 1.1929599 -11.9268163 -1.357040 2
#> 5 1 -14.40 -5.80 -0.1644487 3.4581791 -14.5644487 -2.341821 2
#> 6 1 -3.60 -1.70 1.6290556 0.4892958 -1.9709444 -1.210704 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6320 -37250 6025
#> initial value 998.131940
#> iter 2 value 839.546954
#> iter 3 value 831.298995
#> iter 4 value 830.002911
#> iter 5 value 789.364037
#> iter 6 value 781.212880
#> iter 7 value 779.624756
#> iter 8 value 779.589912
#> iter 9 value 779.589831
#> iter 9 value 779.589820
#> iter 9 value 779.589816
#> final value 779.589816
#> converged
#> This is Run number 116
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.06747118 -1.0469348 -0.4825288 -13.646935 1
#> 2 1 -0.95 -2.35 2.01765020 0.5799595 1.0676502 -1.770041 1
#> 3 1 -6.20 -2.30 -0.75327868 1.0381586 -6.9532787 -1.261841 2
#> 4 1 -13.90 -2.55 0.66372100 1.4667980 -13.2362790 -1.083202 2
#> 5 1 -14.40 -5.80 1.91002904 3.0442269 -12.4899710 -2.755773 2
#> 6 1 -3.60 -1.70 1.64466850 -0.5971875 -1.9553315 -2.297188 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6680 -38775 6900
#> initial value 998.131940
#> iter 2 value 813.306633
#> iter 3 value 802.338936
#> iter 4 value 801.590755
#> iter 5 value 765.141387
#> iter 6 value 756.570232
#> iter 7 value 755.161933
#> iter 8 value 755.130457
#> iter 9 value 755.130397
#> iter 10 value 755.130382
#> iter 10 value 755.130372
#> iter 10 value 755.130365
#> final value 755.130365
#> converged
#> This is Run number 117
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.4045822 0.4387684 0.8545822 -12.161232 1
#> 2 1 -0.95 -2.35 1.3983074 3.4322257 0.4483074 1.082226 2
#> 3 1 -6.20 -2.30 -1.3395984 0.9512213 -7.5395984 -1.348779 2
#> 4 1 -13.90 -2.55 -0.4738667 -0.5406114 -14.3738667 -3.090611 2
#> 5 1 -14.40 -5.80 -0.6829639 2.0351891 -15.0829639 -3.764811 2
#> 6 1 -3.60 -1.70 1.6339875 3.2106441 -1.9660125 1.510644 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7100 -39175 6575
#> initial value 998.131940
#> iter 2 value 808.623354
#> iter 3 value 799.000421
#> iter 4 value 798.628478
#> iter 5 value 763.169641
#> iter 6 value 754.523404
#> iter 7 value 753.024454
#> iter 8 value 752.987845
#> iter 9 value 752.987760
#> iter 10 value 752.987743
#> iter 10 value 752.987734
#> iter 10 value 752.987727
#> final value 752.987727
#> converged
#> This is Run number 118
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.6235698 -0.1444569 -1.1735698 -12.744457 1
#> 2 1 -0.95 -2.35 0.5702282 -0.8272312 -0.3797718 -3.177231 1
#> 3 1 -6.20 -2.30 -0.7591878 4.6361855 -6.9591878 2.336186 2
#> 4 1 -13.90 -2.55 -0.1806253 0.7253241 -14.0806253 -1.824676 2
#> 5 1 -14.40 -5.80 -0.2472027 2.1010108 -14.6472027 -3.698989 2
#> 6 1 -3.60 -1.70 -0.7508465 -0.4454714 -4.3508465 -2.145471 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6000 -38475 7200
#> initial value 998.131940
#> iter 2 value 816.471785
#> iter 3 value 802.714777
#> iter 4 value 800.600099
#> iter 5 value 763.746666
#> iter 6 value 755.268351
#> iter 7 value 753.960391
#> iter 8 value 753.934366
#> iter 9 value 753.934331
#> iter 9 value 753.934320
#> iter 9 value 753.934315
#> final value 753.934315
#> converged
#> This is Run number 119
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.73532364 0.5536026 0.1853236 -12.0463974 1
#> 2 1 -0.95 -2.35 1.06250084 -0.8391651 0.1125008 -3.1891651 1
#> 3 1 -6.20 -2.30 0.13021923 -0.7465294 -6.0697808 -3.0465294 2
#> 4 1 -13.90 -2.55 1.61984241 0.1540740 -12.2801576 -2.3959260 2
#> 5 1 -14.40 -5.80 -0.01241165 4.5142412 -14.4124117 -1.2857588 2
#> 6 1 -3.60 -1.70 -0.76568476 0.9609069 -4.3656848 -0.7390931 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6900 -40675 6575
#> initial value 998.131940
#> iter 2 value 785.510710
#> iter 3 value 772.756777
#> iter 4 value 770.895300
#> iter 5 value 740.440300
#> iter 6 value 731.657421
#> iter 7 value 730.378372
#> iter 8 value 730.347558
#> iter 9 value 730.347508
#> iter 9 value 730.347507
#> iter 9 value 730.347507
#> final value 730.347507
#> converged
#> This is Run number 120
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.01594104 4.1415568 -0.5659410 -8.458443 1
#> 2 1 -0.95 -2.35 1.34969009 0.1006979 0.3996901 -2.249302 1
#> 3 1 -6.20 -2.30 -0.82920188 -1.0474885 -7.0292019 -3.347488 2
#> 4 1 -13.90 -2.55 -0.54090910 0.2416173 -14.4409091 -2.308383 2
#> 5 1 -14.40 -5.80 0.03498942 -0.2569341 -14.3650106 -6.056934 2
#> 6 1 -3.60 -1.70 1.45119880 1.4463160 -2.1488012 -0.253684 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5880 -37025 6550
#> initial value 998.131940
#> iter 2 value 840.204456
#> iter 3 value 829.913440
#> iter 4 value 828.081264
#> iter 5 value 786.992376
#> iter 6 value 778.866204
#> iter 7 value 777.423344
#> iter 8 value 777.394222
#> iter 9 value 777.394169
#> iter 9 value 777.394167
#> iter 9 value 777.394167
#> final value 777.394167
#> converged
#> This is Run number 121
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.007398645 -0.6456223 -0.5573986 -13.2456223 1
#> 2 1 -0.95 -2.35 2.755982139 -1.4123493 1.8059821 -3.7623493 1
#> 3 1 -6.20 -2.30 -0.962504418 1.8263480 -7.1625044 -0.4736520 2
#> 4 1 -13.90 -2.55 -0.738591477 -0.4129857 -14.6385915 -2.9629857 2
#> 5 1 -14.40 -5.80 0.921618417 3.8217972 -13.4783816 -1.9782028 2
#> 6 1 -3.60 -1.70 0.368379844 1.0427421 -3.2316202 -0.6572579 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6620 -39000 6425
#> initial value 998.131940
#> iter 2 value 812.553482
#> iter 3 value 801.917743
#> iter 4 value 800.469960
#> iter 5 value 764.820947
#> iter 6 value 756.213543
#> iter 7 value 754.735317
#> iter 8 value 754.700099
#> iter 9 value 754.700025
#> iter 10 value 754.700013
#> iter 10 value 754.700006
#> iter 10 value 754.700006
#> final value 754.700006
#> converged
#> This is Run number 122
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.1044082 -1.0239845 0.5544082 -13.6239845 1
#> 2 1 -0.95 -2.35 1.8460893 -0.3844123 0.8960893 -2.7344123 1
#> 3 1 -6.20 -2.30 4.6929555 0.2772338 -1.5070445 -2.0227662 1
#> 4 1 -13.90 -2.55 -0.6429437 1.7768983 -14.5429437 -0.7731017 2
#> 5 1 -14.40 -5.80 0.1151027 -1.2141846 -14.2848973 -7.0141846 2
#> 6 1 -3.60 -1.70 2.2423465 0.3866359 -1.3576535 -1.3133641 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6680 -39975 6725
#> initial value 998.131940
#> iter 2 value 796.078869
#> iter 3 value 783.337508
#> iter 4 value 781.563694
#> iter 5 value 748.983905
#> iter 6 value 740.254234
#> iter 7 value 738.934391
#> iter 8 value 738.903793
#> iter 9 value 738.903743
#> iter 9 value 738.903743
#> iter 9 value 738.903743
#> final value 738.903743
#> converged
#> This is Run number 123
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.4958699 0.4953689 -1.0458699 -12.1046311 1
#> 2 1 -0.95 -2.35 0.8843669 2.6466201 -0.0656331 0.2966201 2
#> 3 1 -6.20 -2.30 -0.7861591 0.7865901 -6.9861591 -1.5134099 2
#> 4 1 -13.90 -2.55 -0.8921643 1.7033495 -14.7921643 -0.8466505 2
#> 5 1 -14.40 -5.80 1.3302444 -1.3219559 -13.0697556 -7.1219559 2
#> 6 1 -3.60 -1.70 0.1916989 -0.4053545 -3.4083011 -2.1053545 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6260 -38575 5850
#> initial value 998.131940
#> iter 2 value 821.834037
#> iter 3 value 811.011828
#> iter 4 value 808.291189
#> iter 5 value 771.753259
#> iter 6 value 763.214772
#> iter 7 value 761.632365
#> iter 8 value 761.593493
#> iter 9 value 761.593391
#> iter 10 value 761.593378
#> iter 10 value 761.593377
#> iter 10 value 761.593372
#> final value 761.593372
#> converged
#> This is Run number 124
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.2104237 0.09877969 -0.7604237 -12.5012203 1
#> 2 1 -0.95 -2.35 2.0589260 1.08507825 1.1089260 -1.2649218 1
#> 3 1 -6.20 -2.30 3.1514716 -0.68329469 -3.0485284 -2.9832947 2
#> 4 1 -13.90 -2.55 1.1270583 -0.62843630 -12.7729417 -3.1784363 2
#> 5 1 -14.40 -5.80 1.4032159 -0.33711845 -12.9967841 -6.1371184 2
#> 6 1 -3.60 -1.70 -0.7215012 1.10637593 -4.3215012 -0.5936241 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5880 -39100 7250
#> initial value 998.131940
#> iter 2 value 807.024467
#> iter 3 value 791.045094
#> iter 4 value 787.929812
#> iter 5 value 753.234479
#> iter 6 value 744.677040
#> iter 7 value 743.436278
#> iter 8 value 743.412094
#> iter 9 value 743.412068
#> iter 9 value 743.412061
#> iter 9 value 743.412056
#> final value 743.412056
#> converged
#> This is Run number 125
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.28295939 1.4161426 -0.2670406 -11.1838574 1
#> 2 1 -0.95 -2.35 2.29162878 1.4828809 1.3416288 -0.8671191 1
#> 3 1 -6.20 -2.30 0.13773400 1.0801234 -6.0622660 -1.2198766 2
#> 4 1 -13.90 -2.55 -1.10820683 0.2308282 -15.0082068 -2.3191718 2
#> 5 1 -14.40 -5.80 -0.02794952 -0.2549103 -14.4279495 -6.0549103 2
#> 6 1 -3.60 -1.70 2.24755125 -1.0006981 -1.3524487 -2.7006981 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5960 -38700 6875
#> initial value 998.131940
#> iter 2 value 815.023033
#> iter 3 value 801.068300
#> iter 4 value 798.261613
#> iter 5 value 762.216639
#> iter 6 value 753.678486
#> iter 7 value 752.342646
#> iter 8 value 752.314655
#> iter 9 value 752.314615
#> iter 9 value 752.314606
#> iter 9 value 752.314601
#> final value 752.314601
#> converged
#> This is Run number 126
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 3.1859691 -0.8381323 2.6359691 -13.4381323 1
#> 2 1 -0.95 -2.35 1.1883152 -0.8078310 0.2383152 -3.1578310 1
#> 3 1 -6.20 -2.30 0.7620435 3.6183367 -5.4379565 1.3183367 2
#> 4 1 -13.90 -2.55 1.0069732 1.9725617 -12.8930268 -0.5774383 2
#> 5 1 -14.40 -5.80 -0.2800473 1.2369484 -14.6800473 -4.5630516 2
#> 6 1 -3.60 -1.70 4.4138473 3.1231985 0.8138473 1.4231985 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6100 -38775 6575
#> initial value 998.131940
#> iter 2 value 815.460942
#> iter 3 value 802.537169
#> iter 4 value 799.819079
#> iter 5 value 763.925311
#> iter 6 value 755.356496
#> iter 7 value 753.959953
#> iter 8 value 753.928901
#> iter 9 value 753.928847
#> iter 9 value 753.928837
#> iter 9 value 753.928832
#> final value 753.928832
#> converged
#> This is Run number 127
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.4704153 1.705396125 -0.07958474 -10.8946039 1
#> 2 1 -0.95 -2.35 0.2806316 0.007796026 -0.66936843 -2.3422040 1
#> 3 1 -6.20 -2.30 0.6016990 1.967345465 -5.59830097 -0.3326545 2
#> 4 1 -13.90 -2.55 0.6087371 0.352152908 -13.29126289 -2.1978471 2
#> 5 1 -14.40 -5.80 1.9502347 0.965958981 -12.44976534 -4.8340410 2
#> 6 1 -3.60 -1.70 -0.9923503 -0.619029628 -4.59235026 -2.3190296 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6360 -39575 7700
#> initial value 998.131940
#> iter 2 value 796.921234
#> iter 3 value 781.307460
#> iter 4 value 779.870670
#> iter 5 value 746.228503
#> iter 6 value 737.641984
#> iter 7 value 736.469027
#> iter 8 value 736.447753
#> iter 8 value 736.447749
#> final value 736.447749
#> converged
#> This is Run number 128
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.6155602 0.30384009 1.0655602 -12.2961599 1
#> 2 1 -0.95 -2.35 0.7574315 -0.61876202 -0.1925685 -2.9687620 1
#> 3 1 -6.20 -2.30 1.9302551 2.70334303 -4.2697449 0.4033430 2
#> 4 1 -13.90 -2.55 0.5040528 0.10378346 -13.3959472 -2.4462165 2
#> 5 1 -14.40 -5.80 0.6823083 0.04999199 -13.7176917 -5.7500080 2
#> 6 1 -3.60 -1.70 0.2407718 1.10703430 -3.3592282 -0.5929657 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6580 -37950 5925
#> initial value 998.131940
#> iter 2 value 830.175463
#> iter 3 value 821.900026
#> iter 4 value 820.671042
#> iter 5 value 781.912269
#> iter 6 value 773.571604
#> iter 7 value 771.931159
#> iter 8 value 771.892446
#> iter 9 value 771.892347
#> iter 10 value 771.892335
#> iter 10 value 771.892331
#> iter 10 value 771.892327
#> final value 771.892327
#> converged
#> This is Run number 129
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.013257058 0.6146410 -0.5367429 -11.9853590 1
#> 2 1 -0.95 -2.35 -0.007590402 -0.2269947 -0.9575904 -2.5769947 1
#> 3 1 -6.20 -2.30 -0.129764150 -0.4604442 -6.3297641 -2.7604442 2
#> 4 1 -13.90 -2.55 -0.826629694 0.6566235 -14.7266297 -1.8933765 2
#> 5 1 -14.40 -5.80 0.925438344 -0.3550511 -13.4745617 -6.1550511 2
#> 6 1 -3.60 -1.70 0.523862051 1.2371312 -3.0761379 -0.4628688 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6600 -38925 6375
#> initial value 998.131940
#> iter 2 value 813.935764
#> iter 3 value 803.434884
#> iter 4 value 801.941989
#> iter 5 value 766.082142
#> iter 6 value 757.489358
#> iter 7 value 755.997046
#> iter 8 value 755.961420
#> iter 9 value 755.961344
#> iter 10 value 755.961332
#> iter 10 value 755.961325
#> iter 10 value 755.961325
#> final value 755.961325
#> converged
#> This is Run number 130
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.28706691 0.08503725 -0.8370669 -12.5149627 1
#> 2 1 -0.95 -2.35 0.72972559 1.68337268 -0.2202744 -0.6666273 1
#> 3 1 -6.20 -2.30 1.29963033 -0.42474723 -4.9003697 -2.7247472 2
#> 4 1 -13.90 -2.55 1.16782494 4.82519673 -12.7321751 2.2751967 2
#> 5 1 -14.40 -5.80 -0.03524421 -0.37960836 -14.4352442 -6.1796084 2
#> 6 1 -3.60 -1.70 -0.63969585 -0.34121831 -4.2396959 -2.0412183 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6280 -38225 6475
#> initial value 998.131940
#> iter 2 value 823.840237
#> iter 3 value 813.092715
#> iter 4 value 811.346496
#> iter 5 value 773.561946
#> iter 6 value 765.116619
#> iter 7 value 763.642130
#> iter 8 value 763.609118
#> iter 9 value 763.609052
#> iter 9 value 763.609052
#> iter 9 value 763.609052
#> final value 763.609052
#> converged
#> This is Run number 131
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.3165315 1.524189532 -0.8665315 -11.075810 1
#> 2 1 -0.95 -2.35 1.3164826 0.652308434 0.3664826 -1.697692 1
#> 3 1 -6.20 -2.30 -1.4117486 -0.016456106 -7.6117486 -2.316456 2
#> 4 1 -13.90 -2.55 -0.2352694 -0.080260767 -14.1352694 -2.630261 2
#> 5 1 -14.40 -5.80 0.6037892 0.500541109 -13.7962108 -5.299459 2
#> 6 1 -3.60 -1.70 0.4378517 -0.009254014 -3.1621483 -1.709254 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5580 -39075 8575
#> initial value 998.131940
#> iter 2 value 799.060048
#> iter 3 value 778.598971
#> iter 4 value 775.824969
#> iter 5 value 741.258481
#> iter 6 value 732.942168
#> iter 7 value 731.848667
#> iter 8 value 731.833511
#> iter 9 value 731.833497
#> iter 9 value 731.833494
#> iter 9 value 731.833494
#> final value 731.833494
#> converged
#> This is Run number 132
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.5196768 0.5890659 -1.0696768 -12.01093412 1
#> 2 1 -0.95 -2.35 0.8236607 -0.2641049 -0.1263393 -2.61410492 1
#> 3 1 -6.20 -2.30 4.4109768 -0.1255354 -1.7890232 -2.42553541 1
#> 4 1 -13.90 -2.55 -0.7794212 0.3924532 -14.6794212 -2.15754678 2
#> 5 1 -14.40 -5.80 1.3540949 0.4193582 -13.0459051 -5.38064184 2
#> 6 1 -3.60 -1.70 1.4265360 1.6007162 -2.1734640 -0.09928384 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5720 -36525 7175
#> initial value 998.131940
#> iter 2 value 843.439420
#> iter 3 value 832.706472
#> iter 4 value 831.328997
#> iter 5 value 788.744654
#> iter 6 value 780.755104
#> iter 7 value 779.414690
#> iter 8 value 779.390285
#> iter 9 value 779.390248
#> iter 10 value 779.390236
#> iter 10 value 779.390225
#> iter 10 value 779.390220
#> final value 779.390220
#> converged
#> This is Run number 133
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.6985852 -0.3486969 -1.2485852 -12.9486969 1
#> 2 1 -0.95 -2.35 0.3226493 -0.5028395 -0.6273507 -2.8528395 1
#> 3 1 -6.20 -2.30 3.4734443 0.4955129 -2.7265557 -1.8044871 2
#> 4 1 -13.90 -2.55 0.2666107 0.7923951 -13.6333893 -1.7576049 2
#> 5 1 -14.40 -5.80 1.4734701 4.4063127 -12.9265299 -1.3936873 2
#> 6 1 -3.60 -1.70 -0.1324955 1.1545845 -3.7324955 -0.5454155 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5340 -36175 7200
#> initial value 998.131940
#> iter 2 value 847.822259
#> iter 3 value 836.129674
#> iter 4 value 834.008898
#> iter 5 value 790.676626
#> iter 6 value 782.794608
#> iter 7 value 781.486977
#> iter 8 value 781.464486
#> iter 9 value 781.464457
#> iter 9 value 781.464447
#> iter 9 value 781.464442
#> final value 781.464442
#> converged
#> This is Run number 134
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.87286352 -0.6392067 0.3228635 -13.239207 1
#> 2 1 -0.95 -2.35 1.75347823 -0.2807660 0.8034782 -2.630766 1
#> 3 1 -6.20 -2.30 0.52224873 1.0334426 -5.6777513 -1.266557 2
#> 4 1 -13.90 -2.55 -0.78541897 -1.0078416 -14.6854190 -3.557842 2
#> 5 1 -14.40 -5.80 -0.54515703 1.2838356 -14.9451570 -4.516164 2
#> 6 1 -3.60 -1.70 0.02167894 -1.7751504 -3.5783211 -3.475150 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5840 -36525 7650
#> initial value 998.131940
#> iter 2 value 840.601584
#> iter 3 value 829.543291
#> iter 4 value 828.768332
#> iter 5 value 785.997373
#> iter 6 value 777.977331
#> iter 7 value 776.688733
#> iter 8 value 776.666672
#> iter 9 value 776.666641
#> iter 9 value 776.666629
#> iter 9 value 776.666624
#> final value 776.666624
#> converged
#> This is Run number 135
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.8856850 -0.41886283 0.335685 -13.0188628 1
#> 2 1 -0.95 -2.35 -0.7252232 0.51405599 -1.675223 -1.8359440 1
#> 3 1 -6.20 -2.30 0.3163594 0.41299380 -5.883641 -1.8870062 2
#> 4 1 -13.90 -2.55 1.9515774 -0.08487522 -11.948423 -2.6348752 2
#> 5 1 -14.40 -5.80 1.2379621 -0.57006197 -13.162038 -6.3700620 2
#> 6 1 -3.60 -1.70 0.3179838 2.16273940 -3.282016 0.4627394 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5980 -37075 6825
#> initial value 998.131940
#> iter 2 value 838.047265
#> iter 3 value 827.742923
#> iter 4 value 826.366996
#> iter 5 value 785.280305
#> iter 6 value 777.135385
#> iter 7 value 775.723808
#> iter 8 value 775.695699
#> iter 9 value 775.695649
#> iter 9 value 775.695649
#> iter 9 value 775.695649
#> final value 775.695649
#> converged
#> This is Run number 136
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.23167818 2.42646006 1.681678 -10.1735399 1
#> 2 1 -0.95 -2.35 2.01476686 0.47271232 1.064767 -1.8772877 1
#> 3 1 -6.20 -2.30 -0.20470875 0.05081534 -6.404709 -2.2491847 2
#> 4 1 -13.90 -2.55 2.29210249 -0.08752552 -11.607898 -2.6375255 2
#> 5 1 -14.40 -5.80 0.64678624 -0.08449036 -13.753214 -5.8844904 2
#> 6 1 -3.60 -1.70 -0.09931459 1.05061407 -3.699315 -0.6493859 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5900 -38825 8150
#> initial value 998.131940
#> iter 2 value 805.572942
#> iter 3 value 788.489731
#> iter 4 value 786.670826
#> iter 5 value 750.959618
#> iter 6 value 742.528961
#> iter 7 value 741.373855
#> iter 8 value 741.355702
#> iter 9 value 741.355687
#> iter 9 value 741.355684
#> iter 9 value 741.355675
#> final value 741.355675
#> converged
#> This is Run number 137
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.8511228 -0.02889434 0.30112281 -12.628894 1
#> 2 1 -0.95 -2.35 0.9178843 -0.43448110 -0.03211565 -2.784481 1
#> 3 1 -6.20 -2.30 -0.7812737 0.33578475 -6.98127367 -1.964215 2
#> 4 1 -13.90 -2.55 1.1838083 0.12798655 -12.71619170 -2.422013 2
#> 5 1 -14.40 -5.80 1.4619885 1.73312689 -12.93801148 -4.066873 2
#> 6 1 -3.60 -1.70 -0.5712750 2.11494896 -4.17127502 0.414949 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6460 -38925 7200
#> initial value 998.131940
#> iter 2 value 809.612017
#> iter 3 value 796.934252
#> iter 4 value 795.808298
#> iter 5 value 759.981885
#> iter 6 value 751.403569
#> iter 7 value 750.085991
#> iter 8 value 750.058522
#> iter 9 value 750.058480
#> iter 10 value 750.058468
#> iter 10 value 750.058458
#> iter 10 value 750.058452
#> final value 750.058452
#> converged
#> This is Run number 138
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.8205621 0.3040667 0.2705621 -12.2959333 1
#> 2 1 -0.95 -2.35 0.6763085 2.0613613 -0.2736915 -0.2886387 1
#> 3 1 -6.20 -2.30 1.1298120 -0.1978730 -5.0701880 -2.4978730 2
#> 4 1 -13.90 -2.55 -0.9525673 0.1635724 -14.8525673 -2.3864276 2
#> 5 1 -14.40 -5.80 -0.1402400 0.8233854 -14.5402400 -4.9766146 2
#> 6 1 -3.60 -1.70 -0.6453974 0.0574075 -4.2453974 -1.6425925 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7020 -39900 7525
#> initial value 998.131940
#> iter 2 value 792.314353
#> iter 3 value 778.832828
#> iter 4 value 778.545369
#> iter 5 value 745.526780
#> iter 6 value 736.825756
#> iter 7 value 735.615245
#> iter 8 value 735.591317
#> iter 9 value 735.591286
#> iter 9 value 735.591278
#> iter 9 value 735.591276
#> final value 735.591276
#> converged
#> This is Run number 139
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.58365874 -0.09696646 0.03365874 -12.6969665 1
#> 2 1 -0.95 -2.35 -0.97517770 0.86955234 -1.92517770 -1.4804477 2
#> 3 1 -6.20 -2.30 -1.63648937 1.65310178 -7.83648937 -0.6468982 2
#> 4 1 -13.90 -2.55 -0.02224711 -0.20563262 -13.92224711 -2.7556326 2
#> 5 1 -14.40 -5.80 4.36404999 1.41800687 -10.03595001 -4.3819931 2
#> 6 1 -3.60 -1.70 2.28158734 -1.17624436 -1.31841266 -2.8762444 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5880 -38400 8225
#> initial value 998.131940
#> iter 2 value 811.283694
#> iter 3 value 794.969622
#> iter 4 value 793.501579
#> iter 5 value 756.400747
#> iter 6 value 748.013795
#> iter 7 value 746.843840
#> iter 8 value 746.825819
#> iter 9 value 746.825806
#> iter 9 value 746.825803
#> iter 9 value 746.825792
#> final value 746.825792
#> converged
#> This is Run number 140
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.1195485 -0.99575207 -0.4304515 -13.595752 1
#> 2 1 -0.95 -2.35 -1.0843589 -0.52583176 -2.0343589 -2.875832 1
#> 3 1 -6.20 -2.30 1.9381947 -0.71982923 -4.2618053 -3.019829 2
#> 4 1 -13.90 -2.55 0.1439180 0.52312576 -13.7560820 -2.026874 2
#> 5 1 -14.40 -5.80 -0.2379121 -0.05483515 -14.6379121 -5.854835 2
#> 6 1 -3.60 -1.70 -0.5339392 -0.27023570 -4.1339392 -1.970236 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6360 -35975 6100
#> initial value 998.131940
#> iter 2 value 855.726129
#> iter 3 value 849.449133
#> iter 4 value 848.985625
#> iter 5 value 804.812668
#> iter 6 value 797.105243
#> iter 7 value 795.568336
#> iter 8 value 795.538065
#> iter 9 value 795.537995
#> iter 9 value 795.537989
#> iter 9 value 795.537989
#> final value 795.537989
#> converged
#> This is Run number 141
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.5204681 -0.8373088 -0.02953187 -13.437309 1
#> 2 1 -0.95 -2.35 0.8694662 0.3745249 -0.08053376 -1.975475 1
#> 3 1 -6.20 -2.30 2.4218607 -0.4524521 -3.77813930 -2.752452 2
#> 4 1 -13.90 -2.55 0.1557874 1.0736752 -13.74421264 -1.476325 2
#> 5 1 -14.40 -5.80 -1.2387726 0.7329548 -15.63877263 -5.067045 2
#> 6 1 -3.60 -1.70 2.2043552 -0.4960609 -1.39564481 -2.196061 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6360 -38050 6325
#> initial value 998.131940
#> iter 2 value 827.024049
#> iter 3 value 817.163741
#> iter 4 value 815.642434
#> iter 5 value 777.278519
#> iter 6 value 768.882294
#> iter 7 value 767.360503
#> iter 8 value 767.326015
#> iter 9 value 767.325941
#> iter 10 value 767.325929
#> iter 10 value 767.325922
#> iter 10 value 767.325917
#> final value 767.325917
#> converged
#> This is Run number 142
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.9356484 1.3688998 0.3856484 -11.2311002 1
#> 2 1 -0.95 -2.35 2.0059175 2.6400638 1.0559175 0.2900638 1
#> 3 1 -6.20 -2.30 0.2949954 -0.4800333 -5.9050046 -2.7800333 2
#> 4 1 -13.90 -2.55 -1.2173447 2.3460072 -15.1173447 -0.2039928 2
#> 5 1 -14.40 -5.80 -0.4629034 1.3966766 -14.8629034 -4.4033234 2
#> 6 1 -3.60 -1.70 0.1672113 0.6482633 -3.4327887 -1.0517367 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6340 -38125 6775
#> initial value 998.131940
#> iter 2 value 823.649927
#> iter 3 value 812.860074
#> iter 4 value 811.623783
#> iter 5 value 773.423588
#> iter 6 value 764.999157
#> iter 7 value 763.567407
#> iter 8 value 763.536394
#> iter 9 value 763.536335
#> iter 10 value 763.536322
#> iter 10 value 763.536312
#> iter 10 value 763.536308
#> final value 763.536308
#> converged
#> This is Run number 143
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.01623733 4.4900386 -0.5662373 -8.1099614 1
#> 2 1 -0.95 -2.35 0.14646683 -0.1479136 -0.8035332 -2.4979136 1
#> 3 1 -6.20 -2.30 0.55993888 0.2951670 -5.6400611 -2.0048330 2
#> 4 1 -13.90 -2.55 1.57540644 1.7172438 -12.3245936 -0.8327562 2
#> 5 1 -14.40 -5.80 0.61582758 4.2606734 -13.7841724 -1.5393266 2
#> 6 1 -3.60 -1.70 0.06077692 2.0014828 -3.5392231 0.3014828 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6080 -38850 8000
#> initial value 998.131940
#> iter 2 value 806.102722
#> iter 3 value 790.137963
#> iter 4 value 788.714221
#> iter 5 value 752.930872
#> iter 6 value 744.455297
#> iter 7 value 743.278152
#> iter 8 value 743.258637
#> iter 9 value 743.258617
#> iter 9 value 743.258613
#> iter 9 value 743.258606
#> final value 743.258606
#> converged
#> This is Run number 144
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.02540204 0.08516046 -0.5754020 -12.5148395 1
#> 2 1 -0.95 -2.35 0.12932325 -0.08493782 -0.8206767 -2.4349378 1
#> 3 1 -6.20 -2.30 0.94974298 -0.92341321 -5.2502570 -3.2234132 2
#> 4 1 -13.90 -2.55 5.45093184 0.97000046 -8.4490682 -1.5799995 2
#> 5 1 -14.40 -5.80 0.68751333 -0.09983055 -13.7124867 -5.8998306 2
#> 6 1 -3.60 -1.70 1.06535369 0.74274411 -2.5346463 -0.9572559 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6480 -39550 7625
#> initial value 998.131940
#> iter 2 value 797.674010
#> iter 3 value 782.801550
#> iter 4 value 781.654072
#> iter 5 value 747.826941
#> iter 6 value 739.216033
#> iter 7 value 738.022354
#> iter 8 value 738.000025
#> iter 9 value 738.000002
#> iter 9 value 737.999994
#> iter 9 value 737.999991
#> final value 737.999991
#> converged
#> This is Run number 145
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.1425866 1.0008970 -0.4074134 -11.5991030 1
#> 2 1 -0.95 -2.35 -1.1802779 1.6102184 -2.1302779 -0.7397816 2
#> 3 1 -6.20 -2.30 0.7753154 -0.2292162 -5.4246846 -2.5292162 2
#> 4 1 -13.90 -2.55 -1.2358724 0.9545549 -15.1358724 -1.5954451 2
#> 5 1 -14.40 -5.80 -0.9534038 2.0717363 -15.3534038 -3.7282637 2
#> 6 1 -3.60 -1.70 1.8562992 -0.3633814 -1.7437008 -2.0633814 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5900 -39275 6850
#> initial value 998.131940
#> iter 2 value 806.619959
#> iter 3 value 790.947770
#> iter 4 value 787.259675
#> iter 5 value 753.144637
#> iter 6 value 744.515946
#> iter 7 value 743.238137
#> iter 8 value 743.211328
#> iter 9 value 743.211293
#> iter 9 value 743.211286
#> iter 9 value 743.211281
#> final value 743.211281
#> converged
#> This is Run number 146
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.2867370 -0.9313730 -0.83673697 -13.531373 1
#> 2 1 -0.95 -2.35 0.8640782 0.5480416 -0.08592184 -1.801958 1
#> 3 1 -6.20 -2.30 -1.4136972 0.6295673 -7.61369720 -1.670433 2
#> 4 1 -13.90 -2.55 1.1147061 0.4361971 -12.78529389 -2.113803 2
#> 5 1 -14.40 -5.80 2.4387189 0.3467111 -11.96128112 -5.453289 2
#> 6 1 -3.60 -1.70 0.6153004 -0.8356694 -2.98469961 -2.535669 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6380 -38000 6950
#> initial value 998.131940
#> iter 2 value 824.432157
#> iter 3 value 813.690608
#> iter 4 value 812.771878
#> iter 5 value 774.140127
#> iter 6 value 765.740075
#> iter 7 value 764.328791
#> iter 8 value 764.298907
#> iter 9 value 764.298852
#> iter 10 value 764.298837
#> iter 10 value 764.298827
#> iter 10 value 764.298824
#> final value 764.298824
#> converged
#> This is Run number 147
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.24351930 2.14403611 -1.793519 -10.4559639 1
#> 2 1 -0.95 -2.35 2.90579605 -0.09093662 1.955796 -2.4409366 1
#> 3 1 -6.20 -2.30 0.69668368 0.41219840 -5.503316 -1.8878016 2
#> 4 1 -13.90 -2.55 0.05818041 0.10300689 -13.841820 -2.4469931 2
#> 5 1 -14.40 -5.80 -1.29087069 -0.81303065 -15.690871 -6.6130307 2
#> 6 1 -3.60 -1.70 1.35727580 1.41340633 -2.242724 -0.2865937 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6320 -39350 7225
#> initial value 998.131940
#> iter 2 value 803.207714
#> iter 3 value 789.025029
#> iter 4 value 787.183568
#> iter 5 value 752.857580
#> iter 6 value 744.242693
#> iter 7 value 742.980120
#> iter 8 value 742.954307
#> iter 9 value 742.954274
#> iter 9 value 742.954264
#> iter 9 value 742.954258
#> final value 742.954258
#> converged
#> This is Run number 148
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.19733318 0.51077804 0.6473332 -12.0892220 1
#> 2 1 -0.95 -2.35 -0.52125916 2.13107625 -1.4712592 -0.2189238 2
#> 3 1 -6.20 -2.30 -0.18981702 -0.03074734 -6.3898170 -2.3307473 2
#> 4 1 -13.90 -2.55 1.64015825 3.01803842 -12.2598417 0.4680384 2
#> 5 1 -14.40 -5.80 0.03052362 -0.57099509 -14.3694764 -6.3709951 2
#> 6 1 -3.60 -1.70 1.33886210 -0.39531734 -2.2611379 -2.0953173 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5620 -37600 8125
#> initial value 998.131940
#> iter 2 value 823.285079
#> iter 3 value 808.031135
#> iter 4 value 806.333951
#> iter 5 value 766.884280
#> iter 6 value 758.633079
#> iter 7 value 757.422678
#> iter 8 value 757.403788
#> iter 9 value 757.403772
#> iter 9 value 757.403772
#> iter 9 value 757.403766
#> final value 757.403766
#> converged
#> This is Run number 149
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.43609393 0.7013268 -0.1139061 -11.8986732 1
#> 2 1 -0.95 -2.35 -1.11922853 3.1194979 -2.0692285 0.7694979 2
#> 3 1 -6.20 -2.30 0.06393889 1.0611855 -6.1360611 -1.2388145 2
#> 4 1 -13.90 -2.55 0.79532654 3.7323890 -13.1046735 1.1823890 2
#> 5 1 -14.40 -5.80 -1.15528773 0.2589116 -15.5552877 -5.5410884 2
#> 6 1 -3.60 -1.70 2.16473543 1.4874184 -1.4352646 -0.2125816 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5320 -35950 6950
#> initial value 998.131940
#> iter 2 value 852.058458
#> iter 3 value 841.022494
#> iter 4 value 838.842118
#> iter 5 value 794.959638
#> iter 6 value 787.156416
#> iter 7 value 785.830916
#> iter 8 value 785.807907
#> iter 9 value 785.807875
#> iter 9 value 785.807866
#> iter 9 value 785.807862
#> final value 785.807862
#> converged
#> This is Run number 150
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.1925067 2.04015897 -0.7425067 -10.5598410 1
#> 2 1 -0.95 -2.35 0.1776420 0.05961709 -0.7723580 -2.2903829 1
#> 3 1 -6.20 -2.30 1.7347755 -0.47444233 -4.4652245 -2.7744423 2
#> 4 1 -13.90 -2.55 -0.3297786 1.79303070 -14.2297786 -0.7569693 2
#> 5 1 -14.40 -5.80 0.7295488 0.46424627 -13.6704512 -5.3357537 2
#> 6 1 -3.60 -1.70 -0.3886173 0.29899326 -3.9886173 -1.4010067 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6440 -38450 6275
#> initial value 998.131940
#> iter 2 value 821.505696
#> iter 3 value 811.331868
#> iter 4 value 809.670627
#> iter 5 value 772.483885
#> iter 6 value 763.991729
#> iter 7 value 762.467864
#> iter 8 value 762.432221
#> iter 9 value 762.432143
#> iter 10 value 762.432131
#> iter 10 value 762.432125
#> iter 10 value 762.432123
#> final value 762.432123
#> converged
#> This is Run number 151
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.5600606 1.33529786 -1.1100606 -11.264702 1
#> 2 1 -0.95 -2.35 2.4614802 0.16456444 1.5114802 -2.185436 1
#> 3 1 -6.20 -2.30 -0.6452466 -1.11798262 -6.8452466 -3.417983 2
#> 4 1 -13.90 -2.55 -0.2636248 -0.79869186 -14.1636248 -3.348692 2
#> 5 1 -14.40 -5.80 -0.2024300 2.80931145 -14.6024300 -2.990689 2
#> 6 1 -3.60 -1.70 2.7816691 -0.07894998 -0.8183309 -1.778950 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6260 -38025 6725
#> initial value 998.131940
#> iter 2 value 825.384958
#> iter 3 value 814.547207
#> iter 4 value 813.129980
#> iter 5 value 774.696324
#> iter 6 value 766.297102
#> iter 7 value 764.861318
#> iter 8 value 764.830368
#> iter 9 value 764.830311
#> iter 9 value 764.830311
#> iter 9 value 764.830311
#> final value 764.830311
#> converged
#> This is Run number 152
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.6250066 0.2262293 -1.175007 -12.3737707 1
#> 2 1 -0.95 -2.35 3.3231726 -0.6459198 2.373173 -2.9959198 1
#> 3 1 -6.20 -2.30 -0.5017023 1.5260813 -6.701702 -0.7739187 2
#> 4 1 -13.90 -2.55 0.5679645 0.1826057 -13.332035 -2.3673943 2
#> 5 1 -14.40 -5.80 0.9951574 -0.4104710 -13.404843 -6.2104710 2
#> 6 1 -3.60 -1.70 1.8083609 -1.3865536 -1.791639 -3.0865536 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4860 -35025 6700
#> initial value 998.131940
#> iter 2 value 864.561788
#> iter 3 value 853.366007
#> iter 4 value 850.618570
#> iter 5 value 804.486120
#> iter 6 value 796.982491
#> iter 7 value 795.705861
#> iter 8 value 795.685667
#> iter 9 value 795.685642
#> iter 9 value 795.685636
#> iter 9 value 795.685633
#> final value 795.685633
#> converged
#> This is Run number 153
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.2870767 -0.02050144 -0.8370767 -12.620501 1
#> 2 1 -0.95 -2.35 0.1221351 1.23251082 -0.8278649 -1.117489 1
#> 3 1 -6.20 -2.30 1.0288343 0.70349491 -5.1711657 -1.596505 2
#> 4 1 -13.90 -2.55 -0.7415543 0.29205276 -14.6415543 -2.257947 2
#> 5 1 -14.40 -5.80 -0.5924580 -0.16841918 -14.9924580 -5.968419 2
#> 6 1 -3.60 -1.70 -1.3418374 -0.60850812 -4.9418374 -2.308508 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5380 -36925 7325
#> initial value 998.131940
#> iter 2 value 837.353294
#> iter 3 value 823.886922
#> iter 4 value 821.325484
#> iter 5 value 780.150321
#> iter 6 value 772.039706
#> iter 7 value 770.738327
#> iter 8 value 770.715401
#> iter 9 value 770.715374
#> iter 9 value 770.715364
#> iter 9 value 770.715359
#> final value 770.715359
#> converged
#> This is Run number 154
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.53920613 0.4633758 0.9892061 -12.1366242 1
#> 2 1 -0.95 -2.35 1.71380230 -0.4433767 0.7638023 -2.7933767 1
#> 3 1 -6.20 -2.30 0.03696869 1.8820436 -6.1630313 -0.4179564 2
#> 4 1 -13.90 -2.55 0.19547196 6.2942176 -13.7045280 3.7442176 2
#> 5 1 -14.40 -5.80 -0.88588605 -0.7344021 -15.2858860 -6.5344021 2
#> 6 1 -3.60 -1.70 0.65747306 -0.3554803 -2.9425269 -2.0554803 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6880 -37700 5775
#> initial value 998.131940
#> iter 2 value 834.023460
#> iter 3 value 827.284290
#> iter 4 value 826.728475
#> iter 5 value 787.034662
#> iter 6 value 778.799035
#> iter 7 value 777.075526
#> iter 8 value 777.034725
#> iter 9 value 777.034609
#> iter 10 value 777.034597
#> iter 10 value 777.034592
#> iter 10 value 777.034587
#> final value 777.034587
#> converged
#> This is Run number 155
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.9846353 2.0813401 -1.5346353 -10.518660 1
#> 2 1 -0.95 -2.35 0.3228183 -1.2500166 -0.6271817 -3.600017 1
#> 3 1 -6.20 -2.30 1.3564790 -0.5968467 -4.8435210 -2.896847 2
#> 4 1 -13.90 -2.55 0.3135420 -0.1155842 -13.5864580 -2.665584 2
#> 5 1 -14.40 -5.80 1.5523309 0.1802541 -12.8476691 -5.619746 2
#> 6 1 -3.60 -1.70 1.4359782 -1.2105459 -2.1640218 -2.910546 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6760 -39075 7000
#> initial value 998.131940
#> iter 2 value 808.235077
#> iter 3 value 796.796033
#> iter 4 value 796.120122
#> iter 5 value 760.557113
#> iter 6 value 751.932193
#> iter 7 value 750.559096
#> iter 8 value 750.528560
#> iter 9 value 750.528505
#> iter 10 value 750.528490
#> iter 10 value 750.528480
#> iter 10 value 750.528473
#> final value 750.528473
#> converged
#> This is Run number 156
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.3284442 -0.8323573 0.7784442 -13.432357 1
#> 2 1 -0.95 -2.35 -0.2553660 -0.1226016 -1.2053660 -2.472602 1
#> 3 1 -6.20 -2.30 0.9513305 2.0407260 -5.2486695 -0.259274 2
#> 4 1 -13.90 -2.55 1.8509883 1.2119672 -12.0490117 -1.338033 2
#> 5 1 -14.40 -5.80 0.2170416 0.6717132 -14.1829584 -5.128287 2
#> 6 1 -3.60 -1.70 -0.5796611 0.1742366 -4.1796611 -1.525763 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6520 -38875 7475
#> initial value 998.131940
#> iter 2 value 808.688095
#> iter 3 value 795.657059
#> iter 4 value 794.915069
#> iter 5 value 758.892339
#> iter 6 value 750.324033
#> iter 7 value 749.044868
#> iter 8 value 749.019613
#> iter 9 value 749.019578
#> iter 10 value 749.019566
#> iter 10 value 749.019557
#> iter 10 value 749.019549
#> final value 749.019549
#> converged
#> This is Run number 157
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.1196599 0.3701395 -0.4303401 -12.22986050 1
#> 2 1 -0.95 -2.35 1.8375022 2.0634689 0.8875022 -0.28653107 1
#> 3 1 -6.20 -2.30 -0.2368146 0.5991558 -6.4368146 -1.70084418 2
#> 4 1 -13.90 -2.55 -0.7280566 1.1624193 -14.6280566 -1.38758066 2
#> 5 1 -14.40 -5.80 1.6802103 -0.1810604 -12.7197897 -5.98106041 2
#> 6 1 -3.60 -1.70 -0.1156988 1.7546507 -3.7156988 0.05465075 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7160 -40075 5850
#> initial value 998.131940
#> iter 2 value 798.311202
#> iter 3 value 789.045381
#> iter 4 value 787.698957
#> iter 5 value 755.128609
#> iter 6 value 746.366016
#> iter 7 value 744.780987
#> iter 8 value 744.737392
#> iter 9 value 744.737272
#> iter 10 value 744.737259
#> iter 10 value 744.737259
#> iter 10 value 744.737252
#> final value 744.737252
#> converged
#> This is Run number 158
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.01687771 -0.1186750 -0.5668777 -12.718675 1
#> 2 1 -0.95 -2.35 -0.31483839 1.2810316 -1.2648384 -1.068968 2
#> 3 1 -6.20 -2.30 1.48161290 0.6009233 -4.7183871 -1.699077 2
#> 4 1 -13.90 -2.55 -0.34127499 0.5603407 -14.2412750 -1.989659 2
#> 5 1 -14.40 -5.80 -0.85863450 -1.4289316 -15.2586345 -7.228932 2
#> 6 1 -3.60 -1.70 -0.69124424 0.3564565 -4.2912442 -1.343544 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5580 -37725 6075
#> initial value 998.131940
#> iter 2 value 833.062560
#> iter 3 value 819.839446
#> iter 4 value 816.162791
#> iter 5 value 777.306314
#> iter 6 value 768.889047
#> iter 7 value 767.425852
#> iter 8 value 767.394077
#> iter 9 value 767.394008
#> iter 9 value 767.393996
#> iter 9 value 767.393991
#> final value 767.393991
#> converged
#> This is Run number 159
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.6252827 1.56392814 1.0752827 -11.036072 1
#> 2 1 -0.95 -2.35 1.6101609 -0.70950821 0.6601609 -3.059508 1
#> 3 1 -6.20 -2.30 0.3404632 1.94502896 -5.8595368 -0.354971 2
#> 4 1 -13.90 -2.55 1.7445505 -0.45246603 -12.1554495 -3.002466 2
#> 5 1 -14.40 -5.80 2.3145823 3.10005494 -12.0854177 -2.699945 2
#> 6 1 -3.60 -1.70 -0.3846931 -0.07749941 -3.9846931 -1.777499 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6160 -38825 7325
#> initial value 998.131940
#> iter 2 value 810.565721
#> iter 3 value 796.559650
#> iter 4 value 794.769234
#> iter 5 value 758.876864
#> iter 6 value 750.342003
#> iter 7 value 749.063438
#> iter 8 value 749.038146
#> iter 9 value 749.038114
#> iter 9 value 749.038104
#> iter 9 value 749.038098
#> final value 749.038098
#> converged
#> This is Run number 160
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.1534838 0.1509388 -0.7034838 -12.449061 1
#> 2 1 -0.95 -2.35 -0.7931639 -1.1335804 -1.7431639 -3.483580 1
#> 3 1 -6.20 -2.30 0.1991533 -0.9363168 -6.0008467 -3.236317 2
#> 4 1 -13.90 -2.55 0.1736630 0.5310906 -13.7263370 -2.018909 2
#> 5 1 -14.40 -5.80 0.9010981 0.2076687 -13.4989019 -5.592331 2
#> 6 1 -3.60 -1.70 0.4056225 -0.4256635 -3.1943775 -2.125664 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6720 -40200 6725
#> initial value 998.131940
#> iter 2 value 792.504082
#> iter 3 value 779.511942
#> iter 4 value 777.665254
#> iter 5 value 745.791488
#> iter 6 value 737.045892
#> iter 7 value 735.750623
#> iter 8 value 735.720557
#> iter 9 value 735.720510
#> iter 9 value 735.720509
#> iter 9 value 735.720509
#> final value 735.720509
#> converged
#> This is Run number 161
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 3.8941682 -0.09420352 3.3441682 -12.6942035 1
#> 2 1 -0.95 -2.35 0.4358084 -0.64355644 -0.5141916 -2.9935564 1
#> 3 1 -6.20 -2.30 0.8005120 1.02216237 -5.3994880 -1.2778376 2
#> 4 1 -13.90 -2.55 1.1187836 1.30594143 -12.7812164 -1.2440586 2
#> 5 1 -14.40 -5.80 1.9581834 -0.51155744 -12.4418166 -6.3115574 2
#> 6 1 -3.60 -1.70 -0.1522272 0.90016952 -3.7522272 -0.7998305 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6180 -39575 6800
#> initial value 998.131940
#> iter 2 value 802.223079
#> iter 3 value 787.609132
#> iter 4 value 784.579141
#> iter 5 value 751.191393
#> iter 6 value 742.524072
#> iter 7 value 741.233800
#> iter 8 value 741.205637
#> iter 9 value 741.205597
#> iter 9 value 741.205590
#> iter 9 value 741.205585
#> final value 741.205585
#> converged
#> This is Run number 162
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.4024772 2.2065009 -0.1475228 -10.393499 1
#> 2 1 -0.95 -2.35 1.9501775 -0.6720595 1.0001775 -3.022059 1
#> 3 1 -6.20 -2.30 2.4944470 1.1268340 -3.7055530 -1.173166 2
#> 4 1 -13.90 -2.55 1.0818204 -0.3008397 -12.8181796 -2.850840 2
#> 5 1 -14.40 -5.80 0.3670193 0.7052709 -14.0329807 -5.094729 2
#> 6 1 -3.60 -1.70 0.7669320 0.5907449 -2.8330680 -1.109255 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6460 -38400 6425
#> initial value 998.131940
#> iter 2 value 821.459643
#> iter 3 value 811.235144
#> iter 4 value 809.808167
#> iter 5 value 772.414800
#> iter 6 value 763.932312
#> iter 7 value 762.433650
#> iter 8 value 762.399186
#> iter 9 value 762.399114
#> iter 9 value 762.399113
#> iter 9 value 762.399113
#> final value 762.399113
#> converged
#> This is Run number 163
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.8459106 0.2562057 -1.3959106 -12.34379426 1
#> 2 1 -0.95 -2.35 1.8055598 -0.2288344 0.8555598 -2.57883441 1
#> 3 1 -6.20 -2.30 1.8646730 2.2020751 -4.3353270 -0.09792495 2
#> 4 1 -13.90 -2.55 0.8799374 -0.5573151 -13.0200626 -3.10731515 2
#> 5 1 -14.40 -5.80 4.7217307 0.2221229 -9.6782693 -5.57787711 2
#> 6 1 -3.60 -1.70 0.4361255 -0.8619898 -3.1638745 -2.56198977 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6480 -39225 7050
#> initial value 998.131940
#> iter 2 value 805.972527
#> iter 3 value 793.127502
#> iter 4 value 791.702106
#> iter 5 value 756.829082
#> iter 6 value 748.203899
#> iter 7 value 746.884422
#> iter 8 value 746.856053
#> iter 9 value 746.856009
#> iter 10 value 746.855998
#> iter 10 value 746.855989
#> iter 10 value 746.855983
#> final value 746.855983
#> converged
#> This is Run number 164
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.35174017 -0.2326349 0.8017402 -12.8326349 1
#> 2 1 -0.95 -2.35 0.04486872 0.4759409 -0.9051313 -1.8740591 1
#> 3 1 -6.20 -2.30 0.76992536 0.3174228 -5.4300746 -1.9825772 2
#> 4 1 -13.90 -2.55 -0.60627405 1.6330446 -14.5062740 -0.9169554 2
#> 5 1 -14.40 -5.80 -1.34156099 -0.7300498 -15.7415610 -6.5300498 2
#> 6 1 -3.60 -1.70 4.19109845 -0.5847035 0.5910984 -2.2847035 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7340 -40925 6625
#> initial value 998.131940
#> iter 2 value 780.605962
#> iter 3 value 769.056220
#> iter 4 value 768.294039
#> iter 5 value 738.250872
#> iter 6 value 729.435459
#> iter 7 value 728.148023
#> iter 8 value 728.116321
#> iter 9 value 728.116266
#> iter 10 value 728.116255
#> iter 10 value 728.116248
#> iter 10 value 728.116241
#> final value 728.116241
#> converged
#> This is Run number 165
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.4828286 -0.77702401 0.9328286 -13.377024 1
#> 2 1 -0.95 -2.35 -0.1076765 0.28578178 -1.0576765 -2.064218 1
#> 3 1 -6.20 -2.30 1.5515890 -1.37701768 -4.6484110 -3.677018 2
#> 4 1 -13.90 -2.55 0.7053390 0.04244316 -13.1946610 -2.507557 2
#> 5 1 -14.40 -5.80 -0.3282014 4.34726022 -14.7282014 -1.452740 2
#> 6 1 -3.60 -1.70 1.5438018 -0.65594209 -2.0561982 -2.355942 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6600 -39450 7250
#> initial value 998.131940
#> iter 2 value 801.327289
#> iter 3 value 788.069927
#> iter 4 value 786.986615
#> iter 5 value 752.732022
#> iter 6 value 744.083323
#> iter 7 value 742.808823
#> iter 8 value 742.782266
#> iter 9 value 742.782229
#> iter 10 value 742.782218
#> iter 10 value 742.782208
#> iter 10 value 742.782202
#> final value 742.782202
#> converged
#> This is Run number 166
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 3.2470518 -1.5662488 2.6970518 -14.166249 1
#> 2 1 -0.95 -2.35 1.5102476 0.5018118 0.5602476 -1.848188 1
#> 3 1 -6.20 -2.30 0.7285373 -0.9111377 -5.4714627 -3.211138 2
#> 4 1 -13.90 -2.55 1.0032664 0.5799024 -12.8967336 -1.970098 2
#> 5 1 -14.40 -5.80 -1.0072278 2.3951188 -15.4072278 -3.404881 2
#> 6 1 -3.60 -1.70 -0.5007747 -0.1459498 -4.1007747 -1.845950 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6020 -37850 6450
#> initial value 998.131940
#> iter 2 value 829.396853
#> iter 3 value 818.195621
#> iter 4 value 815.979070
#> iter 5 value 777.273101
#> iter 6 value 768.912330
#> iter 7 value 767.450212
#> iter 8 value 767.418620
#> iter 9 value 767.418560
#> iter 9 value 767.418550
#> iter 9 value 767.418544
#> final value 767.418544
#> converged
#> This is Run number 167
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 6.210010956 0.9690609 5.6600110 -11.6309391 1
#> 2 1 -0.95 -2.35 0.128578778 1.5716314 -0.8214212 -0.7783686 2
#> 3 1 -6.20 -2.30 4.427367559 -0.7495352 -1.7726324 -3.0495352 1
#> 4 1 -13.90 -2.55 -0.432867145 0.8710364 -14.3328671 -1.6789636 2
#> 5 1 -14.40 -5.80 0.002340605 0.9181577 -14.3976594 -4.8818423 2
#> 6 1 -3.60 -1.70 -0.442111183 -0.2147327 -4.0421112 -1.9147327 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6260 -38350 7200
#> initial value 998.131940
#> iter 2 value 818.137327
#> iter 3 value 805.799048
#> iter 4 value 804.553795
#> iter 5 value 767.069334
#> iter 6 value 758.599634
#> iter 7 value 757.260562
#> iter 8 value 757.233309
#> iter 9 value 757.233267
#> iter 10 value 757.233254
#> iter 10 value 757.233244
#> iter 10 value 757.233238
#> final value 757.233238
#> converged
#> This is Run number 168
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.16828034 -0.19179388 -0.7182803 -12.791794 1
#> 2 1 -0.95 -2.35 -0.01768426 -0.95595519 -0.9676843 -3.305955 1
#> 3 1 -6.20 -2.30 1.07361811 0.12428209 -5.1263819 -2.175718 2
#> 4 1 -13.90 -2.55 -1.48609969 0.04991446 -15.3860997 -2.500086 2
#> 5 1 -14.40 -5.80 0.56137385 3.00713266 -13.8386262 -2.792867 2
#> 6 1 -3.60 -1.70 0.51907780 -0.28979636 -3.0809222 -1.989796 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5800 -36425 6625
#> initial value 998.131940
#> iter 2 value 847.707465
#> iter 3 value 838.185997
#> iter 4 value 836.660612
#> iter 5 value 793.887708
#> iter 6 value 785.953742
#> iter 7 value 784.537768
#> iter 8 value 784.510629
#> iter 9 value 784.510581
#> iter 9 value 784.510578
#> iter 9 value 784.510578
#> final value 784.510578
#> converged
#> This is Run number 169
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 4.4480199 -0.75530324 3.8980199 -13.3553032 1
#> 2 1 -0.95 -2.35 0.8271159 1.36319291 -0.1228841 -0.9868071 1
#> 3 1 -6.20 -2.30 2.9929490 5.74847339 -3.2070510 3.4484734 2
#> 4 1 -13.90 -2.55 -1.2897084 2.81034097 -15.1897084 0.2603410 2
#> 5 1 -14.40 -5.80 0.6008244 0.72731480 -13.7991756 -5.0726852 2
#> 6 1 -3.60 -1.70 0.5481241 -0.06931992 -3.0518759 -1.7693199 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7360 -39400 6650
#> initial value 998.131940
#> iter 2 value 804.455522
#> iter 3 value 794.918487
#> iter 4 value 794.819545
#> iter 5 value 759.968614
#> iter 6 value 751.295296
#> iter 7 value 749.801974
#> iter 8 value 749.764962
#> iter 9 value 749.764873
#> iter 10 value 749.764854
#> iter 10 value 749.764846
#> iter 10 value 749.764837
#> final value 749.764837
#> converged
#> This is Run number 170
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.18507888 0.16385218 -0.3649211 -12.436148 1
#> 2 1 -0.95 -2.35 0.39011929 0.91902517 -0.5598807 -1.430975 1
#> 3 1 -6.20 -2.30 0.21859640 -0.55904567 -5.9814036 -2.859046 2
#> 4 1 -13.90 -2.55 -1.12228819 -0.38246311 -15.0222882 -2.932463 2
#> 5 1 -14.40 -5.80 0.07611045 1.03420648 -14.3238895 -4.765794 2
#> 6 1 -3.60 -1.70 0.29273584 0.03752286 -3.3072642 -1.662477 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6420 -38725 6925
#> initial value 998.131940
#> iter 2 value 814.132713
#> iter 3 value 802.258990
#> iter 4 value 800.931184
#> iter 5 value 764.520624
#> iter 6 value 755.970302
#> iter 7 value 754.592956
#> iter 8 value 754.563019
#> iter 9 value 754.562967
#> iter 10 value 754.562955
#> iter 10 value 754.562945
#> iter 10 value 754.562945
#> final value 754.562945
#> converged
#> This is Run number 171
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.38130658 1.0115170 -0.1686934 -11.588483 1
#> 2 1 -0.95 -2.35 0.01982722 1.2410011 -0.9301728 -1.108999 1
#> 3 1 -6.20 -2.30 0.77813010 -0.7520586 -5.4218699 -3.052059 2
#> 4 1 -13.90 -2.55 0.49137246 -0.7456776 -13.4086275 -3.295678 2
#> 5 1 -14.40 -5.80 1.00506794 -0.6362403 -13.3949321 -6.436240 2
#> 6 1 -3.60 -1.70 -0.91253799 0.1935483 -4.5125380 -1.506452 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6860 -40575 6875
#> initial value 998.131940
#> iter 2 value 785.566447
#> iter 3 value 772.155593
#> iter 4 value 770.588870
#> iter 5 value 739.805612
#> iter 6 value 731.052874
#> iter 7 value 729.821595
#> iter 8 value 729.793782
#> iter 9 value 729.793744
#> iter 9 value 729.793735
#> iter 9 value 729.793729
#> final value 729.793729
#> converged
#> This is Run number 172
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.4409470 -0.7932469 -0.99094698 -13.393247 1
#> 2 1 -0.95 -2.35 0.9145395 -0.3289082 -0.03546045 -2.678908 1
#> 3 1 -6.20 -2.30 1.1574568 -0.7803319 -5.04254318 -3.080332 2
#> 4 1 -13.90 -2.55 -0.6775352 -0.5768270 -14.57753519 -3.126827 2
#> 5 1 -14.40 -5.80 0.7977654 -0.2551995 -13.60223459 -6.055199 2
#> 6 1 -3.60 -1.70 -1.0778157 0.3826733 -4.67781574 -1.317327 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5900 -39625 6850
#> initial value 998.131940
#> iter 2 value 801.282254
#> iter 3 value 784.716401
#> iter 4 value 780.606245
#> iter 5 value 747.641999
#> iter 6 value 738.977177
#> iter 7 value 737.740404
#> iter 8 value 737.714532
#> iter 9 value 737.714500
#> iter 9 value 737.714494
#> iter 9 value 737.714490
#> final value 737.714490
#> converged
#> This is Run number 173
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.421346074 0.4893955 0.8713461 -12.1106045 1
#> 2 1 -0.95 -2.35 2.216092730 3.1490119 1.2660927 0.7990119 1
#> 3 1 -6.20 -2.30 1.900551535 1.4918179 -4.2994485 -0.8081821 2
#> 4 1 -13.90 -2.55 1.063080893 1.1520007 -12.8369191 -1.3979993 2
#> 5 1 -14.40 -5.80 -0.003249443 1.4609062 -14.4032494 -4.3390938 2
#> 6 1 -3.60 -1.70 1.932355926 0.7714596 -1.6676441 -0.9285404 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6020 -37375 6250
#> initial value 998.131940
#> iter 2 value 836.943545
#> iter 3 value 826.925249
#> iter 4 value 824.938504
#> iter 5 value 784.846526
#> iter 6 value 776.624489
#> iter 7 value 775.116530
#> iter 8 value 775.084256
#> iter 9 value 775.084190
#> iter 9 value 775.084180
#> iter 9 value 775.084175
#> final value 775.084175
#> converged
#> This is Run number 174
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.31013417 -0.2115279 -0.8601342 -12.8115279 1
#> 2 1 -0.95 -2.35 -0.53787463 -0.3893213 -1.4878746 -2.7393213 1
#> 3 1 -6.20 -2.30 0.04893292 -0.3078683 -6.1510671 -2.6078683 2
#> 4 1 -13.90 -2.55 -0.28150001 1.6459548 -14.1815000 -0.9040452 2
#> 5 1 -14.40 -5.80 1.56821981 1.8214466 -12.8317802 -3.9785534 2
#> 6 1 -3.60 -1.70 -0.35828502 2.0678416 -3.9582850 0.3678416 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6080 -39400 7425
#> initial value 998.131940
#> iter 2 value 801.411006
#> iter 3 value 785.492116
#> iter 4 value 782.999205
#> iter 5 value 749.073145
#> iter 6 value 740.496753
#> iter 7 value 739.288779
#> iter 8 value 739.265701
#> iter 9 value 739.265679
#> iter 9 value 739.265672
#> iter 9 value 739.265666
#> final value 739.265666
#> converged
#> This is Run number 175
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.8872974 0.12341300 0.3372974 -12.4765870 1
#> 2 1 -0.95 -2.35 1.6189959 1.68494407 0.6689959 -0.6650559 1
#> 3 1 -6.20 -2.30 1.8328573 -0.34986021 -4.3671427 -2.6498602 2
#> 4 1 -13.90 -2.55 0.3975676 -0.46245576 -13.5024324 -3.0124558 2
#> 5 1 -14.40 -5.80 0.3211577 -0.06038181 -14.0788423 -5.8603818 2
#> 6 1 -3.60 -1.70 -1.0312273 -1.01319438 -4.6312273 -2.7131944 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5720 -37425 8125
#> initial value 998.131940
#> iter 2 value 825.669270
#> iter 3 value 811.266908
#> iter 4 value 809.984140
#> iter 5 value 769.899215
#> iter 6 value 761.667549
#> iter 7 value 760.451298
#> iter 8 value 760.432272
#> iter 9 value 760.432257
#> iter 9 value 760.432255
#> iter 10 value 760.432241
#> iter 10 value 760.432231
#> iter 10 value 760.432231
#> final value 760.432231
#> converged
#> This is Run number 176
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 3.3745435 -0.29377364 2.8245435 -12.893774 1
#> 2 1 -0.95 -2.35 -0.5793627 0.32469731 -1.5293627 -2.025303 1
#> 3 1 -6.20 -2.30 -0.8267588 -1.55561020 -7.0267588 -3.855610 2
#> 4 1 -13.90 -2.55 1.1583074 -0.05119815 -12.7416926 -2.601198 2
#> 5 1 -14.40 -5.80 0.9096218 0.31094409 -13.4903782 -5.489056 2
#> 6 1 -3.60 -1.70 3.2312005 -0.13720072 -0.3687995 -1.837201 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6960 -40275 7050
#> initial value 998.131940
#> iter 2 value 789.275549
#> iter 3 value 776.363160
#> iter 4 value 775.464621
#> iter 5 value 743.600302
#> iter 6 value 734.854965
#> iter 7 value 733.603681
#> iter 8 value 733.576007
#> iter 9 value 733.575967
#> iter 10 value 733.575956
#> iter 10 value 733.575947
#> iter 10 value 733.575940
#> final value 733.575940
#> converged
#> This is Run number 177
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.174721419 0.2918176 1.6247214 -12.3081824 1
#> 2 1 -0.95 -2.35 1.541069712 0.4410086 0.5910697 -1.9089914 1
#> 3 1 -6.20 -2.30 -1.090772027 1.9146486 -7.2907720 -0.3853514 2
#> 4 1 -13.90 -2.55 0.377090608 -0.9893143 -13.5229094 -3.5393143 2
#> 5 1 -14.40 -5.80 -0.919079935 -0.7391974 -15.3190799 -6.5391974 2
#> 6 1 -3.60 -1.70 0.001740311 1.1685960 -3.5982597 -0.5314040 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6380 -38825 6750
#> initial value 998.131940
#> iter 2 value 813.643151
#> iter 3 value 801.736130
#> iter 4 value 800.051369
#> iter 5 value 764.017687
#> iter 6 value 755.447785
#> iter 7 value 754.051034
#> iter 8 value 754.019933
#> iter 9 value 754.019878
#> iter 10 value 754.019866
#> iter 10 value 754.019858
#> iter 10 value 754.019857
#> final value 754.019857
#> converged
#> This is Run number 178
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.157130763 2.14610729 -0.7071308 -10.4538927 1
#> 2 1 -0.95 -2.35 -1.577677435 0.07339648 -2.5276774 -2.2766035 2
#> 3 1 -6.20 -2.30 -0.003356045 -0.17701049 -6.2033560 -2.4770105 2
#> 4 1 -13.90 -2.55 1.337153663 -0.22073210 -12.5628463 -2.7707321 2
#> 5 1 -14.40 -5.80 1.206183765 -0.88403495 -13.1938162 -6.6840350 2
#> 6 1 -3.60 -1.70 1.164644577 2.39105834 -2.4353554 0.6910583 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6160 -39225 7500
#> initial value 998.131940
#> iter 2 value 803.573969
#> iter 3 value 788.306160
#> iter 4 value 786.339931
#> iter 5 value 751.742337
#> iter 6 value 743.178570
#> iter 7 value 741.958460
#> iter 8 value 741.935311
#> iter 9 value 741.935288
#> iter 9 value 741.935279
#> iter 9 value 741.935273
#> final value 741.935273
#> converged
#> This is Run number 179
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.36614924 0.3678008 -1.916149 -12.232199 1
#> 2 1 -0.95 -2.35 -0.09774777 0.4061983 -1.047748 -1.943802 1
#> 3 1 -6.20 -2.30 -1.38289196 0.1333675 -7.582892 -2.166633 2
#> 4 1 -13.90 -2.55 -0.60933313 -0.3739232 -14.509333 -2.923923 2
#> 5 1 -14.40 -5.80 1.08012001 2.0695022 -13.319880 -3.730498 2
#> 6 1 -3.60 -1.70 1.76909512 -0.6888554 -1.830905 -2.388855 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5380 -38450 8225
#> initial value 998.131940
#> iter 2 value 810.608798
#> iter 3 value 791.580833
#> iter 4 value 788.319662
#> iter 5 value 751.898298
#> iter 6 value 743.572566
#> iter 7 value 742.413209
#> iter 8 value 742.395716
#> iter 8 value 742.395707
#> final value 742.395707
#> converged
#> This is Run number 180
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.42984402 1.15624238 -1.979844 -11.4437576 1
#> 2 1 -0.95 -2.35 0.47558499 1.25333024 -0.474415 -1.0966698 1
#> 3 1 -6.20 -2.30 0.92039109 0.23790478 -5.279609 -2.0620952 2
#> 4 1 -13.90 -2.55 0.11262462 3.27760830 -13.787375 0.7276083 2
#> 5 1 -14.40 -5.80 -0.08676749 0.61826096 -14.486767 -5.1817390 2
#> 6 1 -3.60 -1.70 0.63872769 0.04009302 -2.961272 -1.6599070 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5860 -37675 7550
#> initial value 998.131940
#> iter 2 value 825.792327
#> iter 3 value 812.538935
#> iter 4 value 810.995136
#> iter 5 value 771.683888
#> iter 6 value 763.380591
#> iter 7 value 762.092411
#> iter 8 value 762.069000
#> iter 9 value 762.068970
#> iter 9 value 762.068959
#> iter 9 value 762.068953
#> final value 762.068953
#> converged
#> This is Run number 181
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.5501851 -1.44881516 1.851489e-04 -14.048815 1
#> 2 1 -0.95 -2.35 -0.9403997 2.01401200 -1.890400e+00 -0.335988 2
#> 3 1 -6.20 -2.30 3.2561479 0.02313325 -2.943852e+00 -2.276867 2
#> 4 1 -13.90 -2.55 -0.6795747 0.93851184 -1.457957e+01 -1.611488 2
#> 5 1 -14.40 -5.80 3.2273245 2.75636301 -1.117268e+01 -3.043637 2
#> 6 1 -3.60 -1.70 1.3287723 0.62510498 -2.271228e+00 -1.074895 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6160 -37525 7050
#> initial value 998.131940
#> iter 2 value 830.623869
#> iter 3 value 819.786132
#> iter 4 value 818.726984
#> iter 5 value 778.803378
#> iter 6 value 770.524132
#> iter 7 value 769.135738
#> iter 8 value 769.107769
#> iter 9 value 769.107721
#> iter 10 value 769.107707
#> iter 10 value 769.107696
#> iter 10 value 769.107692
#> final value 769.107692
#> converged
#> This is Run number 182
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.3877798 1.5985972 0.8377798 -11.0014028 1
#> 2 1 -0.95 -2.35 -0.7188988 -0.9631932 -1.6688988 -3.3131932 1
#> 3 1 -6.20 -2.30 0.9125603 -0.1913886 -5.2874397 -2.4913886 2
#> 4 1 -13.90 -2.55 2.4980210 -1.3445891 -11.4019790 -3.8945891 2
#> 5 1 -14.40 -5.80 -1.2407653 0.8945358 -15.6407653 -4.9054642 2
#> 6 1 -3.60 -1.70 2.6447546 1.3720081 -0.9552454 -0.3279919 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6700 -39350 7025
#> initial value 998.131940
#> iter 2 value 804.029515
#> iter 3 value 791.861529
#> iter 4 value 790.907386
#> iter 5 value 756.253960
#> iter 6 value 747.596710
#> iter 7 value 746.261089
#> iter 8 value 746.231653
#> iter 9 value 746.231605
#> iter 10 value 746.231591
#> iter 10 value 746.231582
#> iter 10 value 746.231575
#> final value 746.231575
#> converged
#> This is Run number 183
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.80651529 -0.8156940 0.2565153 -13.415694 1
#> 2 1 -0.95 -2.35 -0.06376154 0.9184796 -1.0137615 -1.431520 1
#> 3 1 -6.20 -2.30 -0.16201991 0.3479954 -6.3620199 -1.952005 2
#> 4 1 -13.90 -2.55 -0.34846009 0.1217536 -14.2484601 -2.428246 2
#> 5 1 -14.40 -5.80 -0.63207541 -0.3123931 -15.0320754 -6.112393 2
#> 6 1 -3.60 -1.70 1.88403816 2.0195630 -1.7159618 0.319563 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6280 -37550 6825
#> initial value 998.131940
#> iter 2 value 831.441654
#> iter 3 value 821.382124
#> iter 4 value 820.418177
#> iter 5 value 780.517258
#> iter 6 value 772.236743
#> iter 7 value 770.800043
#> iter 8 value 770.769984
#> iter 9 value 770.769926
#> iter 10 value 770.769912
#> iter 10 value 770.769902
#> iter 10 value 770.769895
#> final value 770.769895
#> converged
#> This is Run number 184
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.5336898 0.01430224 -1.0836898 -12.585698 1
#> 2 1 -0.95 -2.35 0.5064921 -0.80267268 -0.4435079 -3.152673 1
#> 3 1 -6.20 -2.30 0.7161820 0.93388315 -5.4838180 -1.366117 2
#> 4 1 -13.90 -2.55 1.8915819 -0.08514197 -12.0084181 -2.635142 2
#> 5 1 -14.40 -5.80 6.7373003 0.54983778 -7.6626997 -5.250162 2
#> 6 1 -3.60 -1.70 -0.7919913 -0.13593672 -4.3919913 -1.835937 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6720 -39750 6125
#> initial value 998.131940
#> iter 2 value 802.582106
#> iter 3 value 791.516142
#> iter 4 value 789.415144
#> iter 5 value 756.164762
#> iter 6 value 747.435155
#> iter 7 value 745.952436
#> iter 8 value 745.914516
#> iter 9 value 745.914429
#> iter 9 value 745.914418
#> iter 9 value 745.914411
#> final value 745.914411
#> converged
#> This is Run number 185
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.15265139 2.2761791 0.6026514 -10.32382089 1
#> 2 1 -0.95 -2.35 -0.30652863 -0.3118787 -1.2565286 -2.66187870 1
#> 3 1 -6.20 -2.30 -0.41694314 1.1836174 -6.6169431 -1.11638259 2
#> 4 1 -13.90 -2.55 0.41632608 2.6217143 -13.4836739 0.07171428 2
#> 5 1 -14.40 -5.80 -0.03841894 1.2841927 -14.4384189 -4.51580730 2
#> 6 1 -3.60 -1.70 -0.50718130 -0.5421385 -4.1071813 -2.24213851 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6320 -37575 6500
#> initial value 998.131940
#> iter 2 value 832.782799
#> iter 3 value 823.351503
#> iter 4 value 822.216163
#> iter 5 value 782.414388
#> iter 6 value 774.140895
#> iter 7 value 772.643795
#> iter 8 value 772.611360
#> iter 9 value 772.611293
#> iter 9 value 772.611291
#> iter 9 value 772.611291
#> final value 772.611291
#> converged
#> This is Run number 186
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.31849409 -1.1475188 -0.2315059 -13.7475188 1
#> 2 1 -0.95 -2.35 -0.22081305 1.6985502 -1.1708130 -0.6514498 2
#> 3 1 -6.20 -2.30 0.05877666 0.1210087 -6.1412233 -2.1789913 2
#> 4 1 -13.90 -2.55 0.40693132 -0.3927151 -13.4930687 -2.9427151 2
#> 5 1 -14.40 -5.80 0.83378602 0.9974509 -13.5662140 -4.8025491 2
#> 6 1 -3.60 -1.70 2.03295389 0.9473908 -1.5670461 -0.7526092 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6580 -37500 6275
#> initial value 998.131940
#> iter 2 value 834.726166
#> iter 3 value 826.636796
#> iter 4 value 825.947470
#> iter 5 value 785.782981
#> iter 6 value 777.551282
#> iter 7 value 775.976183
#> iter 8 value 775.941005
#> iter 9 value 775.940921
#> iter 9 value 775.940919
#> iter 9 value 775.940919
#> final value 775.940919
#> converged
#> This is Run number 187
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.1768436 -0.4033544 0.6268436 -13.0033544 1
#> 2 1 -0.95 -2.35 1.7434304 3.3584012 0.7934304 1.0084012 2
#> 3 1 -6.20 -2.30 0.4410919 -0.9225754 -5.7589081 -3.2225754 2
#> 4 1 -13.90 -2.55 0.9139621 -0.4707154 -12.9860379 -3.0207154 2
#> 5 1 -14.40 -5.80 1.8159705 -0.3670249 -12.5840295 -6.1670249 2
#> 6 1 -3.60 -1.70 -0.1686814 2.1369949 -3.7686814 0.4369949 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6280 -37975 6525
#> initial value 998.131940
#> iter 2 value 827.122648
#> iter 3 value 816.774891
#> iter 4 value 815.272899
#> iter 5 value 776.706030
#> iter 6 value 768.322593
#> iter 7 value 766.846473
#> iter 8 value 766.813985
#> iter 9 value 766.813920
#> iter 9 value 766.813920
#> iter 9 value 766.813920
#> final value 766.813920
#> converged
#> This is Run number 188
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.0338425 0.8205150 1.483843 -11.7794850 1
#> 2 1 -0.95 -2.35 -0.8180443 -0.8602384 -1.768044 -3.2102384 1
#> 3 1 -6.20 -2.30 0.6849739 -0.3229602 -5.515026 -2.6229602 2
#> 4 1 -13.90 -2.55 0.3239195 1.8556292 -13.576080 -0.6943708 2
#> 5 1 -14.40 -5.80 -0.7300829 -0.2151003 -15.130083 -6.0151003 2
#> 6 1 -3.60 -1.70 1.4884202 -0.5213997 -2.111580 -2.2213997 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5840 -36775 6075
#> initial value 998.131940
#> iter 2 value 845.878251
#> iter 3 value 836.328672
#> iter 4 value 834.205564
#> iter 5 value 792.548050
#> iter 6 value 784.507969
#> iter 7 value 782.994471
#> iter 8 value 782.963394
#> iter 9 value 782.963331
#> iter 9 value 782.963321
#> iter 9 value 782.963317
#> final value 782.963317
#> converged
#> This is Run number 189
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.4316206 2.0186043 -0.9816206 -10.581396 1
#> 2 1 -0.95 -2.35 -0.9205920 0.9624501 -1.8705920 -1.387550 2
#> 3 1 -6.20 -2.30 -1.0869945 0.3877159 -7.2869945 -1.912284 2
#> 4 1 -13.90 -2.55 2.7058583 1.2630219 -11.1941417 -1.286978 2
#> 5 1 -14.40 -5.80 -0.1632859 -0.3171861 -14.5632859 -6.117186 2
#> 6 1 -3.60 -1.70 0.7129282 0.3385117 -2.8870718 -1.361488 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6500 -38400 6275
#> initial value 998.131940
#> iter 2 value 822.177848
#> iter 3 value 812.347784
#> iter 4 value 810.892362
#> iter 5 value 773.494169
#> iter 6 value 765.015975
#> iter 7 value 763.480907
#> iter 8 value 763.444953
#> iter 9 value 763.444873
#> iter 10 value 763.444861
#> iter 10 value 763.444854
#> iter 10 value 763.444851
#> final value 763.444851
#> converged
#> This is Run number 190
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.8669391 1.2829662 0.3169391 -11.3170338 1
#> 2 1 -0.95 -2.35 -0.4963417 1.0327632 -1.4463417 -1.3172368 2
#> 3 1 -6.20 -2.30 -0.1639651 2.4129229 -6.3639651 0.1129229 2
#> 4 1 -13.90 -2.55 2.1850226 -0.4910186 -11.7149774 -3.0410186 2
#> 5 1 -14.40 -5.80 0.4407121 0.6021247 -13.9592879 -5.1978753 2
#> 6 1 -3.60 -1.70 1.5326628 2.8870041 -2.0673372 1.1870041 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7420 -40625 4875
#> initial value 998.131940
#> iter 2 value 793.259227
#> iter 3 value 785.481207
#> iter 4 value 783.382954
#> iter 5 value 752.757599
#> iter 6 value 744.010708
#> iter 7 value 742.141658
#> iter 8 value 742.079824
#> iter 9 value 742.079515
#> iter 10 value 742.079487
#> iter 10 value 742.079486
#> iter 11 value 742.079468
#> iter 11 value 742.079462
#> iter 11 value 742.079459
#> final value 742.079459
#> converged
#> This is Run number 191
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.04740747 -0.21692241 -0.5974075 -12.81692241 1
#> 2 1 -0.95 -2.35 1.50952731 -0.55648315 0.5595273 -2.90648315 1
#> 3 1 -6.20 -2.30 0.59228059 -0.18472714 -5.6077194 -2.48472714 2
#> 4 1 -13.90 -2.55 0.69356433 0.02821362 -13.2064357 -2.52178638 2
#> 5 1 -14.40 -5.80 -0.15262047 1.87286297 -14.5526205 -3.92713703 2
#> 6 1 -3.60 -1.70 0.38306370 1.61245394 -3.2169363 -0.08754606 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6000 -38250 6925
#> initial value 998.131940
#> iter 2 value 821.246532
#> iter 3 value 808.446353
#> iter 4 value 806.263232
#> iter 5 value 768.732781
#> iter 6 value 760.285536
#> iter 7 value 758.922635
#> iter 8 value 758.894445
#> iter 9 value 758.894402
#> iter 9 value 758.894392
#> iter 9 value 758.894386
#> final value 758.894386
#> converged
#> This is Run number 192
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.77438849 0.3426618 2.224388 -12.257338 1
#> 2 1 -0.95 -2.35 3.31776593 0.4104071 2.367766 -1.939593 1
#> 3 1 -6.20 -2.30 -0.01538850 -1.3005204 -6.215388 -3.600520 2
#> 4 1 -13.90 -2.55 0.05183684 -1.0913297 -13.848163 -3.641330 2
#> 5 1 -14.40 -5.80 -0.54034107 0.2902806 -14.940341 -5.509719 2
#> 6 1 -3.60 -1.70 1.39107077 -0.6858458 -2.208929 -2.385846 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6440 -38950 5975
#> initial value 998.131940
#> iter 2 value 815.636264
#> iter 3 value 804.901308
#> iter 4 value 802.500386
#> iter 5 value 766.969640
#> iter 6 value 758.365476
#> iter 7 value 756.809996
#> iter 8 value 756.771283
#> iter 9 value 756.771187
#> iter 10 value 756.771175
#> iter 10 value 756.771175
#> iter 10 value 756.771170
#> final value 756.771170
#> converged
#> This is Run number 193
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.23681938 4.23561905 1.6868194 -8.364381 1
#> 2 1 -0.95 -2.35 0.62215365 -0.08347456 -0.3278463 -2.433475 1
#> 3 1 -6.20 -2.30 3.33367967 -0.82596626 -2.8663203 -3.125966 1
#> 4 1 -13.90 -2.55 -0.60050490 1.25185987 -14.5005049 -1.298140 2
#> 5 1 -14.40 -5.80 -1.04581477 -0.79087053 -15.4458148 -6.590871 2
#> 6 1 -3.60 -1.70 0.04483899 -0.13272195 -3.5551610 -1.832722 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5680 -38450 6875
#> initial value 998.131940
#> iter 2 value 818.718002
#> iter 3 value 803.697893
#> iter 4 value 800.168359
#> iter 5 value 763.562357
#> iter 6 value 755.061158
#> iter 7 value 753.740804
#> iter 8 value 753.714085
#> iter 9 value 753.714049
#> iter 9 value 753.714041
#> iter 9 value 753.714036
#> final value 753.714036
#> converged
#> This is Run number 194
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.2685430 -0.4870776 -0.8185430 -13.087078 1
#> 2 1 -0.95 -2.35 0.8251384 0.2982941 -0.1248616 -2.051706 1
#> 3 1 -6.20 -2.30 -0.4028685 0.1790501 -6.6028685 -2.120950 2
#> 4 1 -13.90 -2.55 0.2935466 -1.3087466 -13.6064534 -3.858747 2
#> 5 1 -14.40 -5.80 0.5960075 2.7431325 -13.8039925 -3.056868 2
#> 6 1 -3.60 -1.70 0.5781135 1.4689670 -3.0218865 -0.231033 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6960 -41000 6825
#> initial value 998.131940
#> iter 2 value 778.809209
#> iter 3 value 765.158628
#> iter 4 value 763.484505
#> iter 5 value 734.027050
#> iter 6 value 725.271131
#> iter 7 value 724.083866
#> iter 8 value 724.056948
#> iter 9 value 724.056913
#> iter 9 value 724.056912
#> iter 9 value 724.056912
#> final value 724.056912
#> converged
#> This is Run number 195
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.8492848 -0.53395365 2.2992848 -13.1339536 1
#> 2 1 -0.95 -2.35 0.3839092 1.63353669 -0.5660908 -0.7164633 1
#> 3 1 -6.20 -2.30 -0.5999922 -0.02843212 -6.7999922 -2.3284321 2
#> 4 1 -13.90 -2.55 -0.1481716 -1.16700661 -14.0481716 -3.7170066 2
#> 5 1 -14.40 -5.80 -0.1826396 0.62942178 -14.5826396 -5.1705782 2
#> 6 1 -3.60 -1.70 -0.3461750 0.92165860 -3.9461750 -0.7783414 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6920 -38300 7675
#> initial value 998.131940
#> iter 2 value 815.378508
#> iter 3 value 803.595570
#> iter 4 value 803.587425
#> iter 5 value 765.383725
#> iter 6 value 757.202761
#> iter 7 value 755.994848
#> iter 8 value 755.973212
#> iter 9 value 755.973177
#> iter 9 value 755.973170
#> iter 9 value 755.973160
#> final value 755.973160
#> converged
#> This is Run number 196
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.2584187 1.27538370 -0.2915813 -11.3246163 1
#> 2 1 -0.95 -2.35 -1.1944636 1.60267970 -2.1444636 -0.7473203 2
#> 3 1 -6.20 -2.30 0.3963088 0.04613938 -5.8036912 -2.2538606 2
#> 4 1 -13.90 -2.55 1.2945879 -1.05373477 -12.6054121 -3.6037348 2
#> 5 1 -14.40 -5.80 0.7435609 1.86424057 -13.6564391 -3.9357594 2
#> 6 1 -3.60 -1.70 -0.7769179 0.82060087 -4.3769179 -0.8793991 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6860 -40000 6125
#> initial value 998.131940
#> iter 2 value 798.553892
#> iter 3 value 787.687845
#> iter 4 value 785.804415
#> iter 5 value 753.230464
#> iter 6 value 744.470930
#> iter 7 value 742.997792
#> iter 8 value 742.959543
#> iter 9 value 742.959455
#> iter 9 value 742.959444
#> iter 9 value 742.959437
#> final value 742.959437
#> converged
#> This is Run number 197
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.1795092 0.1768442 0.6295092 -12.4231558 1
#> 2 1 -0.95 -2.35 0.4985522 2.6045716 -0.4514478 0.2545716 2
#> 3 1 -6.20 -2.30 -1.2315964 0.9454194 -7.4315964 -1.3545806 2
#> 4 1 -13.90 -2.55 -0.3435481 1.3788827 -14.2435481 -1.1711173 2
#> 5 1 -14.40 -5.80 3.7034150 -0.3254818 -10.6965850 -6.1254818 2
#> 6 1 -3.60 -1.70 2.0566962 3.7886589 -1.5433038 2.0886589 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6820 -40725 7125
#> initial value 998.131940
#> iter 2 value 781.788472
#> iter 3 value 767.303168
#> iter 4 value 765.751687
#> iter 5 value 735.496737
#> iter 6 value 726.782344
#> iter 7 value 725.620422
#> iter 8 value 725.595971
#> iter 9 value 725.595944
#> iter 9 value 725.595937
#> iter 9 value 725.595936
#> final value 725.595936
#> converged
#> This is Run number 198
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.676615 -0.4508708 2.1266146 -13.050871 1
#> 2 1 -0.95 -2.35 1.159416 -0.5837382 0.2094159 -2.933738 1
#> 3 1 -6.20 -2.30 1.261371 -0.7553756 -4.9386295 -3.055376 2
#> 4 1 -13.90 -2.55 2.460986 -0.4025537 -11.4390143 -2.952554 2
#> 5 1 -14.40 -5.80 0.898933 2.3905539 -13.5010670 -3.409446 2
#> 6 1 -3.60 -1.70 -1.191725 0.2209825 -4.7917249 -1.479018 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6640 -40000 7100
#> initial value 998.131940
#> iter 2 value 793.663299
#> iter 3 value 779.872106
#> iter 4 value 778.346302
#> iter 5 value 745.856404
#> iter 6 value 737.157314
#> iter 7 value 735.913605
#> iter 8 value 735.886988
#> iter 9 value 735.886953
#> iter 9 value 735.886943
#> iter 9 value 735.886936
#> final value 735.886936
#> converged
#> This is Run number 199
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.5658026 0.1511926 -1.11580255 -12.4488074 1
#> 2 1 -0.95 -2.35 0.8758248 1.6622111 -0.07417522 -0.6877889 1
#> 3 1 -6.20 -2.30 -0.1747381 1.3247372 -6.37473815 -0.9752628 2
#> 4 1 -13.90 -2.55 -0.6417134 1.1229533 -14.54171342 -1.4270467 2
#> 5 1 -14.40 -5.80 1.6665734 -0.2648074 -12.73342657 -6.0648074 2
#> 6 1 -3.60 -1.70 -0.2353709 0.8166244 -3.83537086 -0.8833756 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6340 -39625 6575
#> initial value 998.131940
#> iter 2 value 802.556116
#> iter 3 value 789.091674
#> iter 4 value 786.330848
#> iter 5 value 752.974064
#> iter 6 value 744.278695
#> iter 7 value 742.933661
#> iter 8 value 742.902636
#> iter 9 value 742.902584
#> iter 9 value 742.902575
#> iter 9 value 742.902570
#> final value 742.902570
#> converged
#> This is Run number 200
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.74858405 -0.5936579 0.1985841 -13.19365786 1
#> 2 1 -0.95 -2.35 -0.50898491 0.2072589 -1.4589849 -2.14274111 1
#> 3 1 -6.20 -2.30 2.07503380 3.9442964 -4.1249662 1.64429640 2
#> 4 1 -13.90 -2.55 -0.08858795 2.1107706 -13.9885880 -0.43922944 2
#> 5 1 -14.40 -5.80 0.76113817 -0.5174640 -13.6388618 -6.31746397 2
#> 6 1 -3.60 -1.70 -0.70785248 1.7888556 -4.3078525 0.08885562 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5920 -38250 7125
#> initial value 998.131940
#> iter 2 value 820.162332
#> iter 3 value 806.641201
#> iter 4 value 804.398536
#> iter 5 value 766.912473
#> iter 6 value 758.474755
#> iter 7 value 757.149550
#> iter 8 value 757.123155
#> iter 9 value 757.123118
#> iter 9 value 757.123108
#> iter 9 value 757.123102
#> final value 757.123102
#> converged
#> This is Run number 201
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.7083281 -0.23988548 -1.258328e+00 -12.839885 1
#> 2 1 -0.95 -2.35 0.9506646 -0.50004482 6.645586e-04 -2.850045 1
#> 3 1 -6.20 -2.30 -0.1447649 -0.03361594 -6.344765e+00 -2.333616 2
#> 4 1 -13.90 -2.55 5.9692551 -1.35843711 -7.930745e+00 -3.908437 2
#> 5 1 -14.40 -5.80 -0.6342011 2.02312797 -1.503420e+01 -3.776872 2
#> 6 1 -3.60 -1.70 -0.3238174 -0.69004692 -3.923817e+00 -2.390047 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6820 -39875 5950
#> initial value 998.131940
#> iter 2 value 801.375294
#> iter 3 value 790.814640
#> iter 4 value 788.724097
#> iter 5 value 755.826632
#> iter 6 value 747.081158
#> iter 7 value 745.554604
#> iter 8 value 745.514137
#> iter 9 value 745.514034
#> iter 10 value 745.514022
#> iter 10 value 745.514022
#> iter 10 value 745.514016
#> final value 745.514016
#> converged
#> This is Run number 202
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.5697809 -0.7909869 0.01978094 -13.3909869 1
#> 2 1 -0.95 -2.35 2.4273928 1.6648303 1.47739277 -0.6851697 1
#> 3 1 -6.20 -2.30 1.4611589 0.3452577 -4.73884110 -1.9547423 2
#> 4 1 -13.90 -2.55 -0.8986482 0.3966028 -14.79864816 -2.1533972 2
#> 5 1 -14.40 -5.80 -1.2740867 0.3010369 -15.67408671 -5.4989631 2
#> 6 1 -3.60 -1.70 1.5582558 -1.1247511 -2.04174419 -2.8247511 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6480 -37450 6125
#> initial value 998.131940
#> iter 2 value 836.231956
#> iter 3 value 828.120323
#> iter 4 value 827.144406
#> iter 5 value 786.934084
#> iter 6 value 778.723677
#> iter 7 value 777.133218
#> iter 8 value 777.097716
#> iter 9 value 777.097631
#> iter 9 value 777.097630
#> iter 9 value 777.097630
#> final value 777.097630
#> converged
#> This is Run number 203
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.97575981 1.77107368 -1.525760 -10.828926 1
#> 2 1 -0.95 -2.35 -0.47955729 -0.02563109 -1.429557 -2.375631 1
#> 3 1 -6.20 -2.30 -0.11500065 0.24392994 -6.315001 -2.056070 2
#> 4 1 -13.90 -2.55 -0.32306038 1.25897720 -14.223060 -1.291023 2
#> 5 1 -14.40 -5.80 0.07754566 -0.51699646 -14.322454 -6.316996 2
#> 6 1 -3.60 -1.70 -1.26012197 -0.26795801 -4.860122 -1.967958 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5540 -37525 7425
#> initial value 998.131940
#> iter 2 value 828.662301
#> iter 3 value 814.421967
#> iter 4 value 811.902972
#> iter 5 value 772.426458
#> iter 6 value 764.166167
#> iter 7 value 762.877585
#> iter 8 value 762.854421
#> iter 9 value 762.854394
#> iter 9 value 762.854384
#> iter 9 value 762.854379
#> final value 762.854379
#> converged
#> This is Run number 204
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.82756837 0.9945737 2.2775684 -11.605426 1
#> 2 1 -0.95 -2.35 0.02854267 -0.2602364 -0.9214573 -2.610236 1
#> 3 1 -6.20 -2.30 0.98715561 1.1569931 -5.2128444 -1.143007 2
#> 4 1 -13.90 -2.55 0.03342283 1.0614358 -13.8665772 -1.488564 2
#> 5 1 -14.40 -5.80 -0.01490610 -0.1229999 -14.4149061 -5.923000 2
#> 6 1 -3.60 -1.70 3.19890631 0.3938729 -0.4010937 -1.306127 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5640 -36900 7025
#> initial value 998.131940
#> iter 2 value 839.381554
#> iter 3 value 827.670726
#> iter 4 value 825.665146
#> iter 5 value 784.278678
#> iter 6 value 776.177329
#> iter 7 value 774.822840
#> iter 8 value 774.797450
#> iter 9 value 774.797412
#> iter 9 value 774.797401
#> iter 9 value 774.797396
#> final value 774.797396
#> converged
#> This is Run number 205
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.6653152 0.2775223 -1.215315 -12.322478 1
#> 2 1 -0.95 -2.35 -0.3506892 0.9136511 -1.300689 -1.436349 1
#> 3 1 -6.20 -2.30 -0.3339382 4.8395650 -6.533938 2.539565 2
#> 4 1 -13.90 -2.55 0.6295637 1.0879722 -13.270436 -1.462028 2
#> 5 1 -14.40 -5.80 -0.4716169 -0.4118703 -14.871617 -6.211870 2
#> 6 1 -3.60 -1.70 0.1401795 -1.1066294 -3.459821 -2.806629 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6720 -38450 6425
#> initial value 998.131940
#> iter 2 value 820.500551
#> iter 3 value 811.148662
#> iter 4 value 810.325943
#> iter 5 value 772.873807
#> iter 6 value 764.382310
#> iter 7 value 762.850214
#> iter 8 value 762.814215
#> iter 9 value 762.814132
#> iter 10 value 762.814118
#> iter 10 value 762.814109
#> iter 10 value 762.814105
#> final value 762.814105
#> converged
#> This is Run number 206
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.00562084 1.3004540 0.4556208 -11.299546 1
#> 2 1 -0.95 -2.35 1.35113052 0.5180916 0.4011305 -1.831908 1
#> 3 1 -6.20 -2.30 0.69321991 0.2222753 -5.5067801 -2.077725 2
#> 4 1 -13.90 -2.55 -0.53267292 -0.1220737 -14.4326729 -2.672074 2
#> 5 1 -14.40 -5.80 2.19095060 0.5133671 -12.2090494 -5.286633 2
#> 6 1 -3.60 -1.70 -0.01871406 0.5301702 -3.6187141 -1.169830 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6640 -38975 8000
#> initial value 998.131940
#> iter 2 value 803.832796
#> iter 3 value 789.484828
#> iter 4 value 789.203618
#> iter 5 value 753.507337
#> iter 6 value 744.940445
#> iter 7 value 743.754970
#> iter 8 value 743.734896
#> iter 9 value 743.734873
#> iter 9 value 743.734867
#> iter 9 value 743.734863
#> final value 743.734863
#> converged
#> This is Run number 207
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.79827061 -1.0301249 1.248271 -13.63012489 1
#> 2 1 -0.95 -2.35 -0.70996696 1.7787087 -1.659967 -0.57129125 2
#> 3 1 -6.20 -2.30 -0.69222404 0.1297352 -6.892224 -2.17026482 2
#> 4 1 -13.90 -2.55 1.28727624 2.4872409 -12.612724 -0.06275913 2
#> 5 1 -14.40 -5.80 -0.85938065 -0.8659836 -15.259381 -6.66598355 2
#> 6 1 -3.60 -1.70 0.09647942 -0.4644043 -3.503521 -2.16440430 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5460 -39225 7775
#> initial value 998.131940
#> iter 2 value 802.031969
#> iter 3 value 782.092187
#> iter 4 value 777.723227
#> iter 5 value 743.861703
#> iter 6 value 735.404082
#> iter 7 value 734.264279
#> iter 8 value 734.245285
#> iter 8 value 734.245277
#> final value 734.245277
#> converged
#> This is Run number 208
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.474340733 1.7911282 -0.07565927 -10.8088718 1
#> 2 1 -0.95 -2.35 -0.556423489 2.9628059 -1.50642349 0.6128059 2
#> 3 1 -6.20 -2.30 -1.296550267 0.3542291 -7.49655027 -1.9457709 2
#> 4 1 -13.90 -2.55 -0.832512501 0.1800411 -14.73251250 -2.3699589 2
#> 5 1 -14.40 -5.80 0.008062101 -0.1892226 -14.39193790 -5.9892226 2
#> 6 1 -3.60 -1.70 0.300677695 -0.3856469 -3.29932230 -2.0856469 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7160 -38275 5350
#> initial value 998.131940
#> iter 2 value 827.439670
#> iter 3 value 821.366945
#> iter 4 value 820.756337
#> iter 5 value 782.650249
#> iter 6 value 774.309125
#> iter 7 value 772.441022
#> iter 8 value 772.393038
#> iter 9 value 772.392877
#> iter 10 value 772.392863
#> iter 10 value 772.392863
#> iter 10 value 772.392859
#> final value 772.392859
#> converged
#> This is Run number 209
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.8225040 -0.1780247 0.272504 -12.7780247 1
#> 2 1 -0.95 -2.35 2.0999462 1.6790221 1.149946 -0.6709779 1
#> 3 1 -6.20 -2.30 1.2541799 3.1807898 -4.945820 0.8807898 2
#> 4 1 -13.90 -2.55 -1.1655911 0.1878590 -15.065591 -2.3621410 2
#> 5 1 -14.40 -5.80 -0.5826035 1.2253266 -14.982604 -4.5746734 2
#> 6 1 -3.60 -1.70 1.6363569 0.9918696 -1.963643 -0.7081304 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6080 -38725 7000
#> initial value 998.131940
#> iter 2 value 813.924157
#> iter 3 value 800.358844
#> iter 4 value 798.069634
#> iter 5 value 761.970917
#> iter 6 value 753.435851
#> iter 7 value 752.107717
#> iter 8 value 752.080088
#> iter 9 value 752.080048
#> iter 9 value 752.080038
#> iter 9 value 752.080032
#> final value 752.080032
#> converged
#> This is Run number 210
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.0804471 1.6148739 -1.6304471 -10.9851261 1
#> 2 1 -0.95 -2.35 1.7314486 0.4688926 0.7814486 -1.8811074 1
#> 3 1 -6.20 -2.30 1.5239115 0.2387191 -4.6760885 -2.0612809 2
#> 4 1 -13.90 -2.55 -0.5629955 1.8695882 -14.4629955 -0.6804118 2
#> 5 1 -14.40 -5.80 -0.1106001 -0.1239423 -14.5106001 -5.9239423 2
#> 6 1 -3.60 -1.70 0.8496519 -0.3173498 -2.7503481 -2.0173498 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6380 -38525 5900
#> initial value 998.131940
#> iter 2 value 822.255128
#> iter 3 value 812.118377
#> iter 4 value 809.853369
#> iter 5 value 773.052328
#> iter 6 value 764.541898
#> iter 7 value 762.948070
#> iter 8 value 762.909123
#> iter 9 value 762.909023
#> iter 10 value 762.909011
#> iter 10 value 762.909011
#> iter 10 value 762.909006
#> final value 762.909006
#> converged
#> This is Run number 211
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.7381860 2.3702811 -1.288186 -10.229719 1
#> 2 1 -0.95 -2.35 -1.0710475 -0.3180330 -2.021048 -2.668033 1
#> 3 1 -6.20 -2.30 -0.1021724 0.1380649 -6.302172 -2.161935 2
#> 4 1 -13.90 -2.55 3.2012258 1.2632025 -10.698774 -1.286798 2
#> 5 1 -14.40 -5.80 0.3240949 -0.5851632 -14.075905 -6.385163 2
#> 6 1 -3.60 -1.70 -0.6865354 -1.2800631 -4.286535 -2.980063 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5640 -38125 7800
#> initial value 998.131940
#> iter 2 value 817.997227
#> iter 3 value 802.145859
#> iter 4 value 799.752160
#> iter 5 value 762.038148
#> iter 6 value 753.679818
#> iter 7 value 752.452537
#> iter 8 value 752.431655
#> iter 9 value 752.431635
#> iter 9 value 752.431629
#> iter 9 value 752.431629
#> final value 752.431629
#> converged
#> This is Run number 212
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.5518995 0.7412249 -1.101900 -11.858775 1
#> 2 1 -0.95 -2.35 -1.2393277 -0.3694231 -2.189328 -2.719423 1
#> 3 1 -6.20 -2.30 2.7140459 0.6899771 -3.485954 -1.610023 2
#> 4 1 -13.90 -2.55 0.5622765 0.9551819 -13.337723 -1.594818 2
#> 5 1 -14.40 -5.80 -0.3327129 -0.1355594 -14.732713 -5.935559 2
#> 6 1 -3.60 -1.70 0.3038434 -1.2381983 -3.296157 -2.938198 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6480 -39400 5850
#> initial value 998.131940
#> iter 2 value 809.433833
#> iter 3 value 798.150084
#> iter 4 value 795.306960
#> iter 5 value 761.213008
#> iter 6 value 752.519260
#> iter 7 value 750.971687
#> iter 8 value 750.931472
#> iter 9 value 750.931362
#> iter 10 value 750.931350
#> iter 10 value 750.931349
#> iter 10 value 750.931343
#> final value 750.931343
#> converged
#> This is Run number 213
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.8397235 0.8683139 0.2897235 -11.7316861 1
#> 2 1 -0.95 -2.35 -0.5890346 0.9158195 -1.5390346 -1.4341805 2
#> 3 1 -6.20 -2.30 2.0217331 0.8086952 -4.1782669 -1.4913048 2
#> 4 1 -13.90 -2.55 -1.1671817 0.2152469 -15.0671817 -2.3347531 2
#> 5 1 -14.40 -5.80 0.6411148 0.3520927 -13.7588852 -5.4479073 2
#> 6 1 -3.60 -1.70 0.1473700 1.2898364 -3.4526300 -0.4101636 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5560 -35925 6275
#> initial value 998.131940
#> iter 2 value 855.875285
#> iter 3 value 846.557284
#> iter 4 value 844.541095
#> iter 5 value 800.651093
#> iter 6 value 792.889076
#> iter 7 value 791.466039
#> iter 8 value 791.439678
#> iter 9 value 791.439632
#> iter 9 value 791.439631
#> iter 9 value 791.439631
#> final value 791.439631
#> converged
#> This is Run number 214
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.5880903 1.72894066 0.03809032 -10.871059 1
#> 2 1 -0.95 -2.35 -1.3183744 0.02608701 -2.26837443 -2.323913 1
#> 3 1 -6.20 -2.30 -0.5867485 -0.76564477 -6.78674846 -3.065645 2
#> 4 1 -13.90 -2.55 2.5043098 0.68273099 -11.39569015 -1.867269 2
#> 5 1 -14.40 -5.80 3.0882450 -1.53274335 -11.31175496 -7.332743 2
#> 6 1 -3.60 -1.70 -1.2458252 -0.81017421 -4.84582520 -2.510174 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6380 -38750 7775
#> initial value 998.131940
#> iter 2 value 808.808801
#> iter 3 value 794.775476
#> iter 4 value 794.006426
#> iter 5 value 757.686181
#> iter 6 value 749.161460
#> iter 7 value 747.932226
#> iter 8 value 747.910021
#> iter 9 value 747.909995
#> iter 9 value 747.909988
#> iter 9 value 747.909986
#> final value 747.909986
#> converged
#> This is Run number 215
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.09169008 -0.1369218 -0.4583099 -12.7369218 1
#> 2 1 -0.95 -2.35 -0.09315536 -0.6526726 -1.0431554 -3.0026726 1
#> 3 1 -6.20 -2.30 -0.45936153 3.2561633 -6.6593615 0.9561633 2
#> 4 1 -13.90 -2.55 -0.26124703 -0.3651859 -14.1612470 -2.9151859 2
#> 5 1 -14.40 -5.80 1.02114270 1.0287486 -13.3788573 -4.7712514 2
#> 6 1 -3.60 -1.70 -0.30273714 0.8162572 -3.9027371 -0.8837428 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6000 -39350 7125
#> initial value 998.131940
#> iter 2 value 803.935733
#> iter 3 value 788.262130
#> iter 4 value 785.181803
#> iter 5 value 751.201637
#> iter 6 value 742.598680
#> iter 7 value 741.353379
#> iter 8 value 741.328242
#> iter 9 value 741.328214
#> iter 9 value 741.328206
#> iter 9 value 741.328201
#> final value 741.328201
#> converged
#> This is Run number 216
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.2066983 2.6146710 -0.7566983 -9.9853290 1
#> 2 1 -0.95 -2.35 0.3564629 1.9682892 -0.5935371 -0.3817108 2
#> 3 1 -6.20 -2.30 1.0512524 1.6769366 -5.1487476 -0.6230634 2
#> 4 1 -13.90 -2.55 2.0165478 0.8636186 -11.8834522 -1.6863814 2
#> 5 1 -14.40 -5.80 1.2738111 0.2055095 -13.1261889 -5.5944905 2
#> 6 1 -3.60 -1.70 -0.4822271 -0.4540221 -4.0822271 -2.1540221 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5720 -37900 7275
#> initial value 998.131940
#> iter 2 value 824.311550
#> iter 3 value 810.335267
#> iter 4 value 807.912021
#> iter 5 value 769.479035
#> iter 6 value 761.124843
#> iter 7 value 759.819415
#> iter 8 value 759.794711
#> iter 9 value 759.794680
#> iter 9 value 759.794670
#> iter 9 value 759.794665
#> final value 759.794665
#> converged
#> This is Run number 217
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.9269806 -0.4281532 0.3769806 -13.028153 1
#> 2 1 -0.95 -2.35 1.9402842 -0.3252042 0.9902842 -2.675204 1
#> 3 1 -6.20 -2.30 3.3392293 0.3297800 -2.8607707 -1.970220 2
#> 4 1 -13.90 -2.55 1.6926674 -0.6094662 -12.2073326 -3.159466 2
#> 5 1 -14.40 -5.80 3.9327639 -0.1386314 -10.4672361 -5.938631 2
#> 6 1 -3.60 -1.70 1.6349908 -1.3948699 -1.9650092 -3.094870 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5900 -39075 7025
#> initial value 998.131940
#> iter 2 value 808.666363
#> iter 3 value 793.236179
#> iter 4 value 789.971672
#> iter 5 value 755.191358
#> iter 6 value 746.609712
#> iter 7 value 745.335143
#> iter 8 value 745.309189
#> iter 9 value 745.309157
#> iter 9 value 745.309150
#> iter 9 value 745.309145
#> final value 745.309145
#> converged
#> This is Run number 218
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.16000160 -0.03526239 -1.710002 -12.63526239 1
#> 2 1 -0.95 -2.35 -0.89423071 -0.64229143 -1.844231 -2.99229143 1
#> 3 1 -6.20 -2.30 -1.17382981 0.14981155 -7.373830 -2.15018845 2
#> 4 1 -13.90 -2.55 0.22575472 -0.32449013 -13.674245 -2.87449013 2
#> 5 1 -14.40 -5.80 -0.03684955 0.32234712 -14.436850 -5.47765288 2
#> 6 1 -3.60 -1.70 0.28921266 1.60723484 -3.310787 -0.09276516 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5920 -38300 7725
#> initial value 998.131940
#> iter 2 value 815.900592
#> iter 3 value 801.140831
#> iter 4 value 799.430577
#> iter 5 value 762.025225
#> iter 6 value 753.610059
#> iter 7 value 752.369440
#> iter 8 value 752.347448
#> iter 9 value 752.347424
#> iter 9 value 752.347416
#> iter 9 value 752.347410
#> final value 752.347410
#> converged
#> This is Run number 219
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.91658657 3.91101543 -1.4665866 -8.688985 1
#> 2 1 -0.95 -2.35 0.08912086 0.07344246 -0.8608791 -2.276558 1
#> 3 1 -6.20 -2.30 1.74606889 0.59702546 -4.4539311 -1.702975 2
#> 4 1 -13.90 -2.55 2.04921261 0.42832508 -11.8507874 -2.121675 2
#> 5 1 -14.40 -5.80 1.52153305 -0.40264686 -12.8784670 -6.202647 2
#> 6 1 -3.60 -1.70 0.54033159 -0.86860529 -3.0596684 -2.568605 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6420 -38650 6850
#> initial value 998.131940
#> iter 2 value 815.638568
#> iter 3 value 804.051855
#> iter 4 value 802.712554
#> iter 5 value 766.072786
#> iter 6 value 757.535318
#> iter 7 value 756.138987
#> iter 8 value 756.108346
#> iter 9 value 756.108292
#> iter 10 value 756.108279
#> iter 10 value 756.108270
#> iter 10 value 756.108268
#> final value 756.108268
#> converged
#> This is Run number 220
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.0654828 0.6547639 -1.6154828 -11.94523608 1
#> 2 1 -0.95 -2.35 0.3993259 0.3562450 -0.5506741 -1.99375501 1
#> 3 1 -6.20 -2.30 2.7682318 1.1207055 -3.4317682 -1.17929447 2
#> 4 1 -13.90 -2.55 1.0575306 1.3948554 -12.8424694 -1.15514458 2
#> 5 1 -14.40 -5.80 2.4069026 0.2330548 -11.9930974 -5.56694521 2
#> 6 1 -3.60 -1.70 -1.1249150 1.7991393 -4.7249150 0.09913926 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5820 -37775 7350
#> initial value 998.131940
#> iter 2 value 825.601490
#> iter 3 value 812.297340
#> iter 4 value 810.377079
#> iter 5 value 771.446108
#> iter 6 value 763.119233
#> iter 7 value 761.810783
#> iter 8 value 761.786157
#> iter 9 value 761.786125
#> iter 9 value 761.786114
#> iter 9 value 761.786108
#> final value 761.786108
#> converged
#> This is Run number 221
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.9000783 -0.004409697 0.3500783 -12.604410 1
#> 2 1 -0.95 -2.35 -0.4800878 0.563000045 -1.4300878 -1.787000 1
#> 3 1 -6.20 -2.30 0.4041835 0.605752274 -5.7958165 -1.694248 2
#> 4 1 -13.90 -2.55 -0.7918820 0.761345481 -14.6918820 -1.788655 2
#> 5 1 -14.40 -5.80 0.8632203 0.200058745 -13.5367797 -5.599941 2
#> 6 1 -3.60 -1.70 0.8651042 0.042409954 -2.7348958 -1.657590 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6580 -39000 7225
#> initial value 998.131940
#> iter 2 value 808.253020
#> iter 3 value 795.813338
#> iter 4 value 794.951389
#> iter 5 value 759.274754
#> iter 6 value 750.677054
#> iter 7 value 749.358660
#> iter 8 value 749.331012
#> iter 9 value 749.330969
#> iter 10 value 749.330956
#> iter 10 value 749.330946
#> iter 10 value 749.330939
#> final value 749.330939
#> converged
#> This is Run number 222
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.5974888 0.7207872 -1.147489 -11.8792128 1
#> 2 1 -0.95 -2.35 2.4177932 1.2107015 1.467793 -1.1392985 1
#> 3 1 -6.20 -2.30 -0.9147225 0.8125029 -7.114723 -1.4874971 2
#> 4 1 -13.90 -2.55 0.9994110 2.1232375 -12.900589 -0.4267625 2
#> 5 1 -14.40 -5.80 -1.0913688 4.5534294 -15.491369 -1.2465706 2
#> 6 1 -3.60 -1.70 -0.0112052 -0.3993452 -3.611205 -2.0993452 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6680 -38075 7100
#> initial value 998.131940
#> iter 2 value 822.261078
#> iter 3 value 811.942835
#> iter 4 value 811.632289
#> iter 5 value 773.078012
#> iter 6 value 764.644017
#> iter 7 value 763.231041
#> iter 8 value 763.200911
#> iter 9 value 763.200851
#> iter 10 value 763.200835
#> iter 10 value 763.200825
#> iter 10 value 763.200818
#> final value 763.200818
#> converged
#> This is Run number 223
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.8476100 1.3207487 1.297610 -11.279251334 1
#> 2 1 -0.95 -2.35 -0.8531956 2.3562997 -1.803196 0.006299748 2
#> 3 1 -6.20 -2.30 1.3090482 -1.4392946 -4.890952 -3.739294611 2
#> 4 1 -13.90 -2.55 0.7109863 1.2417223 -13.189014 -1.308277719 2
#> 5 1 -14.40 -5.80 2.1710187 0.4505619 -12.228981 -5.349438056 2
#> 6 1 -3.60 -1.70 -1.3060764 -0.1635694 -4.906076 -1.863569387 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6280 -37325 6150
#> initial value 998.131940
#> iter 2 value 837.964233
#> iter 3 value 829.286267
#> iter 4 value 827.941315
#> iter 5 value 787.517484
#> iter 6 value 779.333333
#> iter 7 value 777.774281
#> iter 8 value 777.740246
#> iter 9 value 777.740170
#> iter 9 value 777.740170
#> iter 9 value 777.740170
#> final value 777.740170
#> converged
#> This is Run number 224
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.1452453 0.13098693 -1.6952453 -12.4690131 1
#> 2 1 -0.95 -2.35 0.3876162 0.77493437 -0.5623838 -1.5750656 1
#> 3 1 -6.20 -2.30 1.6711713 0.74241078 -4.5288287 -1.5575892 2
#> 4 1 -13.90 -2.55 -0.7816148 1.76706709 -14.6816148 -0.7829329 2
#> 5 1 -14.40 -5.80 0.4505547 -0.46879084 -13.9494453 -6.2687908 2
#> 6 1 -3.60 -1.70 0.3612035 0.07746109 -3.2387965 -1.6225389 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5960 -36850 6500
#> initial value 998.131940
#> iter 2 value 842.752952
#> iter 3 value 833.218933
#> iter 4 value 831.692715
#> iter 5 value 790.047163
#> iter 6 value 781.982992
#> iter 7 value 780.525025
#> iter 8 value 780.495636
#> iter 9 value 780.495581
#> iter 9 value 780.495578
#> iter 9 value 780.495578
#> final value 780.495578
#> converged
#> This is Run number 225
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.5534737 0.51978165 -1.103474 -12.080218 1
#> 2 1 -0.95 -2.35 2.2873416 0.72168668 1.337342 -1.628313 1
#> 3 1 -6.20 -2.30 2.7367478 0.46097836 -3.463252 -1.839022 2
#> 4 1 -13.90 -2.55 2.6558252 -0.38613520 -11.244175 -2.936135 2
#> 5 1 -14.40 -5.80 3.9567387 -0.21961638 -10.443261 -6.019616 2
#> 6 1 -3.60 -1.70 2.2565819 -0.01522072 -1.343418 -1.715221 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6240 -38975 8025
#> initial value 998.131940
#> iter 2 value 804.001710
#> iter 3 value 788.334758
#> iter 4 value 787.279503
#> iter 5 value 751.775799
#> iter 6 value 743.269799
#> iter 7 value 742.099602
#> iter 8 value 742.080249
#> iter 9 value 742.080228
#> iter 9 value 742.080220
#> iter 9 value 742.080216
#> final value 742.080216
#> converged
#> This is Run number 226
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.7441052 0.2947034 1.194105 -12.30529658 1
#> 2 1 -0.95 -2.35 -0.7036946 -1.5217352 -1.653695 -3.87173525 1
#> 3 1 -6.20 -2.30 0.6120319 1.3815294 -5.587968 -0.91847058 2
#> 4 1 -13.90 -2.55 0.9700783 2.5828218 -12.929922 0.03282182 2
#> 5 1 -14.40 -5.80 0.2687309 2.1144806 -14.131269 -3.68551941 2
#> 6 1 -3.60 -1.70 -1.2389821 0.4902838 -4.838982 -1.20971616 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7160 -38425 5725
#> initial value 998.131940
#> iter 2 value 823.668463
#> iter 3 value 816.850808
#> iter 4 value 816.408532
#> iter 5 value 778.669920
#> iter 6 value 770.251297
#> iter 7 value 768.484599
#> iter 8 value 768.439764
#> iter 9 value 768.439627
#> iter 10 value 768.439613
#> iter 10 value 768.439609
#> iter 10 value 768.439606
#> final value 768.439606
#> converged
#> This is Run number 227
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 3.4441583 2.6284613 2.894158 -9.9715387 1
#> 2 1 -0.95 -2.35 -1.0597370 0.4807928 -2.009737 -1.8692072 2
#> 3 1 -6.20 -2.30 0.2773811 2.1961445 -5.922619 -0.1038555 2
#> 4 1 -13.90 -2.55 -0.8482658 1.0370210 -14.748266 -1.5129790 2
#> 5 1 -14.40 -5.80 0.1758028 -0.3642346 -14.224197 -6.1642346 2
#> 6 1 -3.60 -1.70 1.4461426 0.4603274 -2.153857 -1.2396726 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6220 -36625 5775
#> initial value 998.131940
#> iter 2 value 849.049071
#> iter 3 value 841.696413
#> iter 4 value 840.394412
#> iter 5 value 798.144243
#> iter 6 value 790.213110
#> iter 7 value 788.605465
#> iter 8 value 788.571698
#> iter 9 value 788.571618
#> iter 9 value 788.571608
#> iter 9 value 788.571604
#> final value 788.571604
#> converged
#> This is Run number 228
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.0447475 -0.40380582 -0.5052525 -13.0038058 1
#> 2 1 -0.95 -2.35 3.5619603 1.67717616 2.6119603 -0.6728238 1
#> 3 1 -6.20 -2.30 0.7238402 3.03673666 -5.4761598 0.7367367 2
#> 4 1 -13.90 -2.55 0.7806459 -0.08152807 -13.1193541 -2.6315281 2
#> 5 1 -14.40 -5.80 0.9494378 1.00268280 -13.4505622 -4.7973172 2
#> 6 1 -3.60 -1.70 -0.5529688 0.98569664 -4.1529688 -0.7143034 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5500 -36900 7075
#> initial value 998.131940
#> iter 2 value 839.113520
#> iter 3 value 826.637404
#> iter 4 value 824.257472
#> iter 5 value 782.968090
#> iter 6 value 774.862478
#> iter 7 value 773.525022
#> iter 8 value 773.500427
#> iter 9 value 773.500393
#> iter 9 value 773.500383
#> iter 9 value 773.500378
#> final value 773.500378
#> converged
#> This is Run number 229
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.9852670 2.5355131 1.4352670 -10.0644869 1
#> 2 1 -0.95 -2.35 1.1320253 1.9968171 0.1820253 -0.3531829 1
#> 3 1 -6.20 -2.30 -0.6673611 -1.0597203 -6.8673611 -3.3597203 2
#> 4 1 -13.90 -2.55 1.0495013 1.3418826 -12.8504987 -1.2081174 2
#> 5 1 -14.40 -5.80 -0.8831389 0.1121219 -15.2831389 -5.6878781 2
#> 6 1 -3.60 -1.70 1.0609421 2.1497227 -2.5390579 0.4497227 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6120 -37525 7850
#> initial value 998.131940
#> iter 2 value 825.892580
#> iter 3 value 813.272609
#> iter 4 value 812.660445
#> iter 5 value 772.686939
#> iter 6 value 764.388726
#> iter 7 value 763.125869
#> iter 8 value 763.104057
#> iter 9 value 763.104028
#> iter 9 value 763.104020
#> iter 9 value 763.104012
#> final value 763.104012
#> converged
#> This is Run number 230
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.03255199 2.7785120 -0.517448 -9.8214880 1
#> 2 1 -0.95 -2.35 2.77938134 1.2514665 1.829381 -1.0985335 1
#> 3 1 -6.20 -2.30 -0.21063749 -0.5963459 -6.410637 -2.8963459 2
#> 4 1 -13.90 -2.55 1.91723859 3.5261275 -11.982761 0.9761275 2
#> 5 1 -14.40 -5.80 0.72171373 0.8986288 -13.678286 -4.9013712 2
#> 6 1 -3.60 -1.70 0.61462267 0.4009530 -2.985377 -1.2990470 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5860 -38025 8150
#> initial value 998.131940
#> iter 2 value 817.132946
#> iter 3 value 801.813499
#> iter 4 value 800.504616
#> iter 5 value 762.214966
#> iter 6 value 753.869159
#> iter 7 value 752.672882
#> iter 8 value 752.654045
#> iter 9 value 752.654027
#> iter 9 value 752.654020
#> iter 9 value 752.654016
#> final value 752.654016
#> converged
#> This is Run number 231
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.73531656 -1.530465749 -1.285317 -14.1304657 1
#> 2 1 -0.95 -2.35 -0.48852775 2.150363214 -1.438528 -0.1996368 2
#> 3 1 -6.20 -2.30 0.10929049 -0.962438246 -6.090710 -3.2624382 2
#> 4 1 -13.90 -2.55 0.11701363 -1.239015260 -13.782986 -3.7890153 2
#> 5 1 -14.40 -5.80 -0.35429037 0.002149594 -14.754290 -5.7978504 2
#> 6 1 -3.60 -1.70 -0.05224961 2.132736925 -3.652250 0.4327369 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6480 -39450 7575
#> initial value 998.131940
#> iter 2 value 799.503982
#> iter 3 value 784.965112
#> iter 4 value 783.844908
#> iter 5 value 749.690918
#> iter 6 value 741.080205
#> iter 7 value 739.869311
#> iter 8 value 739.846278
#> iter 9 value 739.846252
#> iter 9 value 739.846244
#> iter 9 value 739.846243
#> final value 739.846243
#> converged
#> This is Run number 232
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.8773840 -0.03556040 -1.4273840 -12.6355604 1
#> 2 1 -0.95 -2.35 1.5218759 3.73471566 0.5718759 1.3847157 2
#> 3 1 -6.20 -2.30 -0.7278281 -0.01909818 -6.9278281 -2.3190982 2
#> 4 1 -13.90 -2.55 1.0088512 0.66409343 -12.8911488 -1.8859066 2
#> 5 1 -14.40 -5.80 3.3750571 0.66021795 -11.0249429 -5.1397820 2
#> 6 1 -3.60 -1.70 0.3978376 1.34839978 -3.2021624 -0.3516002 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6260 -38800 6175
#> initial value 998.131940
#> iter 2 value 817.016408
#> iter 3 value 805.408360
#> iter 4 value 802.782092
#> iter 5 value 766.891990
#> iter 6 value 758.309422
#> iter 7 value 756.814807
#> iter 8 value 756.779226
#> iter 9 value 756.779148
#> iter 9 value 756.779137
#> iter 9 value 756.779131
#> final value 756.779131
#> converged
#> This is Run number 233
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.48119914 0.7116074 -1.031199 -11.8883926 1
#> 2 1 -0.95 -2.35 -0.44626121 0.1265621 -1.396261 -2.2234379 1
#> 3 1 -6.20 -2.30 0.08820424 0.6102511 -6.111796 -1.6897489 2
#> 4 1 -13.90 -2.55 0.58974194 -1.2617690 -13.310258 -3.8117690 2
#> 5 1 -14.40 -5.80 -0.15078747 4.0017594 -14.550787 -1.7982406 2
#> 6 1 -3.60 -1.70 2.03602961 1.5876173 -1.563970 -0.1123827 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6360 -39025 6975
#> initial value 998.131940
#> iter 2 value 809.472073
#> iter 3 value 796.658382
#> iter 4 value 794.968249
#> iter 5 value 759.567558
#> iter 6 value 750.973226
#> iter 7 value 749.635459
#> iter 8 value 749.606661
#> iter 9 value 749.606616
#> iter 10 value 749.606605
#> iter 10 value 749.606597
#> iter 10 value 749.606591
#> final value 749.606591
#> converged
#> This is Run number 234
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.20312965 -0.4369401 -0.7531296 -13.036940 1
#> 2 1 -0.95 -2.35 1.58038645 -0.5655113 0.6303864 -2.915511 1
#> 3 1 -6.20 -2.30 0.68258610 -0.3409222 -5.5174139 -2.640922 2
#> 4 1 -13.90 -2.55 1.08750589 -0.4550891 -12.8124941 -3.005089 2
#> 5 1 -14.40 -5.80 -0.09852209 -1.1345732 -14.4985221 -6.934573 2
#> 6 1 -3.60 -1.70 -0.64938331 -1.0224924 -4.2493833 -2.722492 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6620 -40700 6375
#> initial value 998.131940
#> iter 2 value 786.396879
#> iter 3 value 772.502015
#> iter 4 value 769.353571
#> iter 5 value 739.332176
#> iter 6 value 730.547941
#> iter 7 value 729.276095
#> iter 8 value 729.245000
#> iter 9 value 729.244945
#> iter 9 value 729.244939
#> iter 9 value 729.244933
#> final value 729.244933
#> converged
#> This is Run number 235
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.80982266 1.4263786 -1.3598227 -11.173621 1
#> 2 1 -0.95 -2.35 1.27694536 0.9225383 0.3269454 -1.427462 1
#> 3 1 -6.20 -2.30 2.98622402 -0.3988181 -3.2137760 -2.698818 2
#> 4 1 -13.90 -2.55 -0.36101653 0.3252803 -14.2610165 -2.224720 2
#> 5 1 -14.40 -5.80 -0.07688913 0.3382052 -14.4768891 -5.461795 2
#> 6 1 -3.60 -1.70 -0.33120811 0.2577318 -3.9312081 -1.442268 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5980 -38925 7200
#> initial value 998.131940
#> iter 2 value 809.888783
#> iter 3 value 794.990142
#> iter 4 value 792.372727
#> iter 5 value 757.001830
#> iter 6 value 748.455523
#> iter 7 value 747.182970
#> iter 8 value 747.157635
#> iter 9 value 747.157605
#> iter 9 value 747.157596
#> iter 9 value 747.157591
#> final value 747.157591
#> converged
#> This is Run number 236
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.7965914 -0.04870332 1.246591 -12.6487033 1
#> 2 1 -0.95 -2.35 -0.3530705 -0.35677258 -1.303071 -2.7067726 1
#> 3 1 -6.20 -2.30 0.6195920 -0.69061997 -5.580408 -2.9906200 2
#> 4 1 -13.90 -2.55 0.6252621 1.19040595 -13.274738 -1.3595940 2
#> 5 1 -14.40 -5.80 0.5936413 -0.27481174 -13.806359 -6.0748117 2
#> 6 1 -3.60 -1.70 -0.5563107 2.55929414 -4.156311 0.8592941 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5900 -38250 7375
#> initial value 998.131940
#> iter 2 value 818.729364
#> iter 3 value 804.677775
#> iter 4 value 802.616641
#> iter 5 value 765.113626
#> iter 6 value 756.689200
#> iter 7 value 755.400449
#> iter 8 value 755.375906
#> iter 9 value 755.375875
#> iter 9 value 755.375865
#> iter 9 value 755.375859
#> final value 755.375859
#> converged
#> This is Run number 237
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.00448599 0.5773295 -1.554486 -12.02267052 1
#> 2 1 -0.95 -2.35 -1.05295748 2.4025245 -2.002957 0.05252447 2
#> 3 1 -6.20 -2.30 -0.17379317 4.6904100 -6.373793 2.39041002 2
#> 4 1 -13.90 -2.55 0.08746244 -0.7566977 -13.812538 -3.30669772 2
#> 5 1 -14.40 -5.80 0.30851843 1.6665333 -14.091482 -4.13346667 2
#> 6 1 -3.60 -1.70 0.53126972 0.2393648 -3.068730 -1.46063515 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6240 -39125 7100
#> initial value 998.131940
#> iter 2 value 807.356921
#> iter 3 value 793.531199
#> iter 4 value 791.502450
#> iter 5 value 756.531381
#> iter 6 value 747.937458
#> iter 7 value 746.641842
#> iter 8 value 746.614866
#> iter 9 value 746.614830
#> iter 9 value 746.614820
#> iter 9 value 746.614814
#> final value 746.614814
#> converged
#> This is Run number 238
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.8405225 1.2268711 0.2905225 -11.3731289 1
#> 2 1 -0.95 -2.35 -0.1030576 0.2193215 -1.0530576 -2.1306785 1
#> 3 1 -6.20 -2.30 0.6144532 1.3732119 -5.5855468 -0.9267881 2
#> 4 1 -13.90 -2.55 -0.2888606 -0.9605566 -14.1888606 -3.5105566 2
#> 5 1 -14.40 -5.80 0.2597323 2.3425253 -14.1402677 -3.4574747 2
#> 6 1 -3.60 -1.70 -0.6243951 0.1923333 -4.2243951 -1.5076667 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6260 -38050 6900
#> initial value 998.131940
#> iter 2 value 824.087932
#> iter 3 value 812.903341
#> iter 4 value 811.618463
#> iter 5 value 773.234850
#> iter 6 value 764.827717
#> iter 7 value 763.423150
#> iter 8 value 763.393480
#> iter 9 value 763.393428
#> iter 10 value 763.393414
#> iter 10 value 763.393404
#> iter 10 value 763.393400
#> final value 763.393400
#> converged
#> This is Run number 239
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 3.1772484 0.2126690 2.6272484 -12.387331 1
#> 2 1 -0.95 -2.35 0.0816046 0.2679445 -0.8683954 -2.082055 1
#> 3 1 -6.20 -2.30 -0.2190574 0.3126964 -6.4190574 -1.987304 2
#> 4 1 -13.90 -2.55 0.9748933 1.1207130 -12.9251067 -1.429287 2
#> 5 1 -14.40 -5.80 2.5001654 0.1922016 -11.8998346 -5.607798 2
#> 6 1 -3.60 -1.70 0.2016867 -0.2987466 -3.3983133 -1.998747 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6560 -39400 6925
#> initial value 998.131940
#> iter 2 value 803.957698
#> iter 3 value 791.377019
#> iter 4 value 789.925105
#> iter 5 value 755.555420
#> iter 6 value 746.898259
#> iter 7 value 745.564684
#> iter 8 value 745.535133
#> iter 9 value 745.535085
#> iter 10 value 745.535074
#> iter 10 value 745.535065
#> iter 10 value 745.535060
#> final value 745.535060
#> converged
#> This is Run number 240
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 5.0093042 1.02414952 4.459304 -11.57585048 1
#> 2 1 -0.95 -2.35 3.3717477 0.58398147 2.421748 -1.76601853 1
#> 3 1 -6.20 -2.30 -0.5433670 2.35125957 -6.743367 0.05125957 2
#> 4 1 -13.90 -2.55 0.4631510 0.70165006 -13.436849 -1.84834994 2
#> 5 1 -14.40 -5.80 0.4880912 0.03061548 -13.911909 -5.76938452 2
#> 6 1 -3.60 -1.70 1.9404469 0.27519715 -1.659553 -1.42480285 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6700 -38775 7350
#> initial value 998.131940
#> iter 2 value 810.726593
#> iter 3 value 798.730358
#> iter 4 value 798.302582
#> iter 5 value 761.871486
#> iter 6 value 753.298017
#> iter 7 value 751.974126
#> iter 8 value 751.946825
#> iter 9 value 751.946781
#> iter 10 value 751.946766
#> iter 10 value 751.946757
#> iter 10 value 751.946749
#> final value 751.946749
#> converged
#> This is Run number 241
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.31016368 0.8647829 -0.8601637 -11.7352171 1
#> 2 1 -0.95 -2.35 1.11268413 3.9797480 0.1626841 1.6297480 2
#> 3 1 -6.20 -2.30 0.35103620 0.9718929 -5.8489638 -1.3281071 2
#> 4 1 -13.90 -2.55 -0.52632554 -0.3870442 -14.4263255 -2.9370442 2
#> 5 1 -14.40 -5.80 -0.01124584 -0.2165955 -14.4112458 -6.0165955 2
#> 6 1 -3.60 -1.70 -0.87348806 1.3790042 -4.4734881 -0.3209958 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6720 -40375 6750
#> initial value 998.131940
#> iter 2 value 789.591202
#> iter 3 value 776.204988
#> iter 4 value 774.224881
#> iter 5 value 742.933012
#> iter 6 value 734.183495
#> iter 7 value 732.917333
#> iter 8 value 732.888181
#> iter 9 value 732.888137
#> iter 9 value 732.888137
#> iter 9 value 732.888137
#> final value 732.888137
#> converged
#> This is Run number 242
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.6494390 1.54342819 0.09943900 -11.0565718 1
#> 2 1 -0.95 -2.35 1.0192253 0.08960209 0.06922532 -2.2603979 1
#> 3 1 -6.20 -2.30 -0.3140770 2.96674827 -6.51407703 0.6667483 2
#> 4 1 -13.90 -2.55 -0.3208263 2.28910240 -14.22082633 -0.2608976 2
#> 5 1 -14.40 -5.80 1.5841395 -0.17950177 -12.81586051 -5.9795018 2
#> 6 1 -3.60 -1.70 0.5659185 -0.62849461 -3.03408154 -2.3284946 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6840 -37400 6400
#> initial value 998.131940
#> iter 2 value 835.178170
#> iter 3 value 827.635495
#> iter 4 value 827.446241
#> iter 5 value 786.873888
#> iter 6 value 778.675208
#> iter 7 value 777.085423
#> iter 8 value 777.049741
#> iter 9 value 777.049650
#> iter 10 value 777.049634
#> iter 10 value 777.049625
#> iter 10 value 777.049616
#> final value 777.049616
#> converged
#> This is Run number 243
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.4805062 3.0838861 1.93050618 -9.516114 1
#> 2 1 -0.95 -2.35 1.0495383 -0.1520628 0.09953833 -2.502063 1
#> 3 1 -6.20 -2.30 1.9789513 -0.7203178 -4.22104871 -3.020318 2
#> 4 1 -13.90 -2.55 0.8635060 0.1326368 -13.03649397 -2.417363 2
#> 5 1 -14.40 -5.80 0.2057064 2.3673315 -14.19429357 -3.432668 2
#> 6 1 -3.60 -1.70 0.3295832 -0.4042369 -3.27041683 -2.104237 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6400 -38850 6225
#> initial value 998.131940
#> iter 2 value 815.947555
#> iter 3 value 804.900656
#> iter 4 value 802.724024
#> iter 5 value 766.852562
#> iter 6 value 758.269569
#> iter 7 value 756.768084
#> iter 8 value 756.732173
#> iter 9 value 756.732095
#> iter 9 value 756.732084
#> iter 9 value 756.732078
#> final value 756.732078
#> converged
#> This is Run number 244
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.655043227 1.22161720 0.1050432 -11.3783828 1
#> 2 1 -0.95 -2.35 -0.002454318 -0.24362416 -0.9524543 -2.5936242 1
#> 3 1 -6.20 -2.30 -1.006912432 -0.09113768 -7.2069124 -2.3911377 2
#> 4 1 -13.90 -2.55 -0.549814037 3.38010125 -14.4498140 0.8301013 2
#> 5 1 -14.40 -5.80 1.731383699 1.19105735 -12.6686163 -4.6089427 2
#> 6 1 -3.60 -1.70 -0.477807517 1.59538957 -4.0778075 -0.1046104 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6120 -38175 7600
#> initial value 998.131940
#> iter 2 value 818.360246
#> iter 3 value 804.983630
#> iter 4 value 803.822680
#> iter 5 value 765.866144
#> iter 6 value 757.446109
#> iter 7 value 756.170251
#> iter 8 value 756.146611
#> iter 9 value 756.146580
#> iter 9 value 756.146569
#> iter 9 value 756.146563
#> final value 756.146563
#> converged
#> This is Run number 245
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.8445037 0.4627549 2.294504 -12.1372451 1
#> 2 1 -0.95 -2.35 -0.1232785 0.0791009 -1.073279 -2.2708991 1
#> 3 1 -6.20 -2.30 0.5272793 -1.0085839 -5.672721 -3.3085839 2
#> 4 1 -13.90 -2.55 1.9527666 -0.9632221 -11.947233 -3.5132221 2
#> 5 1 -14.40 -5.80 0.9935716 2.0774481 -13.406428 -3.7225519 2
#> 6 1 -3.60 -1.70 1.8113113 1.1359141 -1.788689 -0.5640859 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5860 -36750 6000
#> initial value 998.131940
#> iter 2 value 846.554042
#> iter 3 value 837.205108
#> iter 4 value 835.097604
#> iter 5 value 793.376229
#> iter 6 value 785.348486
#> iter 7 value 783.819987
#> iter 8 value 783.788448
#> iter 9 value 783.788381
#> iter 9 value 783.788372
#> iter 9 value 783.788368
#> final value 783.788368
#> converged
#> This is Run number 246
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.1947171 1.2179700 1.6447171 -11.3820300 1
#> 2 1 -0.95 -2.35 1.2186088 1.7841259 0.2686088 -0.5658741 1
#> 3 1 -6.20 -2.30 1.4122247 0.9045920 -4.7877753 -1.3954080 2
#> 4 1 -13.90 -2.55 0.1791404 -0.5492948 -13.7208596 -3.0992948 2
#> 5 1 -14.40 -5.80 1.6302392 1.9455393 -12.7697608 -3.8544607 2
#> 6 1 -3.60 -1.70 -0.9766555 0.2611104 -4.5766555 -1.4388896 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6680 -38300 6525
#> initial value 998.131940
#> iter 2 value 822.181386
#> iter 3 value 812.747373
#> iter 4 value 811.998231
#> iter 5 value 774.108233
#> iter 6 value 765.647492
#> iter 7 value 764.133339
#> iter 8 value 764.098441
#> iter 9 value 764.098363
#> iter 10 value 764.098348
#> iter 10 value 764.098338
#> iter 10 value 764.098333
#> final value 764.098333
#> converged
#> This is Run number 247
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.2088165 0.5931075 0.6588165 -12.006892 1
#> 2 1 -0.95 -2.35 0.4808139 -1.0211328 -0.4691861 -3.371133 1
#> 3 1 -6.20 -2.30 3.5088141 0.4158355 -2.6911859 -1.884164 2
#> 4 1 -13.90 -2.55 0.8408609 -0.0235867 -13.0591391 -2.573587 2
#> 5 1 -14.40 -5.80 -0.5046380 -0.7710901 -14.9046380 -6.571090 2
#> 6 1 -3.60 -1.70 2.1141948 -0.7719867 -1.4858052 -2.471987 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6180 -38200 6125
#> initial value 998.131940
#> iter 2 value 825.987177
#> iter 3 value 815.241085
#> iter 4 value 812.885430
#> iter 5 value 775.191752
#> iter 6 value 766.746118
#> iter 7 value 765.214787
#> iter 8 value 765.179433
#> iter 9 value 765.179354
#> iter 9 value 765.179343
#> iter 9 value 765.179338
#> final value 765.179338
#> converged
#> This is Run number 248
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.02810859 -0.61540022 -0.5218914 -13.2154002 1
#> 2 1 -0.95 -2.35 -1.27613975 0.54502206 -2.2261397 -1.8049779 2
#> 3 1 -6.20 -2.30 0.14504544 0.40146568 -6.0549546 -1.8985343 2
#> 4 1 -13.90 -2.55 2.08761878 0.05451075 -11.8123812 -2.4954893 2
#> 5 1 -14.40 -5.80 1.33323333 0.58618945 -13.0667667 -5.2138106 2
#> 6 1 -3.60 -1.70 0.42835266 2.52480226 -3.1716473 0.8248023 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6680 -40875 6800
#> initial value 998.131940
#> iter 2 value 781.280346
#> iter 3 value 766.563653
#> iter 4 value 763.997399
#> iter 5 value 734.433159
#> iter 6 value 725.700456
#> iter 7 value 724.523136
#> iter 8 value 724.496845
#> iter 9 value 724.496813
#> iter 9 value 724.496812
#> iter 9 value 724.496812
#> final value 724.496812
#> converged
#> This is Run number 249
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.6333742 -0.7362471 -2.1833742 -13.3362471 1
#> 2 1 -0.95 -2.35 -0.7205674 0.5910431 -1.6705674 -1.7589569 1
#> 3 1 -6.20 -2.30 0.4194497 3.6669410 -5.7805503 1.3669410 2
#> 4 1 -13.90 -2.55 0.8342635 2.3644905 -13.0657365 -0.1855095 2
#> 5 1 -14.40 -5.80 -0.4914265 0.7035326 -14.8914265 -5.0964674 2
#> 6 1 -3.60 -1.70 4.4156025 1.8720871 0.8156025 0.1720871 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6200 -36725 6500
#> initial value 998.131940
#> iter 2 value 844.266208
#> iter 3 value 835.862053
#> iter 4 value 834.980809
#> iter 5 value 792.810447
#> iter 6 value 784.796024
#> iter 7 value 783.312871
#> iter 8 value 783.282686
#> iter 9 value 783.282623
#> iter 9 value 783.282619
#> iter 9 value 783.282619
#> final value 783.282619
#> converged
#> This is Run number 250
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.7381788 1.5872388 1.188179 -11.0127612 1
#> 2 1 -0.95 -2.35 -0.7568609 2.6698661 -1.706861 0.3198661 2
#> 3 1 -6.20 -2.30 2.1164821 0.8411596 -4.083518 -1.4588404 2
#> 4 1 -13.90 -2.55 0.3853132 1.0538036 -13.514687 -1.4961964 2
#> 5 1 -14.40 -5.80 0.5614486 -0.2464262 -13.838551 -6.0464262 2
#> 6 1 -3.60 -1.70 -0.2661704 0.8739728 -3.866170 -0.8260272 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5760 -36625 6350
#> initial value 998.131940
#> iter 2 value 846.527470
#> iter 3 value 836.680841
#> iter 4 value 834.681412
#> iter 5 value 792.580035
#> iter 6 value 784.580769
#> iter 7 value 783.124309
#> iter 8 value 783.095515
#> iter 9 value 783.095462
#> iter 9 value 783.095461
#> iter 9 value 783.095461
#> final value 783.095461
#> converged
#> This is Run number 251
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.1561369 0.7081376 -1.7061369 -11.8918624 1
#> 2 1 -0.95 -2.35 1.4298268 5.7933276 0.4798268 3.4433276 2
#> 3 1 -6.20 -2.30 2.3851884 -0.8059106 -3.8148116 -3.1059106 2
#> 4 1 -13.90 -2.55 -0.8106951 1.2064598 -14.7106951 -1.3435402 2
#> 5 1 -14.40 -5.80 -0.8619319 1.3703933 -15.2619319 -4.4296067 2
#> 6 1 -3.60 -1.70 0.4952075 2.3965973 -3.1047925 0.6965973 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6140 -38150 6675
#> initial value 998.131940
#> iter 2 value 823.951017
#> iter 3 value 812.417941
#> iter 4 value 810.512955
#> iter 5 value 772.582669
#> iter 6 value 764.152880
#> iter 7 value 762.728128
#> iter 8 value 762.697398
#> iter 9 value 762.697342
#> iter 9 value 762.697342
#> iter 9 value 762.697342
#> final value 762.697342
#> converged
#> This is Run number 252
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.5596742 0.55386934 2.009674 -12.0461307 1
#> 2 1 -0.95 -2.35 -0.2015699 2.93604776 -1.151570 0.5860478 2
#> 3 1 -6.20 -2.30 -0.1707201 -0.07179202 -6.370720 -2.3717920 2
#> 4 1 -13.90 -2.55 -0.1397897 0.04092373 -14.039790 -2.5090763 2
#> 5 1 -14.40 -5.80 -0.3211993 2.73792648 -14.721199 -3.0620735 2
#> 6 1 -3.60 -1.70 0.3891829 1.58555717 -3.210817 -0.1144428 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6180 -39125 6675
#> initial value 998.131940
#> iter 2 value 809.707936
#> iter 3 value 796.307177
#> iter 4 value 793.614386
#> iter 5 value 758.761945
#> iter 6 value 750.140558
#> iter 7 value 748.781748
#> iter 8 value 748.751536
#> iter 9 value 748.751486
#> iter 9 value 748.751477
#> iter 9 value 748.751472
#> final value 748.751472
#> converged
#> This is Run number 253
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.6197171 0.999364053 -1.169717 -11.600636 1
#> 2 1 -0.95 -2.35 1.1803660 0.557361371 0.230366 -1.792639 1
#> 3 1 -6.20 -2.30 2.7702375 -0.938393045 -3.429762 -3.238393 2
#> 4 1 -13.90 -2.55 -1.0333665 0.000621511 -14.933366 -2.549378 2
#> 5 1 -14.40 -5.80 5.6772584 0.337473267 -8.722742 -5.462527 2
#> 6 1 -3.60 -1.70 0.7180809 -1.523482153 -2.881919 -3.223482 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6700 -40025 7325
#> initial value 998.131940
#> iter 2 value 791.919262
#> iter 3 value 777.766786
#> iter 4 value 776.609688
#> iter 5 value 744.145843
#> iter 6 value 735.460709
#> iter 7 value 734.252548
#> iter 8 value 734.227952
#> iter 9 value 734.227923
#> iter 9 value 734.227913
#> iter 9 value 734.227906
#> final value 734.227906
#> converged
#> This is Run number 254
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 4.1904158 2.59241227 3.6404158 -10.0075877 1
#> 2 1 -0.95 -2.35 0.6318071 2.14138571 -0.3181929 -0.2086143 2
#> 3 1 -6.20 -2.30 -0.4486886 0.32046953 -6.6486886 -1.9795305 2
#> 4 1 -13.90 -2.55 3.4114280 0.03430246 -10.4885720 -2.5156975 2
#> 5 1 -14.40 -5.80 -0.7089325 2.62019631 -15.1089325 -3.1798037 2
#> 6 1 -3.60 -1.70 6.6011162 -0.72163302 3.0011162 -2.4216330 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6160 -38750 7500
#> initial value 998.131940
#> iter 2 value 810.634163
#> iter 3 value 796.418401
#> iter 4 value 794.857008
#> iter 5 value 758.707181
#> iter 6 value 750.192886
#> iter 7 value 748.934718
#> iter 8 value 748.910741
#> iter 9 value 748.910713
#> iter 9 value 748.910703
#> iter 9 value 748.910696
#> final value 748.910696
#> converged
#> This is Run number 255
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.4402523 -0.9887353 -0.1097477 -13.5887353 1
#> 2 1 -0.95 -2.35 1.5494531 2.8822533 0.5994531 0.5322533 1
#> 3 1 -6.20 -2.30 0.7975385 -0.4613180 -5.4024615 -2.7613180 2
#> 4 1 -13.90 -2.55 0.8567760 -0.9043923 -13.0432240 -3.4543923 2
#> 5 1 -14.40 -5.80 0.2642116 -0.6270664 -14.1357884 -6.4270664 2
#> 6 1 -3.60 -1.70 0.4927658 1.8388325 -3.1072342 0.1388325 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6660 -39125 6500
#> initial value 998.131940
#> iter 2 value 810.270795
#> iter 3 value 799.443926
#> iter 4 value 798.081893
#> iter 5 value 762.782520
#> iter 6 value 754.152172
#> iter 7 value 752.695273
#> iter 8 value 752.660657
#> iter 9 value 752.660586
#> iter 10 value 752.660574
#> iter 10 value 752.660567
#> iter 10 value 752.660561
#> final value 752.660561
#> converged
#> This is Run number 256
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.2436453 1.18896074 -0.7936453 -11.411039 1
#> 2 1 -0.95 -2.35 2.2454091 -0.11922326 1.2954091 -2.469223 1
#> 3 1 -6.20 -2.30 -0.2637810 0.42521340 -6.4637810 -1.874787 2
#> 4 1 -13.90 -2.55 -0.5819784 2.42218098 -14.4819784 -0.127819 2
#> 5 1 -14.40 -5.80 4.0508737 -0.01946365 -10.3491263 -5.819464 2
#> 6 1 -3.60 -1.70 1.3757228 2.77810478 -2.2242772 1.078105 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6100 -40625 8150
#> initial value 998.131940
#> iter 2 value 777.662101
#> iter 3 value 757.006316
#> iter 4 value 754.138877
#> iter 5 value 724.325319
#> iter 6 value 715.943653
#> iter 7 value 714.935922
#> iter 8 value 714.920615
#> iter 9 value 714.920604
#> iter 9 value 714.920598
#> iter 9 value 714.920598
#> final value 714.920598
#> converged
#> This is Run number 257
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.27071338 -0.3540568 0.7207134 -12.9540568 1
#> 2 1 -0.95 -2.35 0.07494138 0.4708555 -0.8750586 -1.8791445 1
#> 3 1 -6.20 -2.30 1.49787382 1.5970045 -4.7021262 -0.7029955 2
#> 4 1 -13.90 -2.55 0.04792892 -0.3201371 -13.8520711 -2.8701371 2
#> 5 1 -14.40 -5.80 0.50897854 0.7292844 -13.8910215 -5.0707156 2
#> 6 1 -3.60 -1.70 0.36966777 -0.3580409 -3.2303322 -2.0580409 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7040 -39325 6300
#> initial value 998.131940
#> iter 2 value 807.854068
#> iter 3 value 798.454167
#> iter 4 value 797.719068
#> iter 5 value 762.759881
#> iter 6 value 754.095581
#> iter 7 value 752.556624
#> iter 8 value 752.517842
#> iter 9 value 752.517749
#> iter 10 value 752.517734
#> iter 10 value 752.517727
#> iter 10 value 752.517720
#> final value 752.517720
#> converged
#> This is Run number 258
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.33196803 2.0588522 -0.2180320 -10.541148 1
#> 2 1 -0.95 -2.35 0.12840013 -0.2039175 -0.8215999 -2.553917 1
#> 3 1 -6.20 -2.30 -0.08936058 0.1248208 -6.2893606 -2.175179 2
#> 4 1 -13.90 -2.55 0.89975357 0.4167752 -13.0002464 -2.133225 2
#> 5 1 -14.40 -5.80 -0.44046379 -0.2346377 -14.8404638 -6.034638 2
#> 6 1 -3.60 -1.70 0.52815807 0.3637958 -3.0718419 -1.336204 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6040 -38150 6875
#> initial value 998.131940
#> iter 2 value 822.927788
#> iter 3 value 810.617600
#> iter 4 value 808.600803
#> iter 5 value 770.726039
#> iter 6 value 762.298998
#> iter 7 value 760.918630
#> iter 8 value 760.889857
#> iter 9 value 760.889811
#> iter 9 value 760.889800
#> iter 9 value 760.889794
#> final value 760.889794
#> converged
#> This is Run number 259
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.8780564 2.20764333 -1.428056 -10.392357 1
#> 2 1 -0.95 -2.35 1.4397950 -1.50001471 0.489795 -3.850015 1
#> 3 1 -6.20 -2.30 -0.2169486 -0.91174839 -6.416949 -3.211748 2
#> 4 1 -13.90 -2.55 -0.1822472 -0.09998267 -14.082247 -2.649983 2
#> 5 1 -14.40 -5.80 0.6001515 -0.08210979 -13.799849 -5.882110 2
#> 6 1 -3.60 -1.70 1.7128590 -1.49172820 -1.887141 -3.191728 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6480 -40025 7825
#> initial value 998.131940
#> iter 2 value 789.078234
#> iter 3 value 772.664622
#> iter 4 value 771.347166
#> iter 5 value 739.089936
#> iter 6 value 730.502929
#> iter 7 value 729.385127
#> iter 8 value 729.365821
#> iter 9 value 729.365800
#> iter 9 value 729.365792
#> iter 9 value 729.365786
#> final value 729.365786
#> converged
#> This is Run number 260
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.2026689 -0.2758724 0.6526689 -12.8758724 1
#> 2 1 -0.95 -2.35 -1.5887154 3.0894023 -2.5387154 0.7394023 2
#> 3 1 -6.20 -2.30 1.0129490 -0.3665425 -5.1870510 -2.6665425 2
#> 4 1 -13.90 -2.55 2.8700788 0.7383350 -11.0299212 -1.8116650 2
#> 5 1 -14.40 -5.80 3.1028744 -0.5085462 -11.2971256 -6.3085462 2
#> 6 1 -3.60 -1.70 0.0027649 0.4068498 -3.5972351 -1.2931502 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5680 -37750 7200
#> initial value 998.131940
#> iter 2 value 826.843666
#> iter 3 value 813.126525
#> iter 4 value 810.641819
#> iter 5 value 771.784682
#> iter 6 value 763.460592
#> iter 7 value 762.142673
#> iter 8 value 762.117632
#> iter 9 value 762.117600
#> iter 9 value 762.117590
#> iter 9 value 762.117585
#> final value 762.117585
#> converged
#> This is Run number 261
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.03938052 1.1927672 -0.5893805 -11.4072328 1
#> 2 1 -0.95 -2.35 3.13432496 0.2028294 2.1843250 -2.1471706 1
#> 3 1 -6.20 -2.30 -0.42791980 0.1915672 -6.6279198 -2.1084328 2
#> 4 1 -13.90 -2.55 2.85895386 -0.5962267 -11.0410461 -3.1462267 2
#> 5 1 -14.40 -5.80 -0.93648301 -1.1104720 -15.3364830 -6.9104720 2
#> 6 1 -3.60 -1.70 0.08913710 1.0899383 -3.5108629 -0.6100617 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5360 -37550 7425
#> initial value 998.131940
#> iter 2 value 828.307070
#> iter 3 value 812.975935
#> iter 4 value 809.816103
#> iter 5 value 770.574733
#> iter 6 value 762.307716
#> iter 7 value 761.032284
#> iter 8 value 761.009774
#> iter 9 value 761.009751
#> iter 9 value 761.009742
#> iter 9 value 761.009738
#> final value 761.009738
#> converged
#> This is Run number 262
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.1425067 -1.4406223 -0.4074933 -14.04062235 1
#> 2 1 -0.95 -2.35 0.1678418 1.3499121 -0.7821582 -1.00008795 1
#> 3 1 -6.20 -2.30 -0.1230280 -0.6759555 -6.3230280 -2.97595551 2
#> 4 1 -13.90 -2.55 2.4721228 2.4826997 -11.4278772 -0.06730028 2
#> 5 1 -14.40 -5.80 0.5183590 -0.4281362 -13.8816410 -6.22813621 2
#> 6 1 -3.60 -1.70 -0.4999486 1.1265143 -4.0999486 -0.57348566 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6460 -38925 7800
#> initial value 998.131940
#> iter 2 value 806.010915
#> iter 3 value 791.830837
#> iter 4 value 791.153079
#> iter 5 value 755.342687
#> iter 6 value 746.791024
#> iter 7 value 745.574160
#> iter 8 value 745.552279
#> iter 8 value 745.552272
#> final value 745.552272
#> converged
#> This is Run number 263
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.6377269 -0.50416279 0.08772691 -13.104163 1
#> 2 1 -0.95 -2.35 -0.5738979 -0.01040989 -1.52389790 -2.360410 1
#> 3 1 -6.20 -2.30 1.0005281 -0.16308516 -5.19947187 -2.463085 2
#> 4 1 -13.90 -2.55 0.7276166 0.29187939 -13.17238336 -2.258121 2
#> 5 1 -14.40 -5.80 2.3134102 3.51299710 -12.08658979 -2.287003 2
#> 6 1 -3.60 -1.70 1.7366259 -0.12815988 -1.86337412 -1.828160 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5920 -37100 6550
#> initial value 998.131940
#> iter 2 value 839.187781
#> iter 3 value 828.928431
#> iter 4 value 827.146195
#> iter 5 value 786.245981
#> iter 6 value 778.098462
#> iter 7 value 776.651350
#> iter 8 value 776.621914
#> iter 9 value 776.621860
#> iter 9 value 776.621858
#> iter 9 value 776.621858
#> final value 776.621858
#> converged
#> This is Run number 264
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.6209664 0.6631102 0.07096643 -11.9368898 1
#> 2 1 -0.95 -2.35 0.8757897 -1.5785130 -0.07421032 -3.9285130 1
#> 3 1 -6.20 -2.30 -0.5101587 3.4580951 -6.71015870 1.1580951 2
#> 4 1 -13.90 -2.55 -0.2240903 0.8752780 -14.12409029 -1.6747220 2
#> 5 1 -14.40 -5.80 0.9276813 3.3713160 -13.47231873 -2.4286840 2
#> 6 1 -3.60 -1.70 -0.1044358 1.1091605 -3.70443581 -0.5908395 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6020 -37825 7100
#> initial value 998.131940
#> iter 2 value 826.266903
#> iter 3 value 814.185859
#> iter 4 value 812.588821
#> iter 5 value 773.680367
#> iter 6 value 765.331249
#> iter 7 value 763.973071
#> iter 8 value 763.945951
#> iter 9 value 763.945909
#> iter 10 value 763.945897
#> iter 10 value 763.945887
#> iter 10 value 763.945885
#> final value 763.945885
#> converged
#> This is Run number 265
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.2552601 -0.08744323 -0.8052601 -12.687443 1
#> 2 1 -0.95 -2.35 -0.8589044 1.28768019 -1.8089044 -1.062320 2
#> 3 1 -6.20 -2.30 0.9168319 0.22914383 -5.2831681 -2.070856 2
#> 4 1 -13.90 -2.55 0.5863428 0.47770852 -13.3136572 -2.072291 2
#> 5 1 -14.40 -5.80 -1.8810551 -0.27699357 -16.2810551 -6.076994 2
#> 6 1 -3.60 -1.70 2.2326590 -0.95832001 -1.3673410 -2.658320 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6320 -38000 7000
#> initial value 998.131940
#> iter 2 value 824.199771
#> iter 3 value 813.149956
#> iter 4 value 812.129540
#> iter 5 value 773.535088
#> iter 6 value 765.136071
#> iter 7 value 763.739798
#> iter 8 value 763.710586
#> iter 9 value 763.710534
#> iter 10 value 763.710520
#> iter 10 value 763.710509
#> iter 10 value 763.710507
#> final value 763.710507
#> converged
#> This is Run number 266
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.5521719 2.1162354 0.002171926 -10.483765 1
#> 2 1 -0.95 -2.35 0.9513936 -0.7059960 0.001393558 -3.055996 1
#> 3 1 -6.20 -2.30 1.0143771 1.0757955 -5.185622869 -1.224204 2
#> 4 1 -13.90 -2.55 1.4865684 -0.3557861 -12.413431599 -2.905786 2
#> 5 1 -14.40 -5.80 0.3326057 0.8715644 -14.067394292 -4.928436 2
#> 6 1 -3.60 -1.70 -0.5109481 0.1392917 -4.110948112 -1.560708 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6160 -37575 7950
#> initial value 998.131940
#> iter 2 value 824.547919
#> iter 3 value 811.706234
#> iter 4 value 811.198739
#> iter 5 value 771.355225
#> iter 6 value 763.040429
#> iter 7 value 761.793135
#> iter 8 value 761.772096
#> iter 8 value 761.772095
#> final value 761.772095
#> converged
#> This is Run number 267
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 3.6418425 1.1239771 3.09184245 -11.4760229 1
#> 2 1 -0.95 -2.35 0.9290501 -0.5259110 -0.02094991 -2.8759110 1
#> 3 1 -6.20 -2.30 1.8655929 1.3855948 -4.33440705 -0.9144052 2
#> 4 1 -13.90 -2.55 0.6335735 4.4043032 -13.26642652 1.8543032 2
#> 5 1 -14.40 -5.80 1.3032937 0.4693574 -13.09670632 -5.3306426 2
#> 6 1 -3.60 -1.70 -1.5845678 3.6242659 -5.18456785 1.9242659 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7080 -38775 6875
#> initial value 998.131940
#> iter 2 value 812.963624
#> iter 3 value 803.078116
#> iter 4 value 802.940144
#> iter 5 value 766.323858
#> iter 6 value 757.748867
#> iter 7 value 756.287536
#> iter 8 value 756.253636
#> iter 9 value 756.253561
#> iter 10 value 756.253542
#> iter 10 value 756.253533
#> iter 10 value 756.253525
#> final value 756.253525
#> converged
#> This is Run number 268
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.85863948 -0.4506675 1.3086395 -13.050668 1
#> 2 1 -0.95 -2.35 0.04596431 -1.5868603 -0.9040357 -3.936860 1
#> 3 1 -6.20 -2.30 -1.23894270 0.2192232 -7.4389427 -2.080777 2
#> 4 1 -13.90 -2.55 -1.77185545 -0.4983418 -15.6718554 -3.048342 2
#> 5 1 -14.40 -5.80 -0.40853453 0.2119774 -14.8085345 -5.588023 2
#> 6 1 -3.60 -1.70 0.50957777 -0.4919903 -3.0904222 -2.191990 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6840 -39725 5950
#> initial value 998.131940
#> iter 2 value 803.676913
#> iter 3 value 793.477023
#> iter 4 value 791.586709
#> iter 5 value 758.173955
#> iter 6 value 749.450544
#> iter 7 value 747.901674
#> iter 8 value 747.860808
#> iter 9 value 747.860704
#> iter 10 value 747.860691
#> iter 10 value 747.860691
#> iter 10 value 747.860685
#> final value 747.860685
#> converged
#> This is Run number 269
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.7718741 -0.3199869 0.2218741 -12.9199869 1
#> 2 1 -0.95 -2.35 -0.3593836 -0.6087115 -1.3093836 -2.9587115 1
#> 3 1 -6.20 -2.30 -0.2082694 0.4688898 -6.4082694 -1.8311102 2
#> 4 1 -13.90 -2.55 1.1035857 0.4758437 -12.7964143 -2.0741563 2
#> 5 1 -14.40 -5.80 1.2532171 2.1069011 -13.1467829 -3.6930989 2
#> 6 1 -3.60 -1.70 0.1925566 1.2763763 -3.4074434 -0.4236237 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6400 -38225 6325
#> initial value 998.131940
#> iter 2 value 824.513406
#> iter 3 value 814.505051
#> iter 4 value 812.957506
#> iter 5 value 775.096424
#> iter 6 value 766.656763
#> iter 7 value 765.137024
#> iter 8 value 765.102162
#> iter 9 value 765.102086
#> iter 10 value 765.102074
#> iter 10 value 765.102068
#> iter 10 value 765.102064
#> final value 765.102064
#> converged
#> This is Run number 270
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.60425824 0.3128764 1.0542582 -12.287124 1
#> 2 1 -0.95 -2.35 0.07235627 3.5707550 -0.8776437 1.220755 2
#> 3 1 -6.20 -2.30 0.96356455 -0.1455178 -5.2364354 -2.445518 2
#> 4 1 -13.90 -2.55 1.17866977 0.7324385 -12.7213302 -1.817561 2
#> 5 1 -14.40 -5.80 0.68413629 0.6136341 -13.7158637 -5.186366 2
#> 6 1 -3.60 -1.70 -0.25629799 -0.1790901 -3.8562980 -1.879090 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6320 -38800 6125
#> initial value 998.131940
#> iter 2 value 817.221522
#> iter 3 value 805.990434
#> iter 4 value 803.505758
#> iter 5 value 767.572377
#> iter 6 value 758.993323
#> iter 7 value 757.478627
#> iter 8 value 757.442193
#> iter 9 value 757.442111
#> iter 9 value 757.442100
#> iter 9 value 757.442094
#> final value 757.442094
#> converged
#> This is Run number 271
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.3979533 -0.3033646 0.8479533 -12.9033646 1
#> 2 1 -0.95 -2.35 1.2403548 -0.1480009 0.2903548 -2.4980009 1
#> 3 1 -6.20 -2.30 0.0979576 -0.4825124 -6.1020424 -2.7825124 2
#> 4 1 -13.90 -2.55 -0.5131946 2.7826686 -14.4131946 0.2326686 2
#> 5 1 -14.40 -5.80 1.4826828 0.8766343 -12.9173172 -4.9233657 2
#> 6 1 -3.60 -1.70 0.7357638 1.2998386 -2.8642362 -0.4001614 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6140 -38450 7975
#> initial value 998.131940
#> iter 2 value 812.070245
#> iter 3 value 797.297561
#> iter 4 value 796.294107
#> iter 5 value 759.173788
#> iter 6 value 750.725941
#> iter 7 value 749.518966
#> iter 8 value 749.498661
#> iter 9 value 749.498644
#> iter 9 value 749.498641
#> iter 10 value 749.498626
#> iter 10 value 749.498616
#> iter 10 value 749.498614
#> final value 749.498614
#> converged
#> This is Run number 272
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.2048856 0.7941502 -0.3451144 -11.8058498 1
#> 2 1 -0.95 -2.35 1.4538246 1.3645683 0.5038246 -0.9854317 1
#> 3 1 -6.20 -2.30 1.7738528 0.3578582 -4.4261472 -1.9421418 2
#> 4 1 -13.90 -2.55 1.4193496 2.0273056 -12.4806504 -0.5226944 2
#> 5 1 -14.40 -5.80 -0.4247481 3.9689190 -14.8247481 -1.8310810 2
#> 6 1 -3.60 -1.70 4.8461607 -0.4444106 1.2461607 -2.1444106 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6460 -38625 7300
#> initial value 998.131940
#> iter 2 value 813.436569
#> iter 3 value 801.091505
#> iter 4 value 800.236617
#> iter 5 value 763.462989
#> iter 6 value 754.932131
#> iter 7 value 753.609375
#> iter 8 value 753.582383
#> iter 9 value 753.582341
#> iter 10 value 753.582327
#> iter 10 value 753.582318
#> iter 10 value 753.582311
#> final value 753.582311
#> converged
#> This is Run number 273
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.2631006 -0.4689069 -1.813101 -13.068907 1
#> 2 1 -0.95 -2.35 -1.1052696 0.4636591 -2.055270 -1.886341 2
#> 3 1 -6.20 -2.30 -0.4097308 -0.2536360 -6.609731 -2.553636 2
#> 4 1 -13.90 -2.55 -0.7447861 4.4598698 -14.644786 1.909870 2
#> 5 1 -14.40 -5.80 2.4652082 -0.6402120 -11.934792 -6.440212 2
#> 6 1 -3.60 -1.70 -0.9450787 -0.2502349 -4.545079 -1.950235 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6580 -36225 6400
#> initial value 998.131940
#> iter 2 value 850.892455
#> iter 3 value 844.306361
#> iter 4 value 844.158057
#> iter 5 value 800.508369
#> iter 6 value 792.693377
#> iter 7 value 791.161015
#> iter 8 value 791.129950
#> iter 9 value 791.129874
#> iter 9 value 791.129871
#> iter 9 value 791.129871
#> final value 791.129871
#> converged
#> This is Run number 274
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.77612950 -0.3865490 -1.3261295 -12.9865490 1
#> 2 1 -0.95 -2.35 0.05689359 0.3934569 -0.8931064 -1.9565431 1
#> 3 1 -6.20 -2.30 0.70066342 -0.8065447 -5.4993366 -3.1065447 2
#> 4 1 -13.90 -2.55 -0.86424704 -1.6095553 -14.7642470 -4.1595553 2
#> 5 1 -14.40 -5.80 1.63653758 1.2759479 -12.7634624 -4.5240521 2
#> 6 1 -3.60 -1.70 1.39532466 2.5278723 -2.2046753 0.8278723 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6460 -39600 7900
#> initial value 998.131940
#> iter 2 value 795.211057
#> iter 3 value 779.397964
#> iter 4 value 778.392022
#> iter 5 value 744.756702
#> iter 6 value 736.178833
#> iter 7 value 735.032101
#> iter 8 value 735.012473
#> iter 9 value 735.012451
#> iter 9 value 735.012444
#> iter 9 value 735.012435
#> final value 735.012435
#> converged
#> This is Run number 275
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.16437206 2.3694129 -0.3856279 -10.230587 1
#> 2 1 -0.95 -2.35 0.07988825 -0.3717487 -0.8701117 -2.721749 1
#> 3 1 -6.20 -2.30 0.26699233 -0.4774439 -5.9330077 -2.777444 2
#> 4 1 -13.90 -2.55 1.86501522 -0.3565152 -12.0349848 -2.906515 2
#> 5 1 -14.40 -5.80 -1.77503947 -0.3541150 -16.1750395 -6.154115 2
#> 6 1 -3.60 -1.70 -1.63781093 -0.5333874 -5.2378109 -2.233387 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6940 -40675 8075
#> initial value 998.131940
#> iter 2 value 776.661939
#> iter 3 value 759.798327
#> iter 4 value 759.358912
#> iter 5 value 728.963762
#> iter 6 value 720.395247
#> iter 7 value 719.362215
#> iter 8 value 719.346455
#> iter 9 value 719.346436
#> iter 9 value 719.346435
#> iter 9 value 719.346435
#> final value 719.346435
#> converged
#> This is Run number 276
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.9293992 -0.2619156 0.3793992 -12.8619156 1
#> 2 1 -0.95 -2.35 -1.4085752 -0.4011672 -2.3585752 -2.7511672 1
#> 3 1 -6.20 -2.30 0.8568314 -0.6484953 -5.3431686 -2.9484953 2
#> 4 1 -13.90 -2.55 -0.8541278 -0.6760779 -14.7541278 -3.2260779 2
#> 5 1 -14.40 -5.80 1.8478614 3.4641571 -12.5521386 -2.3358429 2
#> 6 1 -3.60 -1.70 2.4065746 1.1664569 -1.1934254 -0.5335431 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6800 -39175 6475
#> initial value 998.131940
#> iter 2 value 809.508874
#> iter 3 value 799.180322
#> iter 4 value 798.126497
#> iter 5 value 762.865888
#> iter 6 value 754.225102
#> iter 7 value 752.747693
#> iter 8 value 752.712040
#> iter 9 value 752.711963
#> iter 10 value 752.711950
#> iter 10 value 752.711942
#> iter 10 value 752.711936
#> final value 752.711936
#> converged
#> This is Run number 277
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.9055812 0.1417301 -1.455581 -12.4582699 1
#> 2 1 -0.95 -2.35 1.9247040 -0.2951434 0.974704 -2.6451434 1
#> 3 1 -6.20 -2.30 1.3158075 -1.4302361 -4.884192 -3.7302361 2
#> 4 1 -13.90 -2.55 1.0070552 0.8472370 -12.892945 -1.7027630 2
#> 5 1 -14.40 -5.80 -0.6332324 -0.7995667 -15.033232 -6.5995667 2
#> 6 1 -3.60 -1.70 0.6365395 0.9161157 -2.963460 -0.7838843 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6120 -37225 6350
#> initial value 998.131940
#> iter 2 value 838.431526
#> iter 3 value 829.040606
#> iter 4 value 827.527501
#> iter 5 value 786.886136
#> iter 6 value 778.715630
#> iter 7 value 777.212920
#> iter 8 value 777.181141
#> iter 9 value 777.181076
#> iter 9 value 777.181074
#> iter 9 value 777.181074
#> final value 777.181074
#> converged
#> This is Run number 278
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.001524013 0.6411316 -0.5515240 -11.9588684 1
#> 2 1 -0.95 -2.35 0.750347116 1.0546986 -0.1996529 -1.2953014 1
#> 3 1 -6.20 -2.30 0.466137457 1.2934910 -5.7338625 -1.0065090 2
#> 4 1 -13.90 -2.55 -0.556914859 1.0221688 -14.4569149 -1.5278312 2
#> 5 1 -14.40 -5.80 0.531830013 2.6158880 -13.8681700 -3.1841120 2
#> 6 1 -3.60 -1.70 0.340057256 2.2176824 -3.2599427 0.5176824 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6660 -39800 6675
#> initial value 998.131940
#> iter 2 value 799.085962
#> iter 3 value 786.689506
#> iter 4 value 784.952572
#> iter 5 value 751.821650
#> iter 6 value 743.104778
#> iter 7 value 741.755967
#> iter 8 value 741.724457
#> iter 9 value 741.724402
#> iter 9 value 741.724402
#> iter 9 value 741.724402
#> final value 741.724402
#> converged
#> This is Run number 279
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.7837237 1.5654851 2.233724 -11.0345149 1
#> 2 1 -0.95 -2.35 -0.7079730 -0.2799493 -1.657973 -2.6299493 1
#> 3 1 -6.20 -2.30 2.0591468 1.3507134 -4.140853 -0.9492866 2
#> 4 1 -13.90 -2.55 -0.2930431 0.4137083 -14.193043 -2.1362917 2
#> 5 1 -14.40 -5.80 0.6432261 2.3224831 -13.756774 -3.4775169 2
#> 6 1 -3.60 -1.70 -1.0362391 0.1764486 -4.636239 -1.5235514 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6700 -38250 7300
#> initial value 998.131940
#> iter 2 value 818.607814
#> iter 3 value 807.576347
#> iter 4 value 807.320138
#> iter 5 value 769.300237
#> iter 6 value 760.820854
#> iter 7 value 759.453848
#> iter 8 value 759.425536
#> iter 9 value 759.425485
#> iter 10 value 759.425469
#> iter 10 value 759.425460
#> iter 10 value 759.425452
#> final value 759.425452
#> converged
#> This is Run number 280
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.4847143 -0.9930409 -1.034714 -13.5930409 1
#> 2 1 -0.95 -2.35 -1.3183224 0.3057531 -2.268322 -2.0442469 2
#> 3 1 -6.20 -2.30 1.3990523 0.8340658 -4.800948 -1.4659342 2
#> 4 1 -13.90 -2.55 2.1841161 -0.6417372 -11.715884 -3.1917372 2
#> 5 1 -14.40 -5.80 1.5175532 -0.9624980 -12.882447 -6.7624980 2
#> 6 1 -3.60 -1.70 0.2836440 1.9346242 -3.316356 0.2346242 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5980 -38650 7725
#> initial value 998.131940
#> iter 2 value 810.814263
#> iter 3 value 795.516409
#> iter 4 value 793.698524
#> iter 5 value 757.372226
#> iter 6 value 748.904535
#> iter 7 value 747.681931
#> iter 8 value 747.660163
#> iter 9 value 747.660142
#> iter 9 value 747.660134
#> iter 9 value 747.660134
#> final value 747.660134
#> converged
#> This is Run number 281
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.90509759 0.1638638 0.3550976 -12.436136228 1
#> 2 1 -0.95 -2.35 -0.71653521 0.9526180 -1.6665352 -1.397382042 2
#> 3 1 -6.20 -2.30 0.13383855 -0.8447082 -6.0661614 -3.144708183 2
#> 4 1 -13.90 -2.55 -0.11044502 5.0615541 -14.0104450 2.511554103 2
#> 5 1 -14.40 -5.80 -0.38939275 1.1222731 -14.7893928 -4.677726854 2
#> 6 1 -3.60 -1.70 -0.06628418 1.7069123 -3.6662842 0.006912299 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6680 -38650 6825
#> initial value 998.131940
#> iter 2 value 815.542924
#> iter 3 value 804.944413
#> iter 4 value 804.212859
#> iter 5 value 767.377801
#> iter 6 value 758.831194
#> iter 7 value 757.398925
#> iter 8 value 757.366657
#> iter 9 value 757.366593
#> iter 10 value 757.366578
#> iter 10 value 757.366568
#> iter 10 value 757.366567
#> final value 757.366567
#> converged
#> This is Run number 282
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.2013878 0.5743022 -0.3486122 -12.025698 1
#> 2 1 -0.95 -2.35 1.2066503 0.4031522 0.2566503 -1.946848 1
#> 3 1 -6.20 -2.30 -0.5835865 0.4178137 -6.7835865 -1.882186 2
#> 4 1 -13.90 -2.55 4.6214791 -0.2441506 -9.2785209 -2.794151 2
#> 5 1 -14.40 -5.80 1.0993522 0.5707295 -13.3006478 -5.229271 2
#> 6 1 -3.60 -1.70 -0.4120859 0.1823609 -4.0120859 -1.517639 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6260 -38850 7175
#> initial value 998.131940
#> iter 2 value 811.005481
#> iter 3 value 797.705430
#> iter 4 value 796.054238
#> iter 5 value 760.162451
#> iter 6 value 751.608600
#> iter 7 value 750.299799
#> iter 8 value 750.272891
#> iter 9 value 750.272853
#> iter 10 value 750.272842
#> iter 10 value 750.272833
#> iter 10 value 750.272827
#> final value 750.272827
#> converged
#> This is Run number 283
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.00819158 -1.13168941 0.4581916 -13.731689 1
#> 2 1 -0.95 -2.35 0.42936756 4.24022332 -0.5206324 1.890223 2
#> 3 1 -6.20 -2.30 -0.55317758 0.92729462 -6.7531776 -1.372705 2
#> 4 1 -13.90 -2.55 1.10763434 -0.04370111 -12.7923657 -2.593701 2
#> 5 1 -14.40 -5.80 -0.00558303 0.48576025 -14.4055830 -5.314240 2
#> 6 1 -3.60 -1.70 0.25969910 4.65542024 -3.3403009 2.955420 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6280 -38475 6700
#> initial value 998.131940
#> iter 2 value 819.081953
#> iter 3 value 807.501082
#> iter 4 value 805.762303
#> iter 5 value 768.718316
#> iter 6 value 760.217025
#> iter 7 value 758.798340
#> iter 8 value 758.767109
#> iter 9 value 758.767052
#> iter 9 value 758.767052
#> iter 9 value 758.767052
#> final value 758.767052
#> converged
#> This is Run number 284
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.36788545 1.52636031 -0.9178854 -11.0736397 1
#> 2 1 -0.95 -2.35 0.63709467 0.70875165 -0.3129053 -1.6412484 1
#> 3 1 -6.20 -2.30 1.17739812 3.10833616 -5.0226019 0.8083362 2
#> 4 1 -13.90 -2.55 -0.09264853 0.33344740 -13.9926485 -2.2165526 2
#> 5 1 -14.40 -5.80 0.74080958 0.46590215 -13.6591904 -5.3340978 2
#> 6 1 -3.60 -1.70 0.08153080 0.09503826 -3.5184692 -1.6049617 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6600 -38725 6100
#> initial value 998.131940
#> iter 2 value 818.228753
#> iter 3 value 808.503501
#> iter 4 value 806.905439
#> iter 5 value 770.473138
#> iter 6 value 761.927271
#> iter 7 value 760.358929
#> iter 8 value 760.320643
#> iter 9 value 760.320551
#> iter 10 value 760.320539
#> iter 10 value 760.320535
#> iter 10 value 760.320530
#> final value 760.320530
#> converged
#> This is Run number 285
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.6022371 -1.2033874 -1.1522371 -13.8033874 1
#> 2 1 -0.95 -2.35 1.8182032 -0.5521168 0.8682032 -2.9021168 1
#> 3 1 -6.20 -2.30 0.5816969 -0.4030901 -5.6183031 -2.7030901 2
#> 4 1 -13.90 -2.55 -0.6125738 1.9198178 -14.5125738 -0.6301822 2
#> 5 1 -14.40 -5.80 0.2860004 2.7830409 -14.1139996 -3.0169591 2
#> 6 1 -3.60 -1.70 -0.3261783 -0.8303205 -3.9261783 -2.5303205 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6580 -39500 7625
#> initial value 998.131940
#> iter 2 value 798.351681
#> iter 3 value 783.950087
#> iter 4 value 783.086683
#> iter 5 value 749.024474
#> iter 6 value 740.402224
#> iter 7 value 739.197563
#> iter 8 value 739.174837
#> iter 9 value 739.174811
#> iter 9 value 739.174804
#> iter 9 value 739.174801
#> final value 739.174801
#> converged
#> This is Run number 286
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.1905537 2.18196627 0.6405537 -10.4180337 1
#> 2 1 -0.95 -2.35 0.5388286 -0.27934489 -0.4111714 -2.6293449 1
#> 3 1 -6.20 -2.30 -0.2610999 0.26879412 -6.4610999 -2.0312059 2
#> 4 1 -13.90 -2.55 0.9420888 -0.17029248 -12.9579112 -2.7202925 2
#> 5 1 -14.40 -5.80 0.1548488 0.06150118 -14.2451512 -5.7384988 2
#> 6 1 -3.60 -1.70 -0.1984917 0.95709282 -3.7984917 -0.7429072 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6180 -40400 7475
#> initial value 998.131940
#> iter 2 value 785.470845
#> iter 3 value 767.570924
#> iter 4 value 764.434163
#> iter 5 value 733.773438
#> iter 6 value 725.191845
#> iter 7 value 724.092364
#> iter 8 value 724.072099
#> iter 9 value 724.072087
#> iter 9 value 724.072083
#> iter 9 value 724.072080
#> final value 724.072080
#> converged
#> This is Run number 287
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.5076248 0.98609725 -0.04237522 -11.6139028 1
#> 2 1 -0.95 -2.35 1.3573293 0.03920183 0.40732928 -2.3107982 1
#> 3 1 -6.20 -2.30 -0.3641849 2.01204306 -6.56418492 -0.2879569 2
#> 4 1 -13.90 -2.55 -0.1267031 4.96725074 -14.02670315 2.4172507 2
#> 5 1 -14.40 -5.80 0.2795242 1.54785148 -14.12047585 -4.2521485 2
#> 6 1 -3.60 -1.70 0.6619803 1.37428527 -2.93801969 -0.3257147 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6800 -39850 6600
#> initial value 998.131940
#> iter 2 value 798.567507
#> iter 3 value 786.834120
#> iter 4 value 785.399487
#> iter 5 value 752.302906
#> iter 6 value 743.571146
#> iter 7 value 742.194513
#> iter 8 value 742.161541
#> iter 9 value 742.161480
#> iter 10 value 742.161469
#> iter 10 value 742.161462
#> iter 10 value 742.161456
#> final value 742.161456
#> converged
#> This is Run number 288
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.65580316 -0.4708927 1.1058032 -13.070893 1
#> 2 1 -0.95 -2.35 0.77763706 -0.2816477 -0.1723629 -2.631648 1
#> 3 1 -6.20 -2.30 0.68765278 -0.6020579 -5.5123472 -2.902058 2
#> 4 1 -13.90 -2.55 -0.04588102 0.1147279 -13.9458810 -2.435272 2
#> 5 1 -14.40 -5.80 0.08748400 1.7322508 -14.3125160 -4.067749 2
#> 6 1 -3.60 -1.70 -0.37499139 0.2620016 -3.9749914 -1.437998 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6460 -38850 6600
#> initial value 998.131940
#> iter 2 value 814.007535
#> iter 3 value 802.666717
#> iter 4 value 801.050467
#> iter 5 value 765.044212
#> iter 6 value 756.466101
#> iter 7 value 755.032867
#> iter 8 value 755.000046
#> iter 9 value 754.999983
#> iter 9 value 754.999983
#> iter 9 value 754.999983
#> final value 754.999983
#> converged
#> This is Run number 289
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.6011042 -0.6826234 0.05110418 -13.282623 1
#> 2 1 -0.95 -2.35 -0.1339453 -0.6745897 -1.08394527 -3.024590 1
#> 3 1 -6.20 -2.30 1.2313434 -0.1002653 -4.96865656 -2.400265 2
#> 4 1 -13.90 -2.55 -0.1695969 0.6437505 -14.06959694 -1.906249 2
#> 5 1 -14.40 -5.80 -0.2062934 0.8690371 -14.60629341 -4.930963 2
#> 6 1 -3.60 -1.70 -0.8048178 -0.4197297 -4.40481781 -2.119730 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7100 -41100 6375
#> initial value 998.131940
#> iter 2 value 779.349120
#> iter 3 value 767.145852
#> iter 4 value 765.318087
#> iter 5 value 736.111955
#> iter 6 value 727.303168
#> iter 7 value 726.024776
#> iter 8 value 725.992472
#> iter 9 value 725.992415
#> iter 9 value 725.992414
#> iter 9 value 725.992414
#> final value 725.992414
#> converged
#> This is Run number 290
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.008949155 1.6955392 -0.5410508 -10.9044608 1
#> 2 1 -0.95 -2.35 1.311077425 0.1578775 0.3610774 -2.1921225 1
#> 3 1 -6.20 -2.30 -0.300495483 -0.8522437 -6.5004955 -3.1522437 2
#> 4 1 -13.90 -2.55 3.281663352 0.8756732 -10.6183366 -1.6743268 2
#> 5 1 -14.40 -5.80 -0.523778478 1.6556789 -14.9237785 -4.1443211 2
#> 6 1 -3.60 -1.70 0.390782230 2.4784976 -3.2092178 0.7784976 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6780 -40425 7250
#> initial value 998.131940
#> iter 2 value 785.945036
#> iter 3 value 771.545249
#> iter 4 value 770.243577
#> iter 5 value 739.026683
#> iter 6 value 730.323080
#> iter 7 value 729.144734
#> iter 8 value 729.120485
#> iter 9 value 729.120458
#> iter 9 value 729.120450
#> iter 9 value 729.120449
#> final value 729.120449
#> converged
#> This is Run number 291
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.9916452 -0.1556574 -1.5416452 -12.7556574 1
#> 2 1 -0.95 -2.35 0.4452418 -0.8554306 -0.5047582 -3.2054306 1
#> 3 1 -6.20 -2.30 1.6855650 -0.6379268 -4.5144350 -2.9379268 2
#> 4 1 -13.90 -2.55 2.1738105 2.1950055 -11.7261895 -0.3549945 2
#> 5 1 -14.40 -5.80 -0.5885028 1.6089816 -14.9885028 -4.1910184 2
#> 6 1 -3.60 -1.70 -0.1394898 0.1004576 -3.7394898 -1.5995424 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5900 -38650 7450
#> initial value 998.131940
#> iter 2 value 812.506146
#> iter 3 value 797.376118
#> iter 4 value 795.017916
#> iter 5 value 758.800075
#> iter 6 value 750.317222
#> iter 7 value 749.063814
#> iter 8 value 749.040236
#> iter 9 value 749.040210
#> iter 9 value 749.040201
#> iter 9 value 749.040196
#> final value 749.040196
#> converged
#> This is Run number 292
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.60597228 -0.94821184 -1.1559723 -13.5482118 1
#> 2 1 -0.95 -2.35 0.12246990 0.18554587 -0.8275301 -2.1644541 1
#> 3 1 -6.20 -2.30 -1.07231477 -0.17785620 -7.2723148 -2.4778562 2
#> 4 1 -13.90 -2.55 0.04241251 0.06740511 -13.8575875 -2.4825949 2
#> 5 1 -14.40 -5.80 2.04608595 5.22571290 -12.3539141 -0.5742871 2
#> 6 1 -3.60 -1.70 -0.11791534 -1.01692523 -3.7179153 -2.7169252 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6460 -39250 7300
#> initial value 998.131940
#> iter 2 value 804.182615
#> iter 3 value 790.644777
#> iter 4 value 789.374218
#> iter 5 value 754.587770
#> iter 6 value 745.974760
#> iter 7 value 744.702271
#> iter 8 value 744.676314
#> iter 9 value 744.676279
#> iter 10 value 744.676268
#> iter 10 value 744.676259
#> iter 10 value 744.676253
#> final value 744.676253
#> converged
#> This is Run number 293
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.029249747 0.3062264 0.4792497 -12.2937736 1
#> 2 1 -0.95 -2.35 0.514623864 -1.8646259 -0.4353761 -4.2146259 1
#> 3 1 -6.20 -2.30 -0.448628938 -0.2372209 -6.6486289 -2.5372209 2
#> 4 1 -13.90 -2.55 0.001758364 -1.0346977 -13.8982416 -3.5846977 2
#> 5 1 -14.40 -5.80 2.537414429 -0.6550224 -11.8625856 -6.4550224 2
#> 6 1 -3.60 -1.70 0.715012376 1.1727556 -2.8849876 -0.5272444 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6340 -39650 8000
#> initial value 998.131940
#> iter 2 value 793.893537
#> iter 3 value 777.214278
#> iter 4 value 775.934878
#> iter 5 value 742.562318
#> iter 6 value 734.018357
#> iter 7 value 732.894443
#> iter 8 value 732.875967
#> iter 9 value 732.875950
#> iter 9 value 732.875947
#> iter 9 value 732.875938
#> final value 732.875938
#> converged
#> This is Run number 294
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.4373996 0.1241813 -0.1126004 -12.475819 1
#> 2 1 -0.95 -2.35 -0.5165349 1.0056473 -1.4665349 -1.344353 2
#> 3 1 -6.20 -2.30 2.0784907 1.2938491 -4.1215093 -1.006151 2
#> 4 1 -13.90 -2.55 1.7012782 0.6811564 -12.1987218 -1.868844 2
#> 5 1 -14.40 -5.80 0.1512028 -0.5688786 -14.2487972 -6.368879 2
#> 6 1 -3.60 -1.70 0.9094314 -0.7829091 -2.6905686 -2.482909 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6620 -37150 6000
#> initial value 998.131940
#> iter 2 value 840.750672
#> iter 3 value 833.693096
#> iter 4 value 833.079268
#> iter 5 value 791.941793
#> iter 6 value 783.843641
#> iter 7 value 782.210124
#> iter 8 value 782.173958
#> iter 9 value 782.173866
#> iter 9 value 782.173864
#> iter 9 value 782.173864
#> final value 782.173864
#> converged
#> This is Run number 295
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.7938052 -0.9760831 -1.343805 -13.5760831 1
#> 2 1 -0.95 -2.35 -1.0282976 2.0448155 -1.978298 -0.3051845 2
#> 3 1 -6.20 -2.30 1.9459048 1.2208429 -4.254095 -1.0791571 2
#> 4 1 -13.90 -2.55 -0.6605715 1.6678608 -14.560571 -0.8821392 2
#> 5 1 -14.40 -5.80 -0.3434108 -1.1886303 -14.743411 -6.9886303 2
#> 6 1 -3.60 -1.70 2.3465152 -0.2127604 -1.253485 -1.9127604 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6940 -39775 6500
#> initial value 998.131940
#> iter 2 value 800.092343
#> iter 3 value 789.243112
#> iter 4 value 788.152435
#> iter 5 value 754.693154
#> iter 6 value 745.961532
#> iter 7 value 744.534405
#> iter 8 value 744.499295
#> iter 9 value 744.499223
#> iter 10 value 744.499211
#> iter 10 value 744.499204
#> iter 10 value 744.499197
#> final value 744.499197
#> converged
#> This is Run number 296
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.7061212 -0.6689785 -1.256121 -13.2689785 1
#> 2 1 -0.95 -2.35 -1.1758519 0.9209812 -2.125852 -1.4290188 2
#> 3 1 -6.20 -2.30 3.2063767 2.0893906 -2.993623 -0.2106094 2
#> 4 1 -13.90 -2.55 2.5097990 1.7489708 -11.390201 -0.8010292 2
#> 5 1 -14.40 -5.80 1.2575136 -1.2619651 -13.142486 -7.0619651 2
#> 6 1 -3.60 -1.70 2.3667859 0.5637031 -1.233214 -1.1362969 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7040 -40525 7075
#> initial value 998.131940
#> iter 2 value 785.046841
#> iter 3 value 771.923139
#> iter 4 value 771.078567
#> iter 5 value 739.970771
#> iter 6 value 731.217083
#> iter 7 value 729.996208
#> iter 8 value 729.969426
#> iter 9 value 729.969390
#> iter 9 value 729.969380
#> iter 9 value 729.969372
#> final value 729.969372
#> converged
#> This is Run number 297
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.14881095 0.9628600 -0.6988109 -11.6371400 1
#> 2 1 -0.95 -2.35 -1.14492168 1.2328233 -2.0949217 -1.1171767 2
#> 3 1 -6.20 -2.30 -0.24911549 2.4536071 -6.4491155 0.1536071 2
#> 4 1 -13.90 -2.55 1.80287760 -0.6935562 -12.0971224 -3.2435562 2
#> 5 1 -14.40 -5.80 0.54510694 -0.0591580 -13.8548931 -5.8591580 2
#> 6 1 -3.60 -1.70 0.06751875 -1.2220161 -3.5324813 -2.9220161 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6980 -38725 5425
#> initial value 998.131940
#> iter 2 value 820.869048
#> iter 3 value 813.534167
#> iter 4 value 812.315178
#> iter 5 value 775.724510
#> iter 6 value 767.240817
#> iter 7 value 765.437546
#> iter 8 value 765.389753
#> iter 9 value 765.389596
#> iter 10 value 765.389580
#> iter 10 value 765.389580
#> iter 10 value 765.389574
#> final value 765.389574
#> converged
#> This is Run number 298
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.9067815 0.8753344 0.3567815 -11.7246656 1
#> 2 1 -0.95 -2.35 -0.3677609 1.2240229 -1.3177609 -1.1259771 2
#> 3 1 -6.20 -2.30 0.1482319 2.6328132 -6.0517681 0.3328132 2
#> 4 1 -13.90 -2.55 -0.3982143 0.3043862 -14.2982143 -2.2456138 2
#> 5 1 -14.40 -5.80 0.1167783 -0.4050884 -14.2832217 -6.2050884 2
#> 6 1 -3.60 -1.70 1.0130777 -0.6064547 -2.5869223 -2.3064547 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5500 -37825 7150
#> initial value 998.131940
#> iter 2 value 826.089012
#> iter 3 value 811.223275
#> iter 4 value 808.003946
#> iter 5 value 769.543490
#> iter 6 value 761.194658
#> iter 7 value 759.889914
#> iter 8 value 759.865375
#> iter 9 value 759.865346
#> iter 9 value 759.865338
#> iter 9 value 759.865333
#> final value 759.865333
#> converged
#> This is Run number 299
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.5361188 1.2465345 0.98611875 -11.3534655 1
#> 2 1 -0.95 -2.35 0.9603229 1.8858991 0.01032288 -0.4641009 1
#> 3 1 -6.20 -2.30 2.0126352 0.6903366 -4.18736484 -1.6096634 2
#> 4 1 -13.90 -2.55 1.8404572 0.6342280 -12.05954279 -1.9157720 2
#> 5 1 -14.40 -5.80 -0.5978029 1.4999378 -14.99780294 -4.3000622 2
#> 6 1 -3.60 -1.70 -0.1646452 1.9801847 -3.76464524 0.2801847 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6540 -41075 7775
#> initial value 998.131940
#> iter 2 value 772.434527
#> iter 3 value 754.113941
#> iter 4 value 752.026103
#> iter 5 value 723.240968
#> iter 6 value 714.741473
#> iter 7 value 713.732106
#> iter 8 value 713.715280
#> iter 8 value 713.715275
#> final value 713.715275
#> converged
#> This is Run number 300
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.15985898 -0.538808880 1.6098590 -13.138809 1
#> 2 1 -0.95 -2.35 1.37166454 0.356914519 0.4216645 -1.993085 1
#> 3 1 -6.20 -2.30 -0.16082264 0.429795970 -6.3608226 -1.870204 2
#> 4 1 -13.90 -2.55 -0.29086665 0.002522419 -14.1908667 -2.547478 2
#> 5 1 -14.40 -5.80 0.06632225 -0.550516303 -14.3336778 -6.350516 2
#> 6 1 -3.60 -1.70 0.64579898 0.110839458 -2.9542010 -1.589161 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6720 -37775 6125
#> initial value 998.131940
#> iter 2 value 831.530493
#> iter 3 value 823.698904
#> iter 4 value 823.037123
#> iter 5 value 783.604943
#> iter 6 value 775.308642
#> iter 7 value 773.686855
#> iter 8 value 773.649295
#> iter 9 value 773.649199
#> iter 9 value 773.649198
#> iter 9 value 773.649198
#> final value 773.649198
#> converged
#> This is Run number 301
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.0314769 0.50718647 -1.581477 -12.092814 1
#> 2 1 -0.95 -2.35 -0.2983395 -0.09345339 -1.248339 -2.443453 1
#> 3 1 -6.20 -2.30 0.9058604 0.56780467 -5.294140 -1.732195 2
#> 4 1 -13.90 -2.55 -0.5552764 0.32242730 -14.455276 -2.227573 2
#> 5 1 -14.40 -5.80 -0.7087601 1.05892282 -15.108760 -4.741077 2
#> 6 1 -3.60 -1.70 0.7342840 0.61491542 -2.865716 -1.085085 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6840 -40400 7550
#> initial value 998.131940
#> iter 2 value 784.501724
#> iter 3 value 769.537085
#> iter 4 value 768.676956
#> iter 5 value 737.349320
#> iter 6 value 728.676280
#> iter 7 value 727.538787
#> iter 8 value 727.517249
#> iter 8 value 727.517240
#> final value 727.517240
#> converged
#> This is Run number 302
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.094580 -0.6039929 -1.6445796 -13.203993 1
#> 2 1 -0.95 -2.35 1.314734 -0.3358880 0.3647341 -2.685888 1
#> 3 1 -6.20 -2.30 -1.225248 -0.2580781 -7.4252477 -2.558078 2
#> 4 1 -13.90 -2.55 1.266008 0.1781303 -12.6339917 -2.371870 2
#> 5 1 -14.40 -5.80 1.150231 1.1993404 -13.2497691 -4.600660 2
#> 6 1 -3.60 -1.70 4.937996 -0.9948892 1.3379958 -2.694889 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6760 -36475 5975
#> initial value 998.131940
#> iter 2 value 849.574907
#> iter 3 value 843.707622
#> iter 4 value 843.532292
#> iter 5 value 800.514690
#> iter 6 value 792.666006
#> iter 7 value 791.027325
#> iter 8 value 790.992729
#> iter 9 value 790.992636
#> iter 9 value 790.992632
#> iter 9 value 790.992632
#> final value 790.992632
#> converged
#> This is Run number 303
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.40590684 1.5524560 -0.9559068 -11.04754398 1
#> 2 1 -0.95 -2.35 -0.33068900 2.2673515 -1.2806890 -0.08264855 2
#> 3 1 -6.20 -2.30 -0.38422678 0.1304595 -6.5842268 -2.16954055 2
#> 4 1 -13.90 -2.55 -0.57065640 1.7052237 -14.4706564 -0.84477627 2
#> 5 1 -14.40 -5.80 -0.02260589 -1.0794134 -14.4226059 -6.87941340 2
#> 6 1 -3.60 -1.70 0.06341166 0.3808744 -3.5365883 -1.31912564 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6840 -39500 6275
#> initial value 998.131940
#> iter 2 value 805.562955
#> iter 3 value 795.221860
#> iter 4 value 793.854560
#> iter 5 value 759.629597
#> iter 6 value 750.937319
#> iter 7 value 749.441954
#> iter 8 value 749.404488
#> iter 9 value 749.404404
#> iter 10 value 749.404392
#> iter 10 value 749.404386
#> iter 10 value 749.404380
#> final value 749.404380
#> converged
#> This is Run number 304
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.1941545 3.4089685 -0.7441545 -9.191032 1
#> 2 1 -0.95 -2.35 -1.0789333 0.6011597 -2.0289333 -1.748840 2
#> 3 1 -6.20 -2.30 1.6960547 0.6016739 -4.5039453 -1.698326 2
#> 4 1 -13.90 -2.55 0.6120742 -0.2948327 -13.2879258 -2.844833 2
#> 5 1 -14.40 -5.80 0.3942412 2.4759091 -14.0057588 -3.324091 2
#> 6 1 -3.60 -1.70 3.2190117 0.2208039 -0.3809883 -1.479196 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7220 -41850 6450
#> initial value 998.131940
#> iter 2 value 766.187794
#> iter 3 value 753.018139
#> iter 4 value 750.972112
#> iter 5 value 724.162974
#> iter 6 value 715.413173
#> iter 7 value 714.273728
#> iter 8 value 714.246030
#> iter 9 value 714.245992
#> iter 9 value 714.245991
#> iter 9 value 714.245991
#> final value 714.245991
#> converged
#> This is Run number 305
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.3478016 1.7110517 -0.2021984 -10.8889483 1
#> 2 1 -0.95 -2.35 -0.2451101 1.3942342 -1.1951101 -0.9557658 2
#> 3 1 -6.20 -2.30 0.6828095 0.2478457 -5.5171905 -2.0521543 2
#> 4 1 -13.90 -2.55 3.0780664 -0.1979902 -10.8219336 -2.7479902 2
#> 5 1 -14.40 -5.80 -0.1020145 1.6251434 -14.5020145 -4.1748566 2
#> 6 1 -3.60 -1.70 -0.8691831 4.7392815 -4.4691831 3.0392815 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6280 -38800 6375
#> initial value 998.131940
#> iter 2 value 816.019245
#> iter 3 value 804.269008
#> iter 4 value 801.912782
#> iter 5 value 765.964753
#> iter 6 value 757.389612
#> iter 7 value 755.932605
#> iter 8 value 755.898783
#> iter 9 value 755.898716
#> iter 9 value 755.898705
#> iter 9 value 755.898700
#> final value 755.898700
#> converged
#> This is Run number 306
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 3.7118829 0.4204475 3.1618829 -12.1795525 1
#> 2 1 -0.95 -2.35 1.7955725 1.7363490 0.8455725 -0.6136510 1
#> 3 1 -6.20 -2.30 0.4305091 -0.5401033 -5.7694909 -2.8401033 2
#> 4 1 -13.90 -2.55 -0.7927717 2.4304739 -14.6927717 -0.1195261 2
#> 5 1 -14.40 -5.80 1.2183661 4.1554752 -13.1816339 -1.6445248 2
#> 6 1 -3.60 -1.70 0.3869888 -0.2138273 -3.2130112 -1.9138273 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6340 -37525 6700
#> initial value 998.131940
#> iter 2 value 832.410565
#> iter 3 value 822.815260
#> iter 4 value 821.909317
#> iter 5 value 781.911301
#> iter 6 value 773.642775
#> iter 7 value 772.177353
#> iter 8 value 772.146191
#> iter 9 value 772.146128
#> iter 10 value 772.146114
#> iter 10 value 772.146103
#> iter 10 value 772.146095
#> final value 772.146095
#> converged
#> This is Run number 307
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.58356302 1.27763642 0.03356302 -11.322364 1
#> 2 1 -0.95 -2.35 -0.12069215 -0.14483300 -1.07069215 -2.494833 1
#> 3 1 -6.20 -2.30 0.01304100 0.06300025 -6.18695900 -2.237000 2
#> 4 1 -13.90 -2.55 0.04833979 -0.72771657 -13.85166021 -3.277717 2
#> 5 1 -14.40 -5.80 -0.31499846 -1.20290065 -14.71499846 -7.002901 2
#> 6 1 -3.60 -1.70 0.84668095 0.03858374 -2.75331905 -1.661416 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5400 -36175 7525
#> initial value 998.131940
#> iter 2 value 845.930639
#> iter 3 value 834.155696
#> iter 4 value 832.456199
#> iter 5 value 788.977059
#> iter 6 value 781.089171
#> iter 7 value 779.810499
#> iter 8 value 779.789297
#> iter 9 value 779.789270
#> iter 9 value 779.789260
#> iter 9 value 779.789255
#> final value 779.789255
#> converged
#> This is Run number 308
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.08226743 1.7623610 -0.6322674 -10.8376390 1
#> 2 1 -0.95 -2.35 0.37250021 -1.2937515 -0.5774998 -3.6437515 1
#> 3 1 -6.20 -2.30 1.58191587 2.0350729 -4.6180841 -0.2649271 2
#> 4 1 -13.90 -2.55 0.79278414 -0.2474368 -13.1072159 -2.7974368 2
#> 5 1 -14.40 -5.80 1.31923177 1.1375148 -13.0807682 -4.6624852 2
#> 6 1 -3.60 -1.70 1.29156677 -0.4790823 -2.3084332 -2.1790823 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6020 -38025 7200
#> initial value 998.131940
#> iter 2 value 822.892938
#> iter 3 value 810.215793
#> iter 4 value 808.549339
#> iter 5 value 770.248237
#> iter 6 value 761.855908
#> iter 7 value 760.521086
#> iter 8 value 760.494689
#> iter 9 value 760.494651
#> iter 10 value 760.494639
#> iter 10 value 760.494629
#> iter 10 value 760.494624
#> final value 760.494624
#> converged
#> This is Run number 309
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.50480533 1.801557091 0.9548053 -10.7984429 1
#> 2 1 -0.95 -2.35 0.16168568 0.003540297 -0.7883143 -2.3464597 1
#> 3 1 -6.20 -2.30 0.12520410 4.131404980 -6.0747959 1.8314050 2
#> 4 1 -13.90 -2.55 -0.18819509 4.846869497 -14.0881951 2.2968695 2
#> 5 1 -14.40 -5.80 -0.00632819 -0.379901772 -14.4063282 -6.1799018 2
#> 6 1 -3.60 -1.70 -1.24212465 1.303711640 -4.8421246 -0.3962884 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6540 -38800 7075
#> initial value 998.131940
#> iter 2 value 812.098544
#> iter 3 value 800.225868
#> iter 4 value 799.278769
#> iter 5 value 763.000301
#> iter 6 value 754.432559
#> iter 7 value 753.074910
#> iter 8 value 753.045765
#> iter 9 value 753.045716
#> iter 10 value 753.045703
#> iter 10 value 753.045693
#> iter 10 value 753.045686
#> final value 753.045686
#> converged
#> This is Run number 310
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.7958703 -0.7509965 1.245870 -13.350997 1
#> 2 1 -0.95 -2.35 -0.3219374 0.8200184 -1.271937 -1.529982 1
#> 3 1 -6.20 -2.30 1.3087280 -1.1667017 -4.891272 -3.466702 2
#> 4 1 -13.90 -2.55 -0.4568792 -0.3408168 -14.356879 -2.890817 2
#> 5 1 -14.40 -5.80 1.2741497 -0.2701575 -13.125850 -6.070158 2
#> 6 1 -3.60 -1.70 0.2961015 0.5498952 -3.303898 -1.150105 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5640 -36525 7050
#> initial value 998.131940
#> iter 2 value 844.159748
#> iter 3 value 833.248612
#> iter 4 value 831.564070
#> iter 5 value 789.071110
#> iter 6 value 781.085447
#> iter 7 value 779.735822
#> iter 8 value 779.711083
#> iter 9 value 779.711045
#> iter 9 value 779.711034
#> iter 9 value 779.711029
#> final value 779.711029
#> converged
#> This is Run number 311
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.9673955 0.3836809 2.4173955 -12.216319 1
#> 2 1 -0.95 -2.35 -0.8194546 -1.5325756 -1.7694546 -3.882576 1
#> 3 1 -6.20 -2.30 1.8328013 0.1247555 -4.3671987 -2.175245 2
#> 4 1 -13.90 -2.55 -0.4657669 -1.0624877 -14.3657669 -3.612488 2
#> 5 1 -14.40 -5.80 -1.0640077 0.8685816 -15.4640077 -4.931418 2
#> 6 1 -3.60 -1.70 4.4382296 -0.4285952 0.8382296 -2.128595 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6520 -40750 6825
#> initial value 998.131940
#> iter 2 value 783.314945
#> iter 3 value 767.935947
#> iter 4 value 764.921868
#> iter 5 value 735.113853
#> iter 6 value 726.395622
#> iter 7 value 725.223427
#> iter 8 value 725.197690
#> iter 9 value 725.197660
#> iter 9 value 725.197660
#> iter 9 value 725.197660
#> final value 725.197660
#> converged
#> This is Run number 312
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.7598337 2.1988437 0.2098337 -10.4011563 1
#> 2 1 -0.95 -2.35 1.6586575 -0.5472722 0.7086575 -2.8972722 1
#> 3 1 -6.20 -2.30 0.7093915 -0.4065676 -5.4906085 -2.7065676 2
#> 4 1 -13.90 -2.55 -0.2951693 2.2431632 -14.1951693 -0.3068368 2
#> 5 1 -14.40 -5.80 0.5099310 -0.7741198 -13.8900690 -6.5741198 2
#> 6 1 -3.60 -1.70 2.7061986 0.5877788 -0.8938014 -1.1122212 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6240 -38850 7250
#> initial value 998.131940
#> iter 2 value 810.587099
#> iter 3 value 797.044385
#> iter 4 value 795.405145
#> iter 5 value 759.525050
#> iter 6 value 750.976376
#> iter 7 value 749.681323
#> iter 8 value 749.655125
#> iter 9 value 749.655089
#> iter 10 value 749.655078
#> iter 10 value 749.655069
#> iter 10 value 749.655064
#> final value 749.655064
#> converged
#> This is Run number 313
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.4312399 1.98602725 -0.9812399 -10.613973 1
#> 2 1 -0.95 -2.35 -0.2212085 -0.04895586 -1.1712085 -2.398956 1
#> 3 1 -6.20 -2.30 0.4556414 0.24529476 -5.7443586 -2.054705 2
#> 4 1 -13.90 -2.55 0.6738632 0.73677725 -13.2261368 -1.813223 2
#> 5 1 -14.40 -5.80 -0.3985851 0.52918028 -14.7985851 -5.270820 2
#> 6 1 -3.60 -1.70 -0.6329371 -0.09286154 -4.2329371 -1.792862 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7160 -39975 6350
#> initial value 998.131940
#> iter 2 value 797.469323
#> iter 3 value 787.397342
#> iter 4 value 786.580313
#> iter 5 value 753.596279
#> iter 6 value 744.835139
#> iter 7 value 743.365620
#> iter 8 value 743.327936
#> iter 9 value 743.327850
#> iter 10 value 743.327837
#> iter 10 value 743.327830
#> iter 10 value 743.327823
#> final value 743.327823
#> converged
#> This is Run number 314
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.07219961 -0.1886265 -0.4778004 -12.788627 1
#> 2 1 -0.95 -2.35 -0.32335231 -0.4993384 -1.2733523 -2.849338 1
#> 3 1 -6.20 -2.30 0.41933730 -0.6681020 -5.7806627 -2.968102 2
#> 4 1 -13.90 -2.55 0.54981169 -0.1217973 -13.3501883 -2.671797 2
#> 5 1 -14.40 -5.80 1.39773965 0.1849908 -13.0022603 -5.615009 2
#> 6 1 -3.60 -1.70 -0.30607395 -0.3337629 -3.9060740 -2.033763 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6080 -38600 6325
#> initial value 998.131940
#> iter 2 value 819.297768
#> iter 3 value 806.952963
#> iter 4 value 804.090450
#> iter 5 value 767.693466
#> iter 6 value 759.146204
#> iter 7 value 757.693663
#> iter 8 value 757.660495
#> iter 9 value 757.660429
#> iter 9 value 757.660419
#> iter 9 value 757.660414
#> final value 757.660414
#> converged
#> This is Run number 315
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.36654271 -0.2614218 -0.9165427 -12.8614218 1
#> 2 1 -0.95 -2.35 0.55885513 0.1550267 -0.3911449 -2.1949733 1
#> 3 1 -6.20 -2.30 -0.88384255 -0.9596687 -7.0838425 -3.2596687 2
#> 4 1 -13.90 -2.55 -0.01315882 3.2964378 -13.9131588 0.7464378 2
#> 5 1 -14.40 -5.80 0.62881653 0.1870362 -13.7711835 -5.6129638 2
#> 6 1 -3.60 -1.70 0.38536530 -0.1703279 -3.2146347 -1.8703279 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6540 -39750 7725
#> initial value 998.131940
#> iter 2 value 793.933463
#> iter 3 value 778.614151
#> iter 4 value 777.570860
#> iter 5 value 744.354542
#> iter 6 value 735.740694
#> iter 7 value 734.578079
#> iter 8 value 734.557033
#> iter 9 value 734.557019
#> iter 9 value 734.557015
#> iter 10 value 734.556999
#> iter 10 value 734.556990
#> iter 10 value 734.556986
#> final value 734.556986
#> converged
#> This is Run number 316
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.629480 -0.33385311 1.0794796 -12.933853 1
#> 2 1 -0.95 -2.35 1.845130 0.53983855 0.8951301 -1.810161 1
#> 3 1 -6.20 -2.30 3.448022 -0.06794323 -2.7519780 -2.367943 2
#> 4 1 -13.90 -2.55 -1.364370 1.35255294 -15.2643703 -1.197447 2
#> 5 1 -14.40 -5.80 -1.718977 0.50819185 -16.1189767 -5.291808 2
#> 6 1 -3.60 -1.70 -1.538403 -0.60846442 -5.1384034 -2.308464 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6120 -38600 8500
#> initial value 998.131940
#> iter 2 value 806.427929
#> iter 3 value 789.825732
#> iter 4 value 789.050460
#> iter 5 value 752.407194
#> iter 6 value 743.990863
#> iter 7 value 742.866716
#> iter 8 value 742.850945
#> iter 9 value 742.850927
#> iter 9 value 742.850920
#> iter 9 value 742.850916
#> final value 742.850916
#> converged
#> This is Run number 317
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.06908058 -0.3912956 -0.6190806 -12.991296 1
#> 2 1 -0.95 -2.35 -0.78614594 -0.9567659 -1.7361459 -3.306766 1
#> 3 1 -6.20 -2.30 -0.28215590 0.6953846 -6.4821559 -1.604615 2
#> 4 1 -13.90 -2.55 0.95008130 -1.2485916 -12.9499187 -3.798592 2
#> 5 1 -14.40 -5.80 0.52450917 -0.4985620 -13.8754908 -6.298562 2
#> 6 1 -3.60 -1.70 0.60343276 0.5020075 -2.9965672 -1.197993 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5980 -37250 6725
#> initial value 998.131940
#> iter 2 value 836.230660
#> iter 3 value 825.718979
#> iter 4 value 824.131617
#> iter 5 value 783.584732
#> iter 6 value 775.390734
#> iter 7 value 773.965346
#> iter 8 value 773.936417
#> iter 9 value 773.936366
#> iter 9 value 773.936364
#> iter 9 value 773.936364
#> final value 773.936364
#> converged
#> This is Run number 318
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.1591665 -0.1564187 0.60916653 -12.7564187 1
#> 2 1 -0.95 -2.35 1.0152183 -0.8295712 0.06521828 -3.1795712 1
#> 3 1 -6.20 -2.30 0.6550211 -0.4054553 -5.54497890 -2.7054553 2
#> 4 1 -13.90 -2.55 0.7746068 0.6274750 -13.12539321 -1.9225250 2
#> 5 1 -14.40 -5.80 0.2259394 0.3745007 -14.17406059 -5.4254993 2
#> 6 1 -3.60 -1.70 1.7145243 1.1914711 -1.88547574 -0.5085289 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7020 -39825 7100
#> initial value 998.131940
#> iter 2 value 795.970683
#> iter 3 value 783.852889
#> iter 4 value 783.366889
#> iter 5 value 750.028053
#> iter 6 value 741.302728
#> iter 7 value 739.998851
#> iter 8 value 739.969869
#> iter 9 value 739.969822
#> iter 10 value 739.969808
#> iter 10 value 739.969799
#> iter 10 value 739.969791
#> final value 739.969791
#> converged
#> This is Run number 319
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.0473500 0.2164144 0.4973500 -12.383586 1
#> 2 1 -0.95 -2.35 0.5382308 0.6379600 -0.4117692 -1.712040 1
#> 3 1 -6.20 -2.30 0.9016668 -0.1106530 -5.2983332 -2.410653 2
#> 4 1 -13.90 -2.55 0.6270367 0.3556341 -13.2729633 -2.194366 2
#> 5 1 -14.40 -5.80 4.8086493 1.1028323 -9.5913507 -4.697168 2
#> 6 1 -3.60 -1.70 -0.2528278 -0.6407626 -3.8528278 -2.340763 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6960 -39200 6250
#> initial value 998.131940
#> iter 2 value 810.082501
#> iter 3 value 800.706271
#> iter 4 value 799.829969
#> iter 5 value 764.543425
#> iter 6 value 755.903049
#> iter 7 value 754.352693
#> iter 8 value 754.313796
#> iter 9 value 754.313702
#> iter 10 value 754.313688
#> iter 10 value 754.313681
#> iter 10 value 754.313674
#> final value 754.313674
#> converged
#> This is Run number 320
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.62147554 -1.25170625 0.07147554 -13.8517062 1
#> 2 1 -0.95 -2.35 -0.02247538 -0.32550634 -0.97247538 -2.6755063 1
#> 3 1 -6.20 -2.30 0.41162730 2.79392450 -5.78837270 0.4939245 2
#> 4 1 -13.90 -2.55 -0.03282543 -0.06878074 -13.93282543 -2.6187807 2
#> 5 1 -14.40 -5.80 -0.62926088 0.88401003 -15.02926088 -4.9159900 2
#> 6 1 -3.60 -1.70 0.84006966 -0.03880140 -2.75993034 -1.7388014 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6240 -38950 7050
#> initial value 998.131940
#> iter 2 value 810.245376
#> iter 3 value 796.889710
#> iter 4 value 794.966932
#> iter 5 value 759.431501
#> iter 6 value 750.857944
#> iter 7 value 749.539050
#> iter 8 value 749.511355
#> iter 9 value 749.511315
#> iter 9 value 749.511304
#> iter 9 value 749.511298
#> final value 749.511298
#> converged
#> This is Run number 321
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.47064696 0.5297818 -2.020647 -12.070218 1
#> 2 1 -0.95 -2.35 -0.20229351 3.4539031 -1.152294 1.103903 2
#> 3 1 -6.20 -2.30 -0.46642555 0.9638335 -6.666426 -1.336167 2
#> 4 1 -13.90 -2.55 0.21087505 -0.1197997 -13.689125 -2.669800 2
#> 5 1 -14.40 -5.80 -0.04661594 1.1393276 -14.446616 -4.660672 2
#> 6 1 -3.60 -1.70 -0.21215975 -0.3721022 -3.812160 -2.072102 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7020 -39400 6275
#> initial value 998.131940
#> iter 2 value 806.870198
#> iter 3 value 797.345698
#> iter 4 value 796.502692
#> iter 5 value 761.797805
#> iter 6 value 753.121303
#> iter 7 value 751.587291
#> iter 8 value 751.548489
#> iter 9 value 751.548396
#> iter 10 value 751.548382
#> iter 10 value 751.548375
#> iter 10 value 751.548368
#> final value 751.548368
#> converged
#> This is Run number 322
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.78701341 1.5295592 -1.3370134 -11.0704408 1
#> 2 1 -0.95 -2.35 1.74620565 0.2455997 0.7962057 -2.1044003 1
#> 3 1 -6.20 -2.30 -0.07882724 1.1717892 -6.2788272 -1.1282108 2
#> 4 1 -13.90 -2.55 0.55789649 2.1511872 -13.3421035 -0.3988128 2
#> 5 1 -14.40 -5.80 -0.30563354 -0.8423720 -14.7056335 -6.6423720 2
#> 6 1 -3.60 -1.70 1.39817121 -1.5852613 -2.2018288 -3.2852613 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6320 -38950 5950
#> initial value 998.131940
#> iter 2 value 815.832647
#> iter 3 value 804.480538
#> iter 4 value 801.674112
#> iter 5 value 766.251827
#> iter 6 value 757.634826
#> iter 7 value 756.094215
#> iter 8 value 756.055958
#> iter 9 value 756.055861
#> iter 10 value 756.055849
#> iter 10 value 756.055849
#> iter 10 value 756.055844
#> final value 756.055844
#> converged
#> This is Run number 323
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.38205614 0.37708040 -1.9320561 -12.22291960 1
#> 2 1 -0.95 -2.35 1.51015207 -0.01738002 0.5601521 -2.36738002 1
#> 3 1 -6.20 -2.30 2.11443822 2.35480584 -4.0855618 0.05480584 2
#> 4 1 -13.90 -2.55 -0.63516341 2.27650377 -14.5351634 -0.27349623 2
#> 5 1 -14.40 -5.80 0.21084765 -0.62198258 -14.1891524 -6.42198258 2
#> 6 1 -3.60 -1.70 -0.01578352 0.79606526 -3.6157835 -0.90393474 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5940 -37500 6425
#> initial value 998.131940
#> iter 2 value 834.398041
#> iter 3 value 823.553041
#> iter 4 value 821.385339
#> iter 5 value 781.688435
#> iter 6 value 773.421222
#> iter 7 value 771.955222
#> iter 8 value 771.924271
#> iter 9 value 771.924212
#> iter 9 value 771.924202
#> iter 9 value 771.924197
#> final value 771.924197
#> converged
#> This is Run number 324
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.46787091 1.0533915 -0.08212909 -11.5466085 1
#> 2 1 -0.95 -2.35 -0.46529368 -0.5091562 -1.41529368 -2.8591562 1
#> 3 1 -6.20 -2.30 0.26367336 -1.5893438 -5.93632664 -3.8893438 2
#> 4 1 -13.90 -2.55 1.97487699 -0.1982987 -11.92512301 -2.7482987 2
#> 5 1 -14.40 -5.80 0.07546907 0.4870631 -14.32453093 -5.3129369 2
#> 6 1 -3.60 -1.70 -0.04707616 0.7349967 -3.64707616 -0.9650033 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5860 -37075 7250
#> initial value 998.131940
#> iter 2 value 835.724851
#> iter 3 value 824.291326
#> iter 4 value 822.944198
#> iter 5 value 781.856856
#> iter 6 value 773.701367
#> iter 7 value 772.359923
#> iter 8 value 772.334779
#> iter 9 value 772.334741
#> iter 10 value 772.334728
#> iter 10 value 772.334718
#> iter 10 value 772.334717
#> final value 772.334717
#> converged
#> This is Run number 325
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.8914225 -0.0459648 1.341423 -12.6459648 1
#> 2 1 -0.95 -2.35 -0.6912446 -0.3965918 -1.641245 -2.7465918 1
#> 3 1 -6.20 -2.30 -0.7232214 -0.4788291 -6.923221 -2.7788291 2
#> 4 1 -13.90 -2.55 -1.1017164 2.1832367 -15.001716 -0.3667633 2
#> 5 1 -14.40 -5.80 -0.4048291 -0.8246345 -14.804829 -6.6246345 2
#> 6 1 -3.60 -1.70 -0.8388993 0.7410073 -4.438899 -0.9589927 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6240 -38525 7200
#> initial value 998.131940
#> iter 2 value 815.626289
#> iter 3 value 802.856747
#> iter 4 value 801.428395
#> iter 5 value 764.512520
#> iter 6 value 756.012573
#> iter 7 value 754.686210
#> iter 8 value 754.659194
#> iter 9 value 754.659154
#> iter 10 value 754.659142
#> iter 10 value 754.659132
#> iter 10 value 754.659127
#> final value 754.659127
#> converged
#> This is Run number 326
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.9457421 0.01379859 0.3957421 -12.5862014 1
#> 2 1 -0.95 -2.35 -0.5945031 2.98566041 -1.5445031 0.6356604 2
#> 3 1 -6.20 -2.30 -0.2877314 3.83116242 -6.4877314 1.5311624 2
#> 4 1 -13.90 -2.55 1.1321191 2.43504301 -12.7678809 -0.1149570 2
#> 5 1 -14.40 -5.80 0.3785449 0.51901195 -14.0214551 -5.2809881 2
#> 6 1 -3.60 -1.70 0.3515232 -0.25457716 -3.2484768 -1.9545772 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5940 -38375 6850
#> initial value 998.131940
#> iter 2 value 819.883974
#> iter 3 value 806.603552
#> iter 4 value 804.030163
#> iter 5 value 766.964926
#> iter 6 value 758.487525
#> iter 7 value 757.127083
#> iter 8 value 757.098719
#> iter 9 value 757.098676
#> iter 9 value 757.098667
#> iter 9 value 757.098661
#> final value 757.098661
#> converged
#> This is Run number 327
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.0577793 0.8791231 0.5077793 -11.7208769 1
#> 2 1 -0.95 -2.35 5.0438882 0.9149064 4.0938882 -1.4350936 1
#> 3 1 -6.20 -2.30 -1.5418716 1.9689192 -7.7418716 -0.3310808 2
#> 4 1 -13.90 -2.55 -1.5791201 1.0168672 -15.4791201 -1.5331328 2
#> 5 1 -14.40 -5.80 -0.1454676 0.1607948 -14.5454676 -5.6392052 2
#> 6 1 -3.60 -1.70 -0.6114485 0.7155251 -4.2114485 -0.9844749 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6820 -39775 7275
#> initial value 998.131940
#> iter 2 value 795.976941
#> iter 3 value 782.847966
#> iter 4 value 782.105967
#> iter 5 value 748.740736
#> iter 6 value 740.047123
#> iter 7 value 738.791162
#> iter 8 value 738.764807
#> iter 9 value 738.764770
#> iter 10 value 738.764758
#> iter 10 value 738.764749
#> iter 10 value 738.764742
#> final value 738.764742
#> converged
#> This is Run number 328
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.6164419 -0.55315774 0.06644195 -13.153158 1
#> 2 1 -0.95 -2.35 -1.1933987 0.87491435 -2.14339874 -1.475086 2
#> 3 1 -6.20 -2.30 2.0312490 -0.39272183 -4.16875101 -2.692722 2
#> 4 1 -13.90 -2.55 0.3600632 1.21118110 -13.53993684 -1.338819 2
#> 5 1 -14.40 -5.80 1.5030814 0.04612378 -12.89691861 -5.753876 2
#> 6 1 -3.60 -1.70 -0.6303895 -1.10337349 -4.23038950 -2.803373 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6720 -39575 7650
#> initial value 998.131940
#> iter 2 value 796.916369
#> iter 3 value 782.767329
#> iter 4 value 782.181793
#> iter 5 value 748.280607
#> iter 6 value 739.638262
#> iter 7 value 738.436342
#> iter 8 value 738.413678
#> iter 8 value 738.413678
#> final value 738.413678
#> converged
#> This is Run number 329
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.63345292 -0.03478091 -1.1834529 -12.634781 1
#> 2 1 -0.95 -2.35 -0.02588636 1.05382460 -0.9758864 -1.296175 1
#> 3 1 -6.20 -2.30 1.57338664 -0.49584678 -4.6266134 -2.795847 2
#> 4 1 -13.90 -2.55 0.40664092 -0.86091031 -13.4933591 -3.410910 2
#> 5 1 -14.40 -5.80 0.61196773 0.85964961 -13.7880323 -4.940350 2
#> 6 1 -3.60 -1.70 1.03426258 1.26900504 -2.5657374 -0.430995 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5520 -36575 8450
#> initial value 998.131940
#> iter 2 value 834.882150
#> iter 3 value 821.124482
#> iter 4 value 820.117962
#> iter 5 value 777.433798
#> iter 6 value 769.398374
#> iter 7 value 768.214596
#> iter 8 value 768.198228
#> iter 8 value 768.198224
#> final value 768.198224
#> converged
#> This is Run number 330
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.2014078 -0.7721612 1.6514078 -13.372161 1
#> 2 1 -0.95 -2.35 1.3805602 -0.3667444 0.4305602 -2.716744 1
#> 3 1 -6.20 -2.30 0.3148464 -1.3149346 -5.8851536 -3.614935 2
#> 4 1 -13.90 -2.55 1.4536262 -1.5521222 -12.4463738 -4.102122 2
#> 5 1 -14.40 -5.80 0.5691426 -0.4494811 -13.8308574 -6.249481 2
#> 6 1 -3.60 -1.70 -0.1372707 0.2990096 -3.7372707 -1.400990 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6660 -40100 6075
#> initial value 998.131940
#> iter 2 value 797.419252
#> iter 3 value 785.442034
#> iter 4 value 782.733413
#> iter 5 value 750.717645
#> iter 6 value 741.943265
#> iter 7 value 740.506463
#> iter 8 value 740.469232
#> iter 9 value 740.469146
#> iter 9 value 740.469136
#> iter 9 value 740.469129
#> final value 740.469129
#> converged
#> This is Run number 331
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.498349 4.0480043 -1.0483490 -8.551996 1
#> 2 1 -0.95 -2.35 1.124881 0.4956368 0.1748814 -1.854363 1
#> 3 1 -6.20 -2.30 1.480164 1.0776677 -4.7198361 -1.222332 2
#> 4 1 -13.90 -2.55 1.052400 0.5539734 -12.8475997 -1.996027 2
#> 5 1 -14.40 -5.80 1.328359 1.1621677 -13.0716409 -4.637832 2
#> 6 1 -3.60 -1.70 1.113688 0.5633360 -2.4863120 -1.136664 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6340 -39150 6550
#> initial value 998.131940
#> iter 2 value 809.894170
#> iter 3 value 797.476439
#> iter 4 value 795.166803
#> iter 5 value 760.255640
#> iter 6 value 751.624165
#> iter 7 value 750.223422
#> iter 8 value 750.191202
#> iter 9 value 750.191144
#> iter 9 value 750.191134
#> iter 9 value 750.191128
#> final value 750.191128
#> converged
#> This is Run number 332
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.3830268 -0.1846500 1.833027 -12.7846500 1
#> 2 1 -0.95 -2.35 -0.4897286 1.5980095 -1.439729 -0.7519905 2
#> 3 1 -6.20 -2.30 1.2550224 0.9405607 -4.944978 -1.3594393 2
#> 4 1 -13.90 -2.55 -1.1909683 0.6612989 -15.090968 -1.8887011 2
#> 5 1 -14.40 -5.80 2.9816990 2.2632610 -11.418301 -3.5367390 2
#> 6 1 -3.60 -1.70 1.6000323 -0.2105599 -1.999968 -1.9105599 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6220 -39375 6400
#> initial value 998.131940
#> iter 2 value 807.335537
#> iter 3 value 793.988764
#> iter 4 value 790.869914
#> iter 5 value 756.832940
#> iter 6 value 748.153759
#> iter 7 value 746.766114
#> iter 8 value 746.733642
#> iter 9 value 746.733581
#> iter 9 value 746.733572
#> iter 9 value 746.733567
#> final value 746.733567
#> converged
#> This is Run number 333
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.0589620 -0.15474069 -1.60896196 -12.75474069 1
#> 2 1 -0.95 -2.35 -0.3511384 0.01170706 -1.30113837 -2.33829294 1
#> 3 1 -6.20 -2.30 0.5861452 2.33444235 -5.61385479 0.03444235 2
#> 4 1 -13.90 -2.55 -0.4451951 0.34134033 -14.34519513 -2.20865967 2
#> 5 1 -14.40 -5.80 1.2166667 4.20368226 -13.18333330 -1.59631774 2
#> 6 1 -3.60 -1.70 3.5658421 2.79183590 -0.03415792 1.09183590 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6420 -37475 6425
#> initial value 998.131940
#> iter 2 value 834.458349
#> iter 3 value 825.663412
#> iter 4 value 824.762800
#> iter 5 value 784.607062
#> iter 6 value 776.368431
#> iter 7 value 774.843259
#> iter 8 value 774.809969
#> iter 9 value 774.809896
#> iter 9 value 774.809894
#> iter 9 value 774.809894
#> final value 774.809894
#> converged
#> This is Run number 334
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.9370693 1.1731714 1.387069 -11.426829 1
#> 2 1 -0.95 -2.35 -0.1109525 -0.5582708 -1.060953 -2.908271 1
#> 3 1 -6.20 -2.30 1.1757224 -0.1306707 -5.024278 -2.430671 2
#> 4 1 -13.90 -2.55 0.7755591 1.3042647 -13.124441 -1.245735 2
#> 5 1 -14.40 -5.80 3.8068524 3.3777310 -10.593148 -2.422269 2
#> 6 1 -3.60 -1.70 -0.3400079 -0.5529537 -3.940008 -2.252954 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6480 -39975 7375
#> initial value 998.131940
#> iter 2 value 792.600854
#> iter 3 value 777.487972
#> iter 4 value 775.768040
#> iter 5 value 743.341727
#> iter 6 value 734.691219
#> iter 7 value 733.503723
#> iter 8 value 733.480264
#> iter 9 value 733.480240
#> iter 9 value 733.480232
#> iter 9 value 733.480231
#> final value 733.480231
#> converged
#> This is Run number 335
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.17450730 0.06087795 1.6245073 -12.5391221 1
#> 2 1 -0.95 -2.35 0.78615543 1.94370318 -0.1638446 -0.4062968 1
#> 3 1 -6.20 -2.30 -0.35607041 0.49310307 -6.5560704 -1.8068969 2
#> 4 1 -13.90 -2.55 2.49375070 -0.96443223 -11.4062493 -3.5144322 2
#> 5 1 -14.40 -5.80 0.06726243 -0.25792727 -14.3327376 -6.0579273 2
#> 6 1 -3.60 -1.70 0.07467203 0.21506193 -3.5253280 -1.4849381 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6780 -39175 6275
#> initial value 998.131940
#> iter 2 value 810.537920
#> iter 3 value 800.503656
#> iter 4 value 799.218868
#> iter 5 value 764.005789
#> iter 6 value 755.368255
#> iter 7 value 753.849154
#> iter 8 value 753.811648
#> iter 9 value 753.811562
#> iter 10 value 753.811549
#> iter 10 value 753.811544
#> iter 10 value 753.811538
#> final value 753.811538
#> converged
#> This is Run number 336
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.9344689 -0.1999444 -1.484469 -12.7999444 1
#> 2 1 -0.95 -2.35 -0.2264984 -0.4230930 -1.176498 -2.7730930 1
#> 3 1 -6.20 -2.30 -0.3654192 1.6548446 -6.565419 -0.6451554 2
#> 4 1 -13.90 -2.55 0.3353433 0.6751990 -13.564657 -1.8748010 2
#> 5 1 -14.40 -5.80 3.1321961 1.2437724 -11.267804 -4.5562276 2
#> 6 1 -3.60 -1.70 0.1995289 0.7236368 -3.400471 -0.9763632 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6240 -37575 7425
#> initial value 998.131940
#> iter 2 value 827.724970
#> iter 3 value 816.322784
#> iter 4 value 815.665436
#> iter 5 value 775.809336
#> iter 6 value 767.501065
#> iter 7 value 766.166077
#> iter 8 value 766.140486
#> iter 9 value 766.140445
#> iter 10 value 766.140431
#> iter 10 value 766.140421
#> iter 10 value 766.140415
#> final value 766.140415
#> converged
#> This is Run number 337
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.19867472 0.08149714 -0.7486747 -12.51850286 1
#> 2 1 -0.95 -2.35 2.34185369 0.35699970 1.3918537 -1.99300030 1
#> 3 1 -6.20 -2.30 -0.07446225 -0.10584834 -6.2744622 -2.40584834 2
#> 4 1 -13.90 -2.55 1.29217815 -0.26625308 -12.6078218 -2.81625308 2
#> 5 1 -14.40 -5.80 0.06267331 0.48748990 -14.3373267 -5.31251010 2
#> 6 1 -3.60 -1.70 -1.20717399 1.71801337 -4.8071740 0.01801337 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6420 -37325 7150
#> initial value 998.131940
#> iter 2 value 832.593680
#> iter 3 value 822.704872
#> iter 4 value 822.319291
#> iter 5 value 781.668776
#> iter 6 value 773.426751
#> iter 7 value 772.024920
#> iter 8 value 771.996651
#> iter 9 value 771.996597
#> iter 10 value 771.996581
#> iter 10 value 771.996571
#> iter 10 value 771.996565
#> final value 771.996565
#> converged
#> This is Run number 338
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 3.8362462 -0.1823339 3.286246 -12.782334 1
#> 2 1 -0.95 -2.35 -0.6571561 0.5452190 -1.607156 -1.804781 1
#> 3 1 -6.20 -2.30 2.3490039 -1.6625787 -3.850996 -3.962579 1
#> 4 1 -13.90 -2.55 2.8095248 0.4908367 -11.090475 -2.059163 2
#> 5 1 -14.40 -5.80 -0.7897648 -0.4467115 -15.189765 -6.246712 2
#> 6 1 -3.60 -1.70 2.1597726 -0.7062147 -1.440227 -2.406215 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5820 -38150 6775
#> initial value 998.131940
#> iter 2 value 823.538814
#> iter 3 value 810.213233
#> iter 4 value 807.387565
#> iter 5 value 769.727475
#> iter 6 value 761.291007
#> iter 7 value 759.919689
#> iter 8 value 759.891325
#> iter 9 value 759.891282
#> iter 9 value 759.891272
#> iter 9 value 759.891267
#> final value 759.891267
#> converged
#> This is Run number 339
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.3524023 -0.9301874 1.802402 -13.5301874 1
#> 2 1 -0.95 -2.35 0.5030850 3.4490365 -0.446915 1.0990365 2
#> 3 1 -6.20 -2.30 -0.4448381 1.6999167 -6.644838 -0.6000833 2
#> 4 1 -13.90 -2.55 0.8116578 1.3919652 -13.088342 -1.1580348 2
#> 5 1 -14.40 -5.80 -0.6964294 -1.1663204 -15.096429 -6.9663204 2
#> 6 1 -3.60 -1.70 2.4871416 0.2208575 -1.112858 -1.4791425 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6420 -37250 6350
#> initial value 998.131940
#> iter 2 value 837.889089
#> iter 3 value 829.568678
#> iter 4 value 828.744820
#> iter 5 value 787.951013
#> iter 6 value 779.784982
#> iter 7 value 778.244580
#> iter 8 value 778.211266
#> iter 9 value 778.211191
#> iter 9 value 778.211188
#> iter 9 value 778.211188
#> final value 778.211188
#> converged
#> This is Run number 340
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.72489900 0.3149005 2.1748990 -12.28509945 1
#> 2 1 -0.95 -2.35 0.02140309 1.8697448 -0.9285969 -0.48025524 2
#> 3 1 -6.20 -2.30 2.10168021 -0.3444461 -4.0983198 -2.64444611 2
#> 4 1 -13.90 -2.55 -1.01255683 1.3334944 -14.9125568 -1.21650560 2
#> 5 1 -14.40 -5.80 1.39672169 1.6207472 -13.0032783 -4.17925276 2
#> 6 1 -3.60 -1.70 0.18949537 1.7284294 -3.4105046 0.02842944 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5880 -37125 7150
#> initial value 998.131940
#> iter 2 value 835.619342
#> iter 3 value 824.321636
#> iter 4 value 822.911472
#> iter 5 value 781.978888
#> iter 6 value 773.811433
#> iter 7 value 772.455440
#> iter 8 value 772.429577
#> iter 9 value 772.429536
#> iter 10 value 772.429524
#> iter 10 value 772.429514
#> iter 10 value 772.429510
#> final value 772.429510
#> converged
#> This is Run number 341
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.7428068 2.2897717 0.1928068 -10.310228 1
#> 2 1 -0.95 -2.35 0.8053019 -1.6774258 -0.1446981 -4.027426 1
#> 3 1 -6.20 -2.30 -1.3720056 -0.5339634 -7.5720056 -2.833963 2
#> 4 1 -13.90 -2.55 -0.1080168 3.0104230 -14.0080168 0.460423 2
#> 5 1 -14.40 -5.80 -0.9774153 2.2464676 -15.3774153 -3.553532 2
#> 6 1 -3.60 -1.70 1.4997238 0.1296843 -2.1002762 -1.570316 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6700 -39225 7250
#> initial value 998.131940
#> iter 2 value 804.631655
#> iter 3 value 792.132029
#> iter 4 value 791.422984
#> iter 5 value 756.381034
#> iter 6 value 747.745656
#> iter 7 value 746.440289
#> iter 8 value 746.412789
#> iter 9 value 746.412747
#> iter 10 value 746.412734
#> iter 10 value 746.412724
#> iter 10 value 746.412717
#> final value 746.412717
#> converged
#> This is Run number 342
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.840371383 -1.144275520 1.290371 -13.7442755 1
#> 2 1 -0.95 -2.35 -0.180659912 0.006129065 -1.130660 -2.3438709 1
#> 3 1 -6.20 -2.30 0.169224400 -0.777003133 -6.030776 -3.0770031 2
#> 4 1 -13.90 -2.55 0.828893820 -0.117982112 -13.071106 -2.6679821 2
#> 5 1 -14.40 -5.80 0.752175670 -0.180421255 -13.647824 -5.9804213 2
#> 6 1 -3.60 -1.70 0.005402943 2.129517292 -3.594597 0.4295173 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6180 -38625 6825
#> initial value 998.131940
#> iter 2 value 816.294918
#> iter 3 value 803.736142
#> iter 4 value 801.684681
#> iter 5 value 765.192114
#> iter 6 value 756.664611
#> iter 7 value 755.289655
#> iter 8 value 755.260043
#> iter 9 value 755.259994
#> iter 9 value 755.259984
#> iter 9 value 755.259977
#> final value 755.259977
#> converged
#> This is Run number 343
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.02531463 0.1906863 -0.5753146 -12.409314 1
#> 2 1 -0.95 -2.35 -0.61876090 0.4279317 -1.5687609 -1.922068 1
#> 3 1 -6.20 -2.30 0.18000464 -1.5466374 -6.0199954 -3.846637 2
#> 4 1 -13.90 -2.55 0.95573340 -0.3893291 -12.9442666 -2.939329 2
#> 5 1 -14.40 -5.80 5.78483356 -0.1020647 -8.6151664 -5.902065 2
#> 6 1 -3.60 -1.70 1.73463023 -0.7188000 -1.8653698 -2.418800 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7040 -41025 7575
#> initial value 998.131940
#> iter 2 value 773.979879
#> iter 3 value 758.499143
#> iter 4 value 757.747071
#> iter 5 value 728.330119
#> iter 6 value 719.680609
#> iter 7 value 718.612603
#> iter 8 value 718.593152
#> iter 9 value 718.593129
#> iter 9 value 718.593122
#> iter 9 value 718.593116
#> final value 718.593116
#> converged
#> This is Run number 344
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.7692084 0.7352012 0.2192084 -11.8647988 1
#> 2 1 -0.95 -2.35 -1.8969808 1.2309850 -2.8469808 -1.1190150 2
#> 3 1 -6.20 -2.30 -0.2699617 3.1934366 -6.4699617 0.8934366 2
#> 4 1 -13.90 -2.55 0.3955223 -0.9354481 -13.5044777 -3.4854481 2
#> 5 1 -14.40 -5.80 0.2868132 1.3083763 -14.1131868 -4.4916237 2
#> 6 1 -3.60 -1.70 2.9389821 0.2635140 -0.6610179 -1.4364860 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6620 -40675 7025
#> initial value 998.131940
#> iter 2 value 783.352827
#> iter 3 value 768.259852
#> iter 4 value 765.961852
#> iter 5 value 735.760448
#> iter 6 value 727.056498
#> iter 7 value 725.892092
#> iter 8 value 725.867364
#> iter 9 value 725.867338
#> iter 9 value 725.867331
#> iter 9 value 725.867326
#> final value 725.867326
#> converged
#> This is Run number 345
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.03910911 1.6391779 -0.5891091 -10.9608221 1
#> 2 1 -0.95 -2.35 0.31517967 2.0893938 -0.6348203 -0.2606062 2
#> 3 1 -6.20 -2.30 -0.12868398 1.2851888 -6.3286840 -1.0148112 2
#> 4 1 -13.90 -2.55 -0.69674029 0.3612209 -14.5967403 -2.1887791 2
#> 5 1 -14.40 -5.80 1.60706151 0.1813545 -12.7929385 -5.6186455 2
#> 6 1 -3.60 -1.70 -1.33724400 0.0639025 -4.9372440 -1.6360975 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7100 -40200 6400
#> initial value 998.131940
#> iter 2 value 793.765130
#> iter 3 value 783.031321
#> iter 4 value 781.963710
#> iter 5 value 749.755901
#> iter 6 value 740.974387
#> iter 7 value 739.556976
#> iter 8 value 739.520995
#> iter 9 value 739.520919
#> iter 10 value 739.520907
#> iter 10 value 739.520901
#> iter 10 value 739.520894
#> final value 739.520894
#> converged
#> This is Run number 346
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.1421221 0.08251169 -0.6921221 -12.517488 1
#> 2 1 -0.95 -2.35 0.8369211 0.80858431 -0.1130789 -1.541416 1
#> 3 1 -6.20 -2.30 2.8699339 -1.02739652 -3.3300661 -3.327397 2
#> 4 1 -13.90 -2.55 1.2357735 -1.31597203 -12.6642265 -3.865972 2
#> 5 1 -14.40 -5.80 -0.9792634 -0.70896788 -15.3792634 -6.508968 2
#> 6 1 -3.60 -1.70 4.3953201 0.30450941 0.7953201 -1.395491 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6560 -39100 5150
#> initial value 998.131940
#> iter 2 value 816.875929
#> iter 3 value 807.145751
#> iter 4 value 804.227240
#> iter 5 value 769.235821
#> iter 6 value 760.606304
#> iter 7 value 758.824920
#> iter 8 value 758.773957
#> iter 9 value 758.773733
#> iter 10 value 758.773706
#> iter 10 value 758.773706
#> iter 11 value 758.773694
#> iter 11 value 758.773691
#> iter 11 value 758.773689
#> final value 758.773689
#> converged
#> This is Run number 347
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.4963171 1.54776181 -1.046317 -11.052238 1
#> 2 1 -0.95 -2.35 -0.4092942 -0.73490196 -1.359294 -3.084902 1
#> 3 1 -6.20 -2.30 0.9007669 0.06077286 -5.299233 -2.239227 2
#> 4 1 -13.90 -2.55 -1.1846619 0.96892488 -15.084662 -1.581075 2
#> 5 1 -14.40 -5.80 0.1620215 -1.08171979 -14.237979 -6.881720 2
#> 6 1 -3.60 -1.70 1.9468417 -1.12592985 -1.653158 -2.825930 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6280 -39225 7225
#> initial value 998.131940
#> iter 2 value 805.120005
#> iter 3 value 791.017050
#> iter 4 value 789.157742
#> iter 5 value 754.461374
#> iter 6 value 745.862181
#> iter 7 value 744.591508
#> iter 8 value 744.565599
#> iter 9 value 744.565566
#> iter 9 value 744.565556
#> iter 9 value 744.565550
#> final value 744.565550
#> converged
#> This is Run number 348
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.1070251 1.3735966 -0.4429749 -11.226403 1
#> 2 1 -0.95 -2.35 2.5382252 -1.2283300 1.5882252 -3.578330 1
#> 3 1 -6.20 -2.30 0.3895258 0.2032263 -5.8104742 -2.096774 2
#> 4 1 -13.90 -2.55 -1.2189927 -0.1188508 -15.1189927 -2.668851 2
#> 5 1 -14.40 -5.80 2.6274349 0.1071135 -11.7725651 -5.692886 2
#> 6 1 -3.60 -1.70 2.2582843 -0.6188796 -1.3417157 -2.318880 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7020 -39425 5650
#> initial value 998.131940
#> iter 2 value 809.422403
#> iter 3 value 800.910052
#> iter 4 value 799.485381
#> iter 5 value 765.000282
#> iter 6 value 756.347193
#> iter 7 value 754.653113
#> iter 8 value 754.607029
#> iter 9 value 754.606889
#> iter 10 value 754.606874
#> iter 10 value 754.606874
#> iter 10 value 754.606868
#> final value 754.606868
#> converged
#> This is Run number 349
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.01433267 1.6887938 -0.5643327 -10.9112062 1
#> 2 1 -0.95 -2.35 0.31574402 1.2191064 -0.6342560 -1.1308936 1
#> 3 1 -6.20 -2.30 -0.06492914 0.3449202 -6.2649291 -1.9550798 2
#> 4 1 -13.90 -2.55 3.02505611 0.3281834 -10.8749439 -2.2218166 2
#> 5 1 -14.40 -5.80 -0.62320971 0.3506439 -15.0232097 -5.4493561 2
#> 6 1 -3.60 -1.70 -0.16654804 2.6227382 -3.7665480 0.9227382 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6780 -38625 6300
#> initial value 998.131940
#> iter 2 value 818.532458
#> iter 3 value 809.335732
#> iter 4 value 808.445193
#> iter 5 value 771.500496
#> iter 6 value 762.974936
#> iter 7 value 761.417934
#> iter 8 value 761.380454
#> iter 9 value 761.380365
#> iter 10 value 761.380351
#> iter 10 value 761.380344
#> iter 10 value 761.380340
#> final value 761.380340
#> converged
#> This is Run number 350
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 4.0230003 0.833798587 3.473000 -11.766201 1
#> 2 1 -0.95 -2.35 -1.4871632 -0.615569238 -2.437163 -2.965569 1
#> 3 1 -6.20 -2.30 -1.0053340 1.572916981 -7.205334 -0.727083 2
#> 4 1 -13.90 -2.55 1.3485823 -1.433612543 -12.551418 -3.983613 2
#> 5 1 -14.40 -5.80 1.6443260 -0.004162723 -12.755674 -5.804163 2
#> 6 1 -3.60 -1.70 -0.7486553 -0.173373405 -4.348655 -1.873373 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6820 -40575 6550
#> initial value 998.131940
#> iter 2 value 787.340478
#> iter 3 value 774.450360
#> iter 4 value 772.385245
#> iter 5 value 741.686081
#> iter 6 value 732.908298
#> iter 7 value 731.619766
#> iter 8 value 731.588727
#> iter 9 value 731.588675
#> iter 9 value 731.588675
#> iter 9 value 731.588675
#> final value 731.588675
#> converged
#> This is Run number 351
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.0231889 -0.01071702 -1.573189 -12.610717 1
#> 2 1 -0.95 -2.35 1.9699135 4.06919077 1.019913 1.719191 2
#> 3 1 -6.20 -2.30 0.5046416 -0.95647561 -5.695358 -3.256476 2
#> 4 1 -13.90 -2.55 0.8071614 0.44074450 -13.092839 -2.109255 2
#> 5 1 -14.40 -5.80 0.6271912 -0.35827125 -13.772809 -6.158271 2
#> 6 1 -3.60 -1.70 2.3725348 -0.35232170 -1.227465 -2.052322 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6320 -40575 7550
#> initial value 998.131940
#> iter 2 value 782.134675
#> iter 3 value 764.430684
#> iter 4 value 761.753671
#> iter 5 value 731.521445
#> iter 6 value 722.946360
#> iter 7 value 721.865700
#> iter 8 value 721.846121
#> iter 8 value 721.846115
#> final value 721.846115
#> converged
#> This is Run number 352
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.1767934 -1.7626297 -0.7267934 -14.3626297 1
#> 2 1 -0.95 -2.35 4.1777955 1.8719151 3.2277955 -0.4780849 1
#> 3 1 -6.20 -2.30 2.0225471 1.1616393 -4.1774529 -1.1383607 2
#> 4 1 -13.90 -2.55 -0.3668602 0.1575424 -14.2668602 -2.3924576 2
#> 5 1 -14.40 -5.80 -0.4243312 1.9044261 -14.8243312 -3.8955739 2
#> 6 1 -3.60 -1.70 0.7445153 3.8724074 -2.8554847 2.1724074 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6360 -40350 7950
#> initial value 998.131940
#> iter 2 value 783.234317
#> iter 3 value 765.200002
#> iter 4 value 763.358892
#> iter 5 value 732.308498
#> iter 6 value 723.787577
#> iter 7 value 722.723758
#> iter 8 value 722.706459
#> iter 8 value 722.706452
#> final value 722.706452
#> converged
#> This is Run number 353
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.5889278 1.4076894 -1.138928 -11.192311 1
#> 2 1 -0.95 -2.35 -0.6842479 -0.5114510 -1.634248 -2.861451 1
#> 3 1 -6.20 -2.30 0.4429901 -0.5546245 -5.757010 -2.854624 2
#> 4 1 -13.90 -2.55 -0.5745614 0.3328260 -14.474561 -2.217174 2
#> 5 1 -14.40 -5.80 -0.9843947 -1.1808871 -15.384395 -6.980887 2
#> 6 1 -3.60 -1.70 1.4004910 0.1947095 -2.199509 -1.505290 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6380 -39075 7150
#> initial value 998.131940
#> iter 2 value 807.730018
#> iter 3 value 794.545094
#> iter 4 value 793.043329
#> iter 5 value 757.769096
#> iter 6 value 749.174792
#> iter 7 value 747.869024
#> iter 8 value 747.841730
#> iter 9 value 747.841691
#> iter 10 value 747.841680
#> iter 10 value 747.841671
#> iter 10 value 747.841665
#> final value 747.841665
#> converged
#> This is Run number 354
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.4956821 0.03096127 -1.045682 -12.569039 1
#> 2 1 -0.95 -2.35 -0.1474271 -0.19864114 -1.097427 -2.548641 1
#> 3 1 -6.20 -2.30 1.3401975 0.68786517 -4.859803 -1.612135 2
#> 4 1 -13.90 -2.55 1.7107599 1.14629727 -12.189240 -1.403703 2
#> 5 1 -14.40 -5.80 -0.4163354 -1.05937308 -14.816335 -6.859373 2
#> 6 1 -3.60 -1.70 -0.7355363 -0.33361057 -4.335536 -2.033611 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6500 -38425 6625
#> initial value 998.131940
#> iter 2 value 820.035676
#> iter 3 value 809.586530
#> iter 4 value 808.421991
#> iter 5 value 771.038591
#> iter 6 value 762.546780
#> iter 7 value 761.083672
#> iter 8 value 761.050621
#> iter 9 value 761.050554
#> iter 10 value 761.050541
#> iter 10 value 761.050532
#> iter 10 value 761.050528
#> final value 761.050528
#> converged
#> This is Run number 355
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.1647103 0.07930866 -0.3852897 -12.520691341 1
#> 2 1 -0.95 -2.35 -0.1424667 0.09561892 -1.0924667 -2.254381083 1
#> 3 1 -6.20 -2.30 0.1453071 2.29248432 -6.0546929 -0.007515684 2
#> 4 1 -13.90 -2.55 0.2810925 0.06856221 -13.6189075 -2.481437787 2
#> 5 1 -14.40 -5.80 0.2624897 0.28416731 -14.1375103 -5.515832692 2
#> 6 1 -3.60 -1.70 0.1326678 0.87133245 -3.4673322 -0.828667548 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5800 -38275 7200
#> initial value 998.131940
#> iter 2 value 819.411201
#> iter 3 value 805.080679
#> iter 4 value 802.488279
#> iter 5 value 765.186242
#> iter 6 value 756.750302
#> iter 7 value 755.447849
#> iter 8 value 755.422520
#> iter 9 value 755.422489
#> iter 9 value 755.422479
#> iter 9 value 755.422474
#> final value 755.422474
#> converged
#> This is Run number 356
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 3.1639730 2.2700330 2.6139730 -10.329967 1
#> 2 1 -0.95 -2.35 1.9268195 -0.5313038 0.9768195 -2.881304 1
#> 3 1 -6.20 -2.30 -1.2520206 0.4916557 -7.4520206 -1.808344 2
#> 4 1 -13.90 -2.55 0.7966865 -0.2261394 -13.1033135 -2.776139 2
#> 5 1 -14.40 -5.80 0.9265471 -0.9538936 -13.4734529 -6.753894 2
#> 6 1 -3.60 -1.70 1.3908764 -0.4156827 -2.2091236 -2.115683 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6960 -39750 5700
#> initial value 998.131940
#> iter 2 value 804.298384
#> iter 3 value 794.943756
#> iter 4 value 793.129145
#> iter 5 value 759.748662
#> iter 6 value 751.032268
#> iter 7 value 749.398314
#> iter 8 value 749.353398
#> iter 9 value 749.353266
#> iter 10 value 749.353252
#> iter 10 value 749.353252
#> iter 10 value 749.353245
#> final value 749.353245
#> converged
#> This is Run number 357
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.2163244 2.0755156 -0.7663244 -10.524484 1
#> 2 1 -0.95 -2.35 0.1444617 2.7800720 -0.8055383 0.430072 2
#> 3 1 -6.20 -2.30 4.1538867 1.2051474 -2.0461133 -1.094853 2
#> 4 1 -13.90 -2.55 0.1143133 0.2053682 -13.7856867 -2.344632 2
#> 5 1 -14.40 -5.80 0.2530071 -0.7430220 -14.1469929 -6.543022 2
#> 6 1 -3.60 -1.70 -0.4340374 -0.4435678 -4.0340374 -2.143568 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7540 -37625 5175
#> initial value 998.131940
#> iter 2 value 836.630691
#> iter 3 value 832.151170
#> iter 4 value 832.119520
#> iter 5 value 791.884196
#> iter 6 value 783.886878
#> iter 7 value 781.937015
#> iter 8 value 781.889829
#> iter 9 value 781.889663
#> iter 9 value 781.889653
#> iter 9 value 781.889648
#> final value 781.889648
#> converged
#> This is Run number 358
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.06739831 0.69529612 -0.6173983 -11.9047039 1
#> 2 1 -0.95 -2.35 0.81668059 -0.03531337 -0.1333194 -2.3853134 1
#> 3 1 -6.20 -2.30 0.72046779 0.85285334 -5.4795322 -1.4471467 2
#> 4 1 -13.90 -2.55 -0.15622525 0.10450807 -14.0562253 -2.4454919 2
#> 5 1 -14.40 -5.80 -0.90321422 0.52869760 -15.3032142 -5.2713024 2
#> 6 1 -3.60 -1.70 1.58720911 2.46149805 -2.0127909 0.7614981 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6760 -38125 6750
#> initial value 998.131940
#> iter 2 value 823.398595
#> iter 3 value 813.994851
#> iter 4 value 813.612432
#> iter 5 value 775.153250
#> iter 6 value 766.723202
#> iter 7 value 765.234403
#> iter 8 value 765.200888
#> iter 9 value 765.200814
#> iter 10 value 765.200797
#> iter 10 value 765.200787
#> iter 10 value 765.200783
#> final value 765.200783
#> converged
#> This is Run number 359
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.6188256 -0.06815642 0.06882556 -12.668156 1
#> 2 1 -0.95 -2.35 0.5141668 0.12498910 -0.43583323 -2.225011 1
#> 3 1 -6.20 -2.30 0.3418607 -0.47637036 -5.85813935 -2.776370 2
#> 4 1 -13.90 -2.55 0.7931820 -1.18340333 -13.10681803 -3.733403 2
#> 5 1 -14.40 -5.80 0.3194183 0.43100700 -14.08058172 -5.368993 2
#> 6 1 -3.60 -1.70 0.8196028 -1.63211592 -2.78039724 -3.332116 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6420 -39150 7150
#> initial value 998.131940
#> iter 2 value 806.579370
#> iter 3 value 793.414178
#> iter 4 value 791.969250
#> iter 5 value 756.901162
#> iter 6 value 748.294456
#> iter 7 value 746.991423
#> iter 8 value 746.964086
#> iter 9 value 746.964047
#> iter 10 value 746.964035
#> iter 10 value 746.964026
#> iter 10 value 746.964021
#> final value 746.964021
#> converged
#> This is Run number 360
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.45632825 0.4773167 -1.006328 -12.1226833 1
#> 2 1 -0.95 -2.35 1.41010702 -0.1876814 0.460107 -2.5376814 1
#> 3 1 -6.20 -2.30 0.52837584 -0.2807183 -5.671624 -2.5807183 2
#> 4 1 -13.90 -2.55 1.14854173 3.1284415 -12.751458 0.5784415 2
#> 5 1 -14.40 -5.80 0.19964892 0.4862284 -14.200351 -5.3137716 2
#> 6 1 -3.60 -1.70 0.07946421 -0.2202404 -3.520536 -1.9202404 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6240 -36775 6425
#> initial value 998.131940
#> iter 2 value 843.966177
#> iter 3 value 835.715227
#> iter 4 value 834.837824
#> iter 5 value 792.798838
#> iter 6 value 784.774229
#> iter 7 value 783.273462
#> iter 8 value 783.242586
#> iter 9 value 783.242520
#> iter 9 value 783.242516
#> iter 9 value 783.242516
#> final value 783.242516
#> converged
#> This is Run number 361
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.51498132 2.4538083 -0.03501868 -10.1461917 1
#> 2 1 -0.95 -2.35 -0.71842931 -0.9474839 -1.66842931 -3.2974839 1
#> 3 1 -6.20 -2.30 0.05002474 -0.6330070 -6.14997526 -2.9330070 2
#> 4 1 -13.90 -2.55 0.16714203 -0.3488155 -13.73285797 -2.8988155 2
#> 5 1 -14.40 -5.80 1.91759542 0.6568617 -12.48240458 -5.1431383 2
#> 6 1 -3.60 -1.70 0.66187875 1.3674711 -2.93812125 -0.3325289 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6080 -38875 7300
#> initial value 998.131940
#> iter 2 value 810.012725
#> iter 3 value 795.563277
#> iter 4 value 793.445374
#> iter 5 value 757.797076
#> iter 6 value 749.259800
#> iter 7 value 747.988233
#> iter 8 value 747.963147
#> iter 9 value 747.963116
#> iter 9 value 747.963106
#> iter 9 value 747.963101
#> final value 747.963101
#> converged
#> This is Run number 362
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.23390383 -0.1052986 -0.7839038 -12.7052986 1
#> 2 1 -0.95 -2.35 -0.08126034 1.6060861 -1.0312603 -0.7439139 2
#> 3 1 -6.20 -2.30 0.51963484 5.4460350 -5.6803652 3.1460350 2
#> 4 1 -13.90 -2.55 1.09290992 0.7979132 -12.8070901 -1.7520868 2
#> 5 1 -14.40 -5.80 0.04661247 1.5709687 -14.3533875 -4.2290313 2
#> 6 1 -3.60 -1.70 1.93927856 -0.5402503 -1.6607214 -2.2402503 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6580 -37025 6000
#> initial value 998.131940
#> iter 2 value 842.458362
#> iter 3 value 835.460265
#> iter 4 value 834.835288
#> iter 5 value 793.373097
#> iter 6 value 785.313892
#> iter 7 value 783.688344
#> iter 8 value 783.652790
#> iter 9 value 783.652701
#> iter 9 value 783.652699
#> iter 9 value 783.652699
#> final value 783.652699
#> converged
#> This is Run number 363
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.4375808 2.5347218 -0.9875808 -10.065278 1
#> 2 1 -0.95 -2.35 0.4008422 -0.5472970 -0.5491578 -2.897297 1
#> 3 1 -6.20 -2.30 0.4459111 0.0593896 -5.7540889 -2.240610 2
#> 4 1 -13.90 -2.55 1.4093182 0.4646540 -12.4906818 -2.085346 2
#> 5 1 -14.40 -5.80 -0.5070267 3.3176282 -14.9070267 -2.482372 2
#> 6 1 -3.60 -1.70 0.4878147 -0.3172919 -3.1121853 -2.017292 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6220 -39075 7825
#> initial value 998.131940
#> iter 2 value 803.797170
#> iter 3 value 788.358299
#> iter 4 value 787.012756
#> iter 5 value 751.851182
#> iter 6 value 743.322542
#> iter 7 value 742.132008
#> iter 8 value 742.111126
#> iter 8 value 742.111115
#> final value 742.111115
#> converged
#> This is Run number 364
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.01995143 0.53422335 -0.5300486 -12.065777 1
#> 2 1 -0.95 -2.35 -0.62971605 0.06020800 -1.5797160 -2.289792 1
#> 3 1 -6.20 -2.30 0.60995632 0.08139514 -5.5900437 -2.218605 2
#> 4 1 -13.90 -2.55 1.60937819 0.61695081 -12.2906218 -1.933049 2
#> 5 1 -14.40 -5.80 -0.40124867 0.31516816 -14.8012487 -5.484832 2
#> 6 1 -3.60 -1.70 2.24563245 -0.54011054 -1.3543676 -2.240111 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7060 -40475 6650
#> initial value 998.131940
#> iter 2 value 788.148555
#> iter 3 value 776.257903
#> iter 4 value 775.121898
#> iter 5 value 743.831508
#> iter 6 value 735.044632
#> iter 7 value 733.728957
#> iter 8 value 733.697153
#> iter 9 value 733.697098
#> iter 9 value 733.697087
#> iter 9 value 733.697079
#> final value 733.697079
#> converged
#> This is Run number 365
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.8751368 -0.9911158 0.3251368 -13.591116 1
#> 2 1 -0.95 -2.35 0.1464418 3.5580936 -0.8035582 1.208094 2
#> 3 1 -6.20 -2.30 -1.1980566 -0.1028167 -7.3980566 -2.402817 2
#> 4 1 -13.90 -2.55 2.7824423 -0.6203856 -11.1175577 -3.170386 2
#> 5 1 -14.40 -5.80 -0.3606440 0.6812046 -14.7606440 -5.118795 2
#> 6 1 -3.60 -1.70 0.8549905 2.9972896 -2.7450095 1.297290 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6540 -38900 6550
#> initial value 998.131940
#> iter 2 value 813.464444
#> iter 3 value 802.458650
#> iter 4 value 800.983558
#> iter 5 value 765.069570
#> iter 6 value 756.481052
#> iter 7 value 755.031367
#> iter 8 value 754.997685
#> iter 9 value 754.997618
#> iter 10 value 754.997606
#> iter 10 value 754.997598
#> iter 10 value 754.997597
#> final value 754.997597
#> converged
#> This is Run number 366
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.5695015 0.20727390 0.01950149 -12.3927261 1
#> 2 1 -0.95 -2.35 0.2393554 0.29883996 -0.71064464 -2.0511600 1
#> 3 1 -6.20 -2.30 2.1657006 -0.19050295 -4.03429936 -2.4905029 2
#> 4 1 -13.90 -2.55 1.4067805 0.63720574 -12.49321950 -1.9127943 2
#> 5 1 -14.40 -5.80 0.6878175 -0.06525298 -13.71218248 -5.8652530 2
#> 6 1 -3.60 -1.70 0.4342491 1.46327143 -3.16575094 -0.2367286 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6080 -37950 6125
#> initial value 998.131940
#> iter 2 value 829.572433
#> iter 3 value 818.815599
#> iter 4 value 816.389203
#> iter 5 value 778.008470
#> iter 6 value 769.620999
#> iter 7 value 768.093586
#> iter 8 value 768.059064
#> iter 9 value 768.058989
#> iter 9 value 768.058978
#> iter 9 value 768.058973
#> final value 768.058973
#> converged
#> This is Run number 367
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.1874893 -1.2087198 -0.737489278 -13.8087198 1
#> 2 1 -0.95 -2.35 0.9526646 0.1423270 0.002664623 -2.2076730 1
#> 3 1 -6.20 -2.30 1.8403500 1.8578535 -4.359649967 -0.4421465 2
#> 4 1 -13.90 -2.55 2.8530679 -0.2822310 -11.046932091 -2.8322310 2
#> 5 1 -14.40 -5.80 -0.8516124 2.7621652 -15.251612433 -3.0378348 2
#> 6 1 -3.60 -1.70 6.3520478 0.9184675 2.752047773 -0.7815325 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6400 -39375 7975
#> initial value 998.131940
#> iter 2 value 798.210136
#> iter 3 value 782.427358
#> iter 4 value 781.475501
#> iter 5 value 747.154833
#> iter 6 value 738.600097
#> iter 7 value 737.447510
#> iter 8 value 737.428186
#> iter 9 value 737.428165
#> iter 9 value 737.428157
#> iter 9 value 737.428148
#> final value 737.428148
#> converged
#> This is Run number 368
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.4062999 2.8343699 -0.1437001 -9.765630 1
#> 2 1 -0.95 -2.35 1.5973706 -1.5884579 0.6473706 -3.938458 1
#> 3 1 -6.20 -2.30 0.3456394 -0.4764808 -5.8543606 -2.776481 2
#> 4 1 -13.90 -2.55 -0.8083315 -0.6385367 -14.7083315 -3.188537 2
#> 5 1 -14.40 -5.80 1.0850059 0.1068061 -13.3149941 -5.693194 2
#> 6 1 -3.60 -1.70 0.5018938 3.3553942 -3.0981062 1.655394 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5580 -37275 7000
#> initial value 998.131940
#> iter 2 value 834.499348
#> iter 3 value 821.640321
#> iter 4 value 819.097887
#> iter 5 value 778.892110
#> iter 6 value 770.679340
#> iter 7 value 769.330882
#> iter 8 value 769.305245
#> iter 9 value 769.305209
#> iter 9 value 769.305199
#> iter 9 value 769.305194
#> final value 769.305194
#> converged
#> This is Run number 369
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.7902159 -0.8189835 -1.340216 -13.4189835 1
#> 2 1 -0.95 -2.35 -0.3906358 -0.4260556 -1.340636 -2.7760556 1
#> 3 1 -6.20 -2.30 1.0894944 1.7445495 -5.110506 -0.5554505 2
#> 4 1 -13.90 -2.55 -0.1850612 0.6815254 -14.085061 -1.8684746 2
#> 5 1 -14.40 -5.80 0.6805067 2.3398522 -13.719493 -3.4601478 2
#> 6 1 -3.60 -1.70 0.5428826 -0.7067463 -3.057117 -2.4067463 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6600 -39800 7750
#> initial value 998.131940
#> iter 2 value 792.951216
#> iter 3 value 777.683514
#> iter 4 value 776.777968
#> iter 5 value 743.683178
#> iter 6 value 735.062785
#> iter 7 value 733.905691
#> iter 8 value 733.884880
#> iter 9 value 733.884862
#> iter 9 value 733.884859
#> iter 10 value 733.884845
#> iter 10 value 733.884836
#> iter 10 value 733.884834
#> final value 733.884834
#> converged
#> This is Run number 370
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.3909281 -0.6072395 -0.9409281 -13.2072395 1
#> 2 1 -0.95 -2.35 -0.3691396 1.6925847 -1.3191396 -0.6574153 2
#> 3 1 -6.20 -2.30 0.3141480 2.4939592 -5.8858520 0.1939592 2
#> 4 1 -13.90 -2.55 1.6185558 -0.6706478 -12.2814442 -3.2206478 2
#> 5 1 -14.40 -5.80 2.6666213 -1.3239352 -11.7333787 -7.1239352 2
#> 6 1 -3.60 -1.70 -0.3682570 -0.4843449 -3.9682570 -2.1843449 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6500 -39150 6975
#> initial value 998.131940
#> iter 2 value 807.500091
#> iter 3 value 795.041824
#> iter 4 value 793.660719
#> iter 5 value 758.533229
#> iter 6 value 749.913357
#> iter 7 value 748.571412
#> iter 8 value 748.542120
#> iter 9 value 748.542073
#> iter 10 value 748.542061
#> iter 10 value 748.542052
#> iter 10 value 748.542046
#> final value 748.542046
#> converged
#> This is Run number 371
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.8273588 1.1024889 2.277359 -11.4975111 1
#> 2 1 -0.95 -2.35 -0.2498194 -0.4256222 -1.199819 -2.7756222 1
#> 3 1 -6.20 -2.30 0.8873638 -0.1677692 -5.312636 -2.4677692 2
#> 4 1 -13.90 -2.55 1.0876094 -0.6882743 -12.812391 -3.2382743 2
#> 5 1 -14.40 -5.80 -0.9126750 0.8517798 -15.312675 -4.9482202 2
#> 6 1 -3.60 -1.70 -0.7615486 1.0037164 -4.361549 -0.6962836 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6000 -39000 7725
#> initial value 998.131940
#> iter 2 value 805.646106
#> iter 3 value 789.618798
#> iter 4 value 787.555409
#> iter 5 value 752.359711
#> iter 6 value 743.855228
#> iter 7 value 742.656718
#> iter 8 value 742.635422
#> iter 9 value 742.635403
#> iter 9 value 742.635397
#> iter 9 value 742.635394
#> final value 742.635394
#> converged
#> This is Run number 372
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.2984392 2.4489337 -0.8484392 -10.1510663 1
#> 2 1 -0.95 -2.35 -0.4680845 -0.1391742 -1.4180845 -2.4891742 1
#> 3 1 -6.20 -2.30 0.8443279 -1.0376599 -5.3556721 -3.3376599 2
#> 4 1 -13.90 -2.55 -0.8184065 3.0300119 -14.7184065 0.4800119 2
#> 5 1 -14.40 -5.80 -1.3966762 0.2316948 -15.7966762 -5.5683052 2
#> 6 1 -3.60 -1.70 -0.8443892 0.8223841 -4.4443892 -0.8776159 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6980 -38750 6975
#> initial value 998.131940
#> iter 2 value 812.911051
#> iter 3 value 802.599545
#> iter 4 value 802.398700
#> iter 5 value 765.749538
#> iter 6 value 757.173248
#> iter 7 value 755.743221
#> iter 8 value 755.710822
#> iter 9 value 755.710754
#> iter 10 value 755.710736
#> iter 10 value 755.710727
#> iter 10 value 755.710719
#> final value 755.710719
#> converged
#> This is Run number 373
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.40311048 0.6188739 -0.1468895 -11.98112608 1
#> 2 1 -0.95 -2.35 -0.07586796 3.8948570 -1.0258680 1.54485697 2
#> 3 1 -6.20 -2.30 0.26682261 2.3918669 -5.9331774 0.09186686 2
#> 4 1 -13.90 -2.55 -0.57302935 1.1657545 -14.4730293 -1.38424551 2
#> 5 1 -14.40 -5.80 -1.04429617 0.3873057 -15.4442962 -5.41269430 2
#> 6 1 -3.60 -1.70 -0.07368434 -0.8095394 -3.6736843 -2.50953943 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6560 -38525 6175
#> initial value 998.131940
#> iter 2 value 820.813180
#> iter 3 value 811.159712
#> iter 4 value 809.679208
#> iter 5 value 772.638315
#> iter 6 value 764.135057
#> iter 7 value 762.576863
#> iter 8 value 762.539612
#> iter 9 value 762.539525
#> iter 10 value 762.539513
#> iter 10 value 762.539507
#> iter 10 value 762.539505
#> final value 762.539505
#> converged
#> This is Run number 374
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.0094982 1.0977488 0.4594982 -11.502251 1
#> 2 1 -0.95 -2.35 0.1242718 -0.1444734 -0.8257282 -2.494473 1
#> 3 1 -6.20 -2.30 2.6413519 -0.6005646 -3.5586481 -2.900565 2
#> 4 1 -13.90 -2.55 3.2114058 0.8292145 -10.6885942 -1.720785 2
#> 5 1 -14.40 -5.80 -0.9376428 1.5703528 -15.3376428 -4.229647 2
#> 6 1 -3.60 -1.70 0.9083187 1.2261480 -2.6916813 -0.473852 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5680 -38625 6800
#> initial value 998.131940
#> iter 2 value 816.578230
#> iter 3 value 801.196248
#> iter 4 value 797.396418
#> iter 5 value 761.347269
#> iter 6 value 752.802784
#> iter 7 value 751.486929
#> iter 8 value 751.459930
#> iter 9 value 751.459893
#> iter 9 value 751.459885
#> iter 9 value 751.459881
#> final value 751.459881
#> converged
#> This is Run number 375
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.8416216 0.4739841 0.2916216 -12.1260159 1
#> 2 1 -0.95 -2.35 0.7674261 1.9003111 -0.1825739 -0.4496889 1
#> 3 1 -6.20 -2.30 -0.1642891 0.5924705 -6.3642891 -1.7075295 2
#> 4 1 -13.90 -2.55 -1.2235572 0.3337879 -15.1235572 -2.2162121 2
#> 5 1 -14.40 -5.80 1.9947066 3.4438550 -12.4052934 -2.3561450 2
#> 6 1 -3.60 -1.70 0.4160676 -0.4382540 -3.1839324 -2.1382540 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5680 -37725 6675
#> initial value 998.131940
#> iter 2 value 830.066285
#> iter 3 value 817.050882
#> iter 4 value 814.099169
#> iter 5 value 775.240155
#> iter 6 value 766.894687
#> iter 7 value 765.505296
#> iter 8 value 765.477041
#> iter 9 value 765.476996
#> iter 9 value 765.476987
#> iter 9 value 765.476983
#> final value 765.476983
#> converged
#> This is Run number 376
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.6336797 0.3933123 0.08367973 -12.2066877 1
#> 2 1 -0.95 -2.35 0.8934883 1.6525625 -0.05651167 -0.6974375 1
#> 3 1 -6.20 -2.30 1.9000939 0.8107729 -4.29990613 -1.4892271 2
#> 4 1 -13.90 -2.55 2.1753895 1.2698681 -11.72461046 -1.2801319 2
#> 5 1 -14.40 -5.80 2.0232928 1.8456050 -12.37670722 -3.9543950 2
#> 6 1 -3.60 -1.70 2.1533809 0.2632653 -1.44661913 -1.4367347 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7020 -39125 6575
#> initial value 998.131940
#> iter 2 value 809.477345
#> iter 3 value 799.713789
#> iter 4 value 799.231085
#> iter 5 value 763.657755
#> iter 6 value 755.020669
#> iter 7 value 753.528709
#> iter 8 value 753.492554
#> iter 9 value 753.492472
#> iter 10 value 753.492456
#> iter 10 value 753.492446
#> iter 10 value 753.492439
#> final value 753.492439
#> converged
#> This is Run number 377
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.6985567 1.0295795 2.1485567 -11.5704205 1
#> 2 1 -0.95 -2.35 1.4779324 1.3619245 0.5279324 -0.9880755 1
#> 3 1 -6.20 -2.30 0.6740668 1.5149367 -5.5259332 -0.7850633 2
#> 4 1 -13.90 -2.55 1.2484564 1.8452279 -12.6515436 -0.7047721 2
#> 5 1 -14.40 -5.80 1.7680666 -1.0564887 -12.6319334 -6.8564887 2
#> 6 1 -3.60 -1.70 0.5286699 0.8785516 -3.0713301 -0.8214484 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6920 -39200 6350
#> initial value 998.131940
#> iter 2 value 809.632558
#> iter 3 value 799.928793
#> iter 4 value 799.041545
#> iter 5 value 763.775590
#> iter 6 value 755.131952
#> iter 7 value 753.611110
#> iter 8 value 753.573484
#> iter 9 value 753.573397
#> iter 10 value 753.573383
#> iter 10 value 753.573376
#> iter 10 value 753.573369
#> final value 753.573369
#> converged
#> This is Run number 378
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.6366927 1.6028180 0.08669266 -10.99718195 1
#> 2 1 -0.95 -2.35 1.6326450 2.1872964 0.68264500 -0.16270357 1
#> 3 1 -6.20 -2.30 0.1648658 -0.2870617 -6.03513422 -2.58706174 2
#> 4 1 -13.90 -2.55 0.6211208 -0.8389696 -13.27887924 -3.38896964 2
#> 5 1 -14.40 -5.80 0.1086370 1.7454727 -14.29136297 -4.05452735 2
#> 6 1 -3.60 -1.70 1.7543899 1.7103005 -1.84561007 0.01030046 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5900 -38450 8125
#> initial value 998.131940
#> iter 2 value 811.211263
#> iter 3 value 795.105425
#> iter 4 value 793.571699
#> iter 5 value 756.627645
#> iter 6 value 748.224357
#> iter 7 value 747.044111
#> iter 8 value 747.025357
#> iter 9 value 747.025339
#> iter 9 value 747.025332
#> iter 9 value 747.025324
#> final value 747.025324
#> converged
#> This is Run number 379
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.4299685 0.3667506 -0.1200315 -12.233249 1
#> 2 1 -0.95 -2.35 0.6316911 0.3922987 -0.3183089 -1.957701 1
#> 3 1 -6.20 -2.30 -0.2325828 0.2415930 -6.4325828 -2.058407 2
#> 4 1 -13.90 -2.55 -0.0566559 0.6890830 -13.9566559 -1.860917 2
#> 5 1 -14.40 -5.80 -0.1040032 1.4518417 -14.5040032 -4.348158 2
#> 6 1 -3.60 -1.70 0.8550014 0.2665985 -2.7449986 -1.433401 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6920 -41625 7525
#> initial value 998.131940
#> iter 2 value 764.397068
#> iter 3 value 747.441781
#> iter 4 value 745.870165
#> iter 5 value 718.539216
#> iter 6 value 710.004995
#> iter 7 value 709.018109
#> iter 8 value 709.000720
#> iter 9 value 709.000705
#> iter 9 value 709.000702
#> iter 9 value 709.000702
#> final value 709.000702
#> converged
#> This is Run number 380
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.9233471 -0.2593132 2.373347 -12.8593132 1
#> 2 1 -0.95 -2.35 2.0873200 2.1207258 1.137320 -0.2292742 1
#> 3 1 -6.20 -2.30 0.9967502 1.6615115 -5.203250 -0.6384885 2
#> 4 1 -13.90 -2.55 -0.4637537 0.8230316 -14.363754 -1.7269684 2
#> 5 1 -14.40 -5.80 1.6764089 0.5599035 -12.723591 -5.2400965 2
#> 6 1 -3.60 -1.70 -0.1407450 -0.1025925 -3.740745 -1.8025925 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6240 -39800 7200
#> initial value 998.131940
#> iter 2 value 796.501366
#> iter 3 value 780.971417
#> iter 4 value 778.392952
#> iter 5 value 745.649741
#> iter 6 value 737.009404
#> iter 7 value 735.798112
#> iter 8 value 735.773603
#> iter 9 value 735.773577
#> iter 9 value 735.773570
#> iter 9 value 735.773565
#> final value 735.773565
#> converged
#> This is Run number 381
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.98134842 2.1886455 -1.531348 -10.41135446 1
#> 2 1 -0.95 -2.35 -0.95216744 -0.1455566 -1.902167 -2.49555657 1
#> 3 1 -6.20 -2.30 -0.69298069 2.2827336 -6.892981 -0.01726645 2
#> 4 1 -13.90 -2.55 0.08347104 0.9776597 -13.816529 -1.57234034 2
#> 5 1 -14.40 -5.80 -0.04771824 -0.3847907 -14.447718 -6.18479073 2
#> 6 1 -3.60 -1.70 1.16966859 2.2530089 -2.430331 0.55300889 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5720 -36125 7525
#> initial value 998.131940
#> iter 2 value 846.520309
#> iter 3 value 836.101753
#> iter 4 value 835.218213
#> iter 5 value 791.396658
#> iter 6 value 783.511009
#> iter 7 value 782.218537
#> iter 8 value 782.196578
#> iter 9 value 782.196545
#> iter 10 value 782.196533
#> iter 10 value 782.196525
#> iter 10 value 782.196520
#> final value 782.196520
#> converged
#> This is Run number 382
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.02408941 -0.3231195 -0.5740894 -12.9231195 1
#> 2 1 -0.95 -2.35 -0.28691271 1.3415195 -1.2369127 -1.0084805 2
#> 3 1 -6.20 -2.30 -0.69591141 0.8037257 -6.8959114 -1.4962743 2
#> 4 1 -13.90 -2.55 0.97163116 2.0660749 -12.9283688 -0.4839251 2
#> 5 1 -14.40 -5.80 2.51790328 1.9915539 -11.8820967 -3.8084461 2
#> 6 1 -3.60 -1.70 0.88624229 -1.9995759 -2.7137577 -3.6995759 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6900 -40700 5975
#> initial value 998.131940
#> iter 2 value 788.075215
#> iter 3 value 776.338320
#> iter 4 value 773.726556
#> iter 5 value 743.491964
#> iter 6 value 734.672884
#> iter 7 value 733.264983
#> iter 8 value 733.226944
#> iter 9 value 733.226852
#> iter 9 value 733.226843
#> iter 9 value 733.226835
#> final value 733.226835
#> converged
#> This is Run number 383
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.4022502 -0.75425242 -0.9522502 -13.354252 1
#> 2 1 -0.95 -2.35 0.6445126 -0.06195407 -0.3054874 -2.411954 1
#> 3 1 -6.20 -2.30 -1.0436236 -0.09434359 -7.2436236 -2.394344 2
#> 4 1 -13.90 -2.55 -0.3128351 0.79290920 -14.2128351 -1.757091 2
#> 5 1 -14.40 -5.80 -1.0383794 0.10552442 -15.4383794 -5.694476 2
#> 6 1 -3.60 -1.70 1.0426777 0.35749799 -2.5573223 -1.342502 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6240 -38400 7300
#> initial value 998.131940
#> iter 2 value 816.854078
#> iter 3 value 804.130658
#> iter 4 value 802.881237
#> iter 5 value 765.561760
#> iter 6 value 757.085971
#> iter 7 value 755.767722
#> iter 8 value 755.741401
#> iter 9 value 755.741362
#> iter 10 value 755.741350
#> iter 10 value 755.741340
#> iter 10 value 755.741334
#> final value 755.741334
#> converged
#> This is Run number 384
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.86016070 2.09920781 0.3101607 -10.5007922 1
#> 2 1 -0.95 -2.35 4.86636467 -0.61936208 3.9163647 -2.9693621 1
#> 3 1 -6.20 -2.30 0.22126184 0.08310593 -5.9787382 -2.2168941 2
#> 4 1 -13.90 -2.55 -1.26723880 1.85423949 -15.1672388 -0.6957605 2
#> 5 1 -14.40 -5.80 0.37560552 2.73209412 -14.0243945 -3.0679059 2
#> 6 1 -3.60 -1.70 0.06485589 1.80668976 -3.5351441 0.1066898 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6060 -38750 6700
#> initial value 998.131940
#> iter 2 value 815.191067
#> iter 3 value 801.930440
#> iter 4 value 799.233029
#> iter 5 value 763.277896
#> iter 6 value 754.720174
#> iter 7 value 753.348200
#> iter 8 value 753.318367
#> iter 9 value 753.318318
#> iter 9 value 753.318309
#> iter 9 value 753.318304
#> final value 753.318304
#> converged
#> This is Run number 385
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.5750582 0.7749512 -1.1250582 -11.825049 1
#> 2 1 -0.95 -2.35 1.7181055 3.5591389 0.7681055 1.209139 2
#> 3 1 -6.20 -2.30 1.8240353 -0.4220063 -4.3759647 -2.722006 2
#> 4 1 -13.90 -2.55 4.0793705 -0.7976963 -9.8206295 -3.347696 2
#> 5 1 -14.40 -5.80 1.7985952 0.8337251 -12.6014048 -4.966275 2
#> 6 1 -3.60 -1.70 -0.7872331 2.6730500 -4.3872331 0.973050 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6340 -37200 7475
#> initial value 998.131940
#> iter 2 value 832.449713
#> iter 3 value 821.863762
#> iter 4 value 821.556165
#> iter 5 value 780.569566
#> iter 6 value 772.343081
#> iter 7 value 771.001017
#> iter 8 value 770.975645
#> iter 9 value 770.975602
#> iter 10 value 770.975587
#> iter 10 value 770.975579
#> iter 10 value 770.975572
#> final value 770.975572
#> converged
#> This is Run number 386
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.5546662 -0.67921366 1.0046662 -13.2792137 1
#> 2 1 -0.95 -2.35 0.4346368 0.01529455 -0.5153632 -2.3347055 1
#> 3 1 -6.20 -2.30 2.4643902 1.98883111 -3.7356098 -0.3111689 2
#> 4 1 -13.90 -2.55 -1.3766436 0.71933013 -15.2766436 -1.8306699 2
#> 5 1 -14.40 -5.80 -1.0012224 1.04021914 -15.4012224 -4.7597809 2
#> 6 1 -3.60 -1.70 -0.6257157 0.14101634 -4.2257157 -1.5589837 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6040 -37725 6400
#> initial value 998.131940
#> iter 2 value 831.381448
#> iter 3 value 820.595030
#> iter 4 value 818.501825
#> iter 5 value 779.408249
#> iter 6 value 771.083088
#> iter 7 value 769.605764
#> iter 8 value 769.573850
#> iter 9 value 769.573788
#> iter 9 value 769.573778
#> iter 9 value 769.573773
#> final value 769.573773
#> converged
#> This is Run number 387
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.1934979 0.5068392 0.6434979 -12.093161 1
#> 2 1 -0.95 -2.35 -0.3887606 0.7939239 -1.3387606 -1.556076 1
#> 3 1 -6.20 -2.30 1.4601304 -0.8008198 -4.7398696 -3.100820 2
#> 4 1 -13.90 -2.55 0.4544119 0.7148145 -13.4455881 -1.835186 2
#> 5 1 -14.40 -5.80 0.9843404 0.2833669 -13.4156596 -5.516633 2
#> 6 1 -3.60 -1.70 -0.5844084 -1.1428747 -4.1844084 -2.842875 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6660 -38875 6375
#> initial value 998.131940
#> iter 2 value 814.618530
#> iter 3 value 804.447411
#> iter 4 value 803.156669
#> iter 5 value 767.082485
#> iter 6 value 758.499976
#> iter 7 value 756.995069
#> iter 8 value 756.959054
#> iter 9 value 756.958975
#> iter 10 value 756.958963
#> iter 10 value 756.958956
#> iter 10 value 756.958954
#> final value 756.958954
#> converged
#> This is Run number 388
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.36159854 -0.61719830 0.8115985 -13.2171983 1
#> 2 1 -0.95 -2.35 -0.06827419 -1.02220040 -1.0182742 -3.3722004 1
#> 3 1 -6.20 -2.30 -1.12219955 -0.95754697 -7.3221995 -3.2575470 2
#> 4 1 -13.90 -2.55 -0.72812885 -0.06459167 -14.6281289 -2.6145917 2
#> 5 1 -14.40 -5.80 0.71409152 -1.03773856 -13.6859085 -6.8377386 2
#> 6 1 -3.60 -1.70 -0.79821620 1.08541548 -4.3982162 -0.6145845 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6720 -39925 6150
#> initial value 998.131940
#> iter 2 value 799.745642
#> iter 3 value 788.312436
#> iter 4 value 786.072679
#> iter 5 value 753.394435
#> iter 6 value 744.643204
#> iter 7 value 743.188895
#> iter 8 value 743.151675
#> iter 9 value 743.151591
#> iter 9 value 743.151581
#> iter 9 value 743.151574
#> final value 743.151574
#> converged
#> This is Run number 389
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.2616386 1.4979140 0.7116386 -11.1020860 1
#> 2 1 -0.95 -2.35 1.2850819 -0.1074828 0.3350819 -2.4574828 1
#> 3 1 -6.20 -2.30 1.0901391 0.6865399 -5.1098609 -1.6134601 2
#> 4 1 -13.90 -2.55 -0.6815610 1.5983537 -14.5815610 -0.9516463 2
#> 5 1 -14.40 -5.80 -0.7099566 0.0504715 -15.1099566 -5.7495285 2
#> 6 1 -3.60 -1.70 2.7168153 1.1040768 -0.8831847 -0.5959232 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6480 -38950 7150
#> initial value 998.131940
#> iter 2 value 809.511573
#> iter 3 value 796.974740
#> iter 4 value 795.840962
#> iter 5 value 760.079997
#> iter 6 value 751.495065
#> iter 7 value 750.168892
#> iter 8 value 750.140925
#> iter 9 value 750.140882
#> iter 10 value 750.140869
#> iter 10 value 750.140859
#> iter 10 value 750.140853
#> final value 750.140853
#> converged
#> This is Run number 390
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.0300587 -0.05836067 0.4800587 -12.6583607 1
#> 2 1 -0.95 -2.35 -0.6573730 1.95293425 -1.6073730 -0.3970657 2
#> 3 1 -6.20 -2.30 1.1908195 1.06384082 -5.0091805 -1.2361592 2
#> 4 1 -13.90 -2.55 0.6757082 -0.30707691 -13.2242918 -2.8570769 2
#> 5 1 -14.40 -5.80 1.3173434 0.29613831 -13.0826566 -5.5038617 2
#> 6 1 -3.60 -1.70 -0.6502400 0.72564662 -4.2502400 -0.9743534 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6840 -39375 6400
#> initial value 998.131940
#> iter 2 value 806.835596
#> iter 3 value 796.471155
#> iter 4 value 795.313944
#> iter 5 value 760.665973
#> iter 6 value 751.992247
#> iter 7 value 750.512155
#> iter 8 value 750.475792
#> iter 9 value 750.475712
#> iter 10 value 750.475700
#> iter 10 value 750.475693
#> iter 10 value 750.475687
#> final value 750.475687
#> converged
#> This is Run number 391
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.1793078 0.0597127 0.6293078 -12.540287 1
#> 2 1 -0.95 -2.35 3.8157788 0.7884374 2.8657788 -1.561563 1
#> 3 1 -6.20 -2.30 1.6935533 0.8035916 -4.5064467 -1.496408 2
#> 4 1 -13.90 -2.55 2.4354232 0.3897652 -11.4645768 -2.160235 2
#> 5 1 -14.40 -5.80 1.9754951 -0.7870454 -12.4245049 -6.587045 2
#> 6 1 -3.60 -1.70 -0.8367366 -0.4017785 -4.4367366 -2.101778 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5700 -36925 6475
#> initial value 998.131940
#> iter 2 value 841.964213
#> iter 3 value 831.073092
#> iter 4 value 828.757340
#> iter 5 value 787.527215
#> iter 6 value 779.419312
#> iter 7 value 777.984234
#> iter 8 value 777.955670
#> iter 9 value 777.955620
#> iter 9 value 777.955611
#> iter 9 value 777.955606
#> final value 777.955606
#> converged
#> This is Run number 392
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.98760318 0.5246833 1.437603 -12.075317 1
#> 2 1 -0.95 -2.35 2.50915485 0.2717297 1.559155 -2.078270 1
#> 3 1 -6.20 -2.30 1.15533925 0.6709925 -5.044661 -1.629008 2
#> 4 1 -13.90 -2.55 -0.32659327 -0.2357859 -14.226593 -2.785786 2
#> 5 1 -14.40 -5.80 1.64875434 1.5635779 -12.751246 -4.236422 2
#> 6 1 -3.60 -1.70 -0.03715614 0.6983324 -3.637156 -1.001668 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6480 -39050 6950
#> initial value 998.131940
#> iter 2 value 809.148236
#> iter 3 value 796.850569
#> iter 4 value 795.466566
#> iter 5 value 760.037556
#> iter 6 value 751.432168
#> iter 7 value 750.078961
#> iter 8 value 750.049374
#> iter 9 value 750.049325
#> iter 10 value 750.049313
#> iter 10 value 750.049304
#> iter 10 value 750.049298
#> final value 750.049298
#> converged
#> This is Run number 393
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.5609193 0.8057181 0.01091932 -11.794282 1
#> 2 1 -0.95 -2.35 -0.2319742 -0.2740095 -1.18197415 -2.624010 1
#> 3 1 -6.20 -2.30 2.6065732 0.3612030 -3.59342683 -1.938797 2
#> 4 1 -13.90 -2.55 -0.1184011 -0.3454797 -14.01840113 -2.895480 2
#> 5 1 -14.40 -5.80 -0.5362941 0.9843056 -14.93629406 -4.815694 2
#> 6 1 -3.60 -1.70 -0.5271261 -0.7200434 -4.12712612 -2.420043 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5900 -37575 5900
#> initial value 998.131940
#> iter 2 value 835.910071
#> iter 3 value 825.124327
#> iter 4 value 822.340933
#> iter 5 value 782.985077
#> iter 6 value 774.678965
#> iter 7 value 773.122856
#> iter 8 value 773.088035
#> iter 9 value 773.087952
#> iter 10 value 773.087940
#> iter 10 value 773.087940
#> iter 10 value 773.087937
#> final value 773.087937
#> converged
#> This is Run number 394
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.87306595 0.7340686 1.323066 -11.8659314 1
#> 2 1 -0.95 -2.35 3.55007143 1.5317993 2.600071 -0.8182007 1
#> 3 1 -6.20 -2.30 1.92309765 -0.6364091 -4.276902 -2.9364091 2
#> 4 1 -13.90 -2.55 0.73380606 1.9614065 -13.166194 -0.5885935 2
#> 5 1 -14.40 -5.80 -0.06800317 2.3975514 -14.468003 -3.4024486 2
#> 6 1 -3.60 -1.70 2.02615738 0.5378184 -1.573843 -1.1621816 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6420 -38350 6475
#> initial value 998.131940
#> iter 2 value 821.954559
#> iter 3 value 811.576562
#> iter 4 value 810.124366
#> iter 5 value 772.601574
#> iter 6 value 764.129285
#> iter 7 value 762.643118
#> iter 8 value 762.609300
#> iter 9 value 762.609230
#> iter 9 value 762.609230
#> iter 9 value 762.609230
#> final value 762.609230
#> converged
#> This is Run number 395
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.5197825 0.2284862 -1.06978247 -12.3715138 1
#> 2 1 -0.95 -2.35 0.9222157 -0.1965568 -0.02778429 -2.5465568 1
#> 3 1 -6.20 -2.30 0.4212002 0.9388130 -5.77879980 -1.3611870 2
#> 4 1 -13.90 -2.55 -0.5108112 0.3571466 -14.41081125 -2.1928534 2
#> 5 1 -14.40 -5.80 0.5565217 0.1597867 -13.84347832 -5.6402133 2
#> 6 1 -3.60 -1.70 0.7062580 2.1187989 -2.89374204 0.4187989 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6700 -39600 6375
#> initial value 998.131940
#> iter 2 value 803.678521
#> iter 3 value 792.391759
#> iter 4 value 790.634522
#> iter 5 value 756.855822
#> iter 6 value 748.150599
#> iter 7 value 746.710049
#> iter 8 value 746.674721
#> iter 9 value 746.674648
#> iter 9 value 746.674637
#> iter 9 value 746.674630
#> final value 746.674630
#> converged
#> This is Run number 396
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.7716232 -0.07867748 0.2216232 -12.678677 1
#> 2 1 -0.95 -2.35 1.2084628 0.55151828 0.2584628 -1.798482 1
#> 3 1 -6.20 -2.30 1.2289188 -0.84870033 -4.9710812 -3.148700 2
#> 4 1 -13.90 -2.55 0.5936138 1.28716332 -13.3063862 -1.262837 2
#> 5 1 -14.40 -5.80 0.7854765 0.07561280 -13.6145235 -5.724387 2
#> 6 1 -3.60 -1.70 -0.8077821 -0.18979441 -4.4077821 -1.889794 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6320 -38550 5950
#> initial value 998.131940
#> iter 2 value 821.700769
#> iter 3 value 811.158228
#> iter 4 value 808.737250
#> iter 5 value 772.053890
#> iter 6 value 763.530926
#> iter 7 value 761.959675
#> iter 8 value 761.921551
#> iter 9 value 761.921456
#> iter 10 value 761.921444
#> iter 10 value 761.921444
#> iter 10 value 761.921440
#> final value 761.921440
#> converged
#> This is Run number 397
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.09800931 0.07762348 -0.6480093 -12.5223765 1
#> 2 1 -0.95 -2.35 -0.71189947 -1.03019867 -1.6618995 -3.3801987 1
#> 3 1 -6.20 -2.30 -0.42530173 0.32014262 -6.6253017 -1.9798574 2
#> 4 1 -13.90 -2.55 1.41832048 1.19219493 -12.4816795 -1.3578051 2
#> 5 1 -14.40 -5.80 0.05305799 0.86979775 -14.3469420 -4.9302023 2
#> 6 1 -3.60 -1.70 -0.51863770 2.55608217 -4.1186377 0.8560822 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6700 -37325 5775
#> initial value 998.131940
#> iter 2 value 839.352210
#> iter 3 value 832.595632
#> iter 4 value 831.896448
#> iter 5 value 791.251158
#> iter 6 value 783.120603
#> iter 7 value 781.427220
#> iter 8 value 781.388647
#> iter 9 value 781.388543
#> iter 9 value 781.388532
#> iter 9 value 781.388527
#> final value 781.388527
#> converged
#> This is Run number 398
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.005288403 2.1169402 -0.5552884 -10.4830598 1
#> 2 1 -0.95 -2.35 -0.472443097 1.5677220 -1.4224431 -0.7822780 2
#> 3 1 -6.20 -2.30 1.991515053 1.9780401 -4.2084849 -0.3219599 2
#> 4 1 -13.90 -2.55 0.630065536 -0.7929014 -13.2699345 -3.3429014 2
#> 5 1 -14.40 -5.80 0.060043352 -0.5819580 -14.3399566 -6.3819580 2
#> 6 1 -3.60 -1.70 1.788968914 0.2464999 -1.8110311 -1.4535001 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6480 -38100 6650
#> initial value 998.131940
#> iter 2 value 824.558933
#> iter 3 value 814.553368
#> iter 4 value 813.575052
#> iter 5 value 775.206284
#> iter 6 value 766.789392
#> iter 7 value 765.316547
#> iter 8 value 765.283844
#> iter 9 value 765.283777
#> iter 10 value 765.283763
#> iter 10 value 765.283753
#> iter 10 value 765.283747
#> final value 765.283747
#> converged
#> This is Run number 399
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.04688664 -1.2120014 -0.5031134 -13.812001 1
#> 2 1 -0.95 -2.35 -0.13104231 1.0593395 -1.0810423 -1.290660 1
#> 3 1 -6.20 -2.30 -0.32275209 -0.4262292 -6.5227521 -2.726229 2
#> 4 1 -13.90 -2.55 0.20126180 -0.2126988 -13.6987382 -2.762699 2
#> 5 1 -14.40 -5.80 0.50840447 -0.2068077 -13.8915955 -6.006808 2
#> 6 1 -3.60 -1.70 -1.41150988 -1.3783189 -5.0115099 -3.078319 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6180 -39400 7425
#> initial value 998.131940
#> iter 2 value 801.363611
#> iter 3 value 785.961565
#> iter 4 value 783.821350
#> iter 5 value 749.788339
#> iter 6 value 741.201845
#> iter 7 value 739.985822
#> iter 8 value 739.962368
#> iter 9 value 739.962345
#> iter 9 value 739.962336
#> iter 9 value 739.962330
#> final value 739.962330
#> converged
#> This is Run number 400
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.2217718 0.20697389 -0.32822816 -12.393026 1
#> 2 1 -0.95 -2.35 1.0128797 -1.03146229 0.06287967 -3.381462 1
#> 3 1 -6.20 -2.30 0.8820241 -1.11248262 -5.31797587 -3.412483 2
#> 4 1 -13.90 -2.55 1.8566836 -0.79412064 -12.04331641 -3.344121 2
#> 5 1 -14.40 -5.80 -0.7138804 -0.27749917 -15.11388043 -6.077499 2
#> 6 1 -3.60 -1.70 3.4019058 0.01002359 -0.19809417 -1.689976 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6200 -38975 6950
#> initial value 998.131940
#> iter 2 value 810.452373
#> iter 3 value 797.032710
#> iter 4 value 794.853280
#> iter 5 value 759.452026
#> iter 6 value 750.870833
#> iter 7 value 749.542047
#> iter 8 value 749.513770
#> iter 9 value 749.513728
#> iter 9 value 749.513718
#> iter 9 value 749.513712
#> final value 749.513712
#> converged
#>
#>
#> ================ ==== === ===== ==== ====== ===== ===== ===== ===== ======== ====
#> \ vars n mean sd median min max range skew kurtosis se
#> ================ ==== === ===== ==== ====== ===== ===== ===== ===== ======== ====
#> est_bpreis 1 400 -0.01 0.00 -0.01 -0.01 0.00 0.01 0.14 -0.09 0.00
#> est_blade 2 400 -0.01 0.00 -0.01 -0.02 -0.01 0.00 -0.01 0.00 0.00
#> est_bwarte 3 400 0.01 0.00 0.01 0.00 0.01 0.01 0.12 -0.21 0.00
#> rob_pval0_bpreis 4 400 0.08 0.14 0.03 0.00 0.89 0.89 3.12 11.56 0.01
#> rob_pval0_blade 5 400 0.00 0.00 0.00 0.00 0.00 0.00 NaN NaN 0.00
#> rob_pval0_bwarte 6 400 0.00 0.00 0.00 0.00 0.02 0.02 12.43 157.23 0.00
#> ================ ==== === ===== ==== ====== ===== ===== ===== ===== ======== ====
#>
#> FALSE TRUE
#> 39.5 60.5
#> 'simple' is deprecated and will be removed in the future. Use 'exact' instead.
#> bcoeff_lookup already exists; skipping modification.
#> Utility function used in simulation, ie the true utility:
#>
#> $u1
#> $u1$v1
#> V.1 ~ bpreis * alt1.x1 + blade * alt1.x2 + bwarte * alt1.x3
#> <environment: 0x5cc5fa59c340>
#>
#> $u1$v2
#> V.2 ~ bpreis * alt2.x1 + blade * alt2.x2 + bwarte * alt2.x3
#> <environment: 0x5cc5ff73c3f8>
#>
#>
#> $u2
#> $u2$v1
#> V.1 ~ bpreis * alt1.x1
#> <environment: 0x5cc5fa47aac8>
#>
#> $u2$v2
#> V.2 ~ bpreis * alt2.x1
#> <environment: 0x5cc602342058>
#> 'destype' is deprecated. Please use 'designtype' instead.
#> New names:
#>
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 3.4067198 2.2592227 1.0567198 -9.9407773 1
#> 2 1 -6.20 -3.90 0.3349690 -0.8642693 -5.8650310 -4.7642693 2
#> 3 1 -14.20 -5.80 1.3866982 1.1314531 -12.8133018 -4.6685469 2
#> 4 1 -2.10 -13.20 0.4485455 0.1741001 -1.6514545 -13.0258999 1
#> 5 1 -1.70 -4.30 0.9047444 0.7390266 -0.7952556 -3.5609734 1
#> 6 1 -6.90 -1.55 -1.0202728 1.2444422 -7.9202728 -0.3055578 2
#>
#>
#> Transformed utility function (type: simple ):
#> [1] "U_1 = @bpreis * $alt1_x1 + @blade * $alt1_x2 + @bwarte * $alt1_x3 ;U_2 = @bpreis * $alt2_x1 + @blade * $alt2_x2 + @bwarte * $alt2_x3 ;"
#> This is Run number 1
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.7319505 0.11444472 -3.0819505 -12.085555 1
#> 2 1 -6.20 -3.90 1.4362204 0.42102585 -4.7637796 -3.478974 2
#> 3 1 -14.20 -5.80 0.6587789 1.32408012 -13.5412211 -4.475920 2
#> 4 1 -2.10 -13.20 2.7182567 0.10518714 0.6182567 -13.094813 1
#> 5 1 -1.70 -4.30 -0.9148015 -0.52089662 -2.6148015 -4.820897 1
#> 6 1 -6.90 -1.55 -1.0560936 -0.01388186 -7.9560936 -1.563882 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4720 -38550 7325
#> initial value 998.131940
#> iter 2 value 825.310412
#> iter 3 value 821.153371
#> iter 4 value 816.651404
#> iter 5 value 770.388073
#> iter 6 value 760.396657
#> iter 7 value 758.911258
#> iter 8 value 758.884143
#> iter 9 value 758.884012
#> iter 10 value 758.883964
#> iter 10 value 758.883961
#> iter 10 value 758.883954
#> final value 758.883954
#> converged
#> This is Run number 2
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.2295296 -0.8751128 -3.5795296 -13.075113 1
#> 2 1 -6.20 -3.90 0.1574216 1.1650507 -6.0425784 -2.734949 2
#> 3 1 -14.20 -5.80 0.5427261 0.5174867 -13.6572739 -5.282513 2
#> 4 1 -2.10 -13.20 -0.2517136 3.6272465 -2.3517136 -9.572754 1
#> 5 1 -1.70 -4.30 0.8085399 -0.6735272 -0.8914601 -4.973527 1
#> 6 1 -6.90 -1.55 -0.5439133 -0.8040005 -7.4439133 -2.354000 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4280 -37750 7575
#> initial value 998.131940
#> iter 2 value 834.994815
#> iter 3 value 830.862279
#> iter 4 value 825.857090
#> iter 5 value 776.264858
#> iter 6 value 766.555380
#> iter 7 value 765.023705
#> iter 8 value 764.998426
#> iter 9 value 764.998337
#> iter 10 value 764.998279
#> iter 10 value 764.998279
#> iter 10 value 764.998275
#> final value 764.998275
#> converged
#> This is Run number 3
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.7322418 3.6273303 -3.0822418 -8.572670 1
#> 2 1 -6.20 -3.90 2.5280089 0.9755771 -3.6719911 -2.924423 2
#> 3 1 -14.20 -5.80 -0.3422426 1.1968711 -14.5422426 -4.603129 2
#> 4 1 -2.10 -13.20 -1.2580096 0.2338313 -3.3580096 -12.966169 1
#> 5 1 -1.70 -4.30 1.1329713 0.1901108 -0.5670287 -4.109889 1
#> 6 1 -6.90 -1.55 -0.6143258 -0.3320346 -7.5143258 -1.882035 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3980 -35800 9850
#> initial value 998.131940
#> iter 2 value 845.231568
#> iter 3 value 824.696946
#> iter 4 value 824.248186
#> iter 5 value 783.361872
#> iter 6 value 776.267336
#> iter 7 value 775.643166
#> iter 8 value 775.621372
#> iter 9 value 775.621110
#> iter 10 value 775.620878
#> iter 11 value 775.620621
#> iter 12 value 775.620511
#> iter 12 value 775.620511
#> iter 12 value 775.620511
#> final value 775.620511
#> converged
#> This is Run number 4
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.1297209 0.52518522 -3.4797209 -11.674815 1
#> 2 1 -6.20 -3.90 2.4520130 1.04414498 -3.7479870 -2.855855 2
#> 3 1 -14.20 -5.80 2.4018497 0.92780739 -11.7981503 -4.872193 2
#> 4 1 -2.10 -13.20 1.5132752 0.59761188 -0.5867248 -12.602388 1
#> 5 1 -1.70 -4.30 1.4571803 0.07054883 -0.2428197 -4.229451 1
#> 6 1 -6.90 -1.55 -0.1447297 3.01532050 -7.0447297 1.465321 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4740 -37775 7100
#> initial value 998.131940
#> iter 2 value 837.590811
#> iter 3 value 834.923861
#> iter 4 value 831.190558
#> iter 5 value 782.541478
#> iter 6 value 772.727586
#> iter 7 value 771.203023
#> iter 8 value 771.173745
#> iter 9 value 771.173710
#> iter 10 value 771.173539
#> iter 10 value 771.173539
#> iter 11 value 771.173507
#> iter 12 value 771.173490
#> iter 12 value 771.173489
#> iter 12 value 771.173486
#> final value 771.173486
#> converged
#> This is Run number 5
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.7052337 -0.01113643 -1.644766 -12.211136 1
#> 2 1 -6.20 -3.90 -0.9929875 1.54859296 -7.192987 -2.351407 2
#> 3 1 -14.20 -5.80 -0.8621834 3.35798866 -15.062183 -2.442011 2
#> 4 1 -2.10 -13.20 0.3661770 1.04306171 -1.733823 -12.156938 1
#> 5 1 -1.70 -4.30 -0.2749495 0.49903110 -1.974949 -3.800969 1
#> 6 1 -6.90 -1.55 1.9017416 0.20376958 -4.998258 -1.346230 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4880 -38025 7525
#> initial value 998.131940
#> iter 2 value 831.778853
#> iter 3 value 830.002808
#> iter 4 value 827.116558
#> iter 5 value 778.357684
#> iter 6 value 768.524369
#> iter 7 value 767.041356
#> iter 8 value 767.013562
#> iter 9 value 767.013261
#> iter 10 value 767.013063
#> iter 10 value 767.013062
#> iter 11 value 767.013045
#> iter 12 value 767.013001
#> iter 12 value 767.013001
#> iter 12 value 767.012999
#> final value 767.012999
#> converged
#> This is Run number 6
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.05385395 -0.6374426 -2.403854 -12.837443 1
#> 2 1 -6.20 -3.90 -0.03725587 -0.4194024 -6.237256 -4.319402 2
#> 3 1 -14.20 -5.80 1.81374075 -0.9260723 -12.386259 -6.726072 2
#> 4 1 -2.10 -13.20 -0.50216610 0.2567539 -2.602166 -12.943246 1
#> 5 1 -1.70 -4.30 0.53083692 0.2043818 -1.169163 -4.095618 1
#> 6 1 -6.90 -1.55 0.39289697 4.4403211 -6.507103 2.890321 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4680 -36175 8200
#> initial value 998.131940
#> iter 2 value 852.431655
#> iter 3 value 838.279037
#> iter 4 value 837.676018
#> iter 5 value 795.711241
#> iter 6 value 787.815682
#> iter 7 value 786.665519
#> iter 8 value 786.628507
#> iter 9 value 786.627917
#> iter 10 value 786.627731
#> iter 11 value 786.627493
#> iter 12 value 786.627347
#> iter 12 value 786.627347
#> iter 12 value 786.627347
#> final value 786.627347
#> converged
#> This is Run number 7
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.2145506 -0.9101014 -2.135449 -13.1101014 1
#> 2 1 -6.20 -3.90 0.5533264 1.9511195 -5.646674 -1.9488805 2
#> 3 1 -14.20 -5.80 -1.1585438 0.6832981 -15.358544 -5.1167019 2
#> 4 1 -2.10 -13.20 -0.6593329 0.2395157 -2.759333 -12.9604843 1
#> 5 1 -1.70 -4.30 -0.3714403 -0.1176897 -2.071440 -4.4176897 1
#> 6 1 -6.90 -1.55 0.5245958 1.2349465 -6.375404 -0.3150535 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3880 -37175 7875
#> initial value 998.131940
#> iter 2 value 840.717972
#> iter 3 value 836.460799
#> iter 4 value 830.879941
#> iter 5 value 778.615877
#> iter 6 value 769.152550
#> iter 7 value 767.574797
#> iter 8 value 767.551216
#> iter 8 value 767.551216
#> final value 767.551216
#> converged
#> This is Run number 8
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.2892283 0.7829595 -2.639228 -11.417040 1
#> 2 1 -6.20 -3.90 0.9495775 -0.9723260 -5.250423 -4.872326 2
#> 3 1 -14.20 -5.80 0.1064353 2.1516768 -14.093565 -3.648323 2
#> 4 1 -2.10 -13.20 0.5013370 2.0012226 -1.598663 -11.198777 1
#> 5 1 -1.70 -4.30 0.1789177 0.9749531 -1.521082 -3.325047 1
#> 6 1 -6.90 -1.55 1.2743899 1.7829220 -5.625610 0.232922 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4260 -37125 7300
#> initial value 998.131940
#> iter 2 value 845.078792
#> iter 3 value 841.817304
#> iter 4 value 837.254910
#> iter 5 value 785.962000
#> iter 6 value 776.408451
#> iter 7 value 774.862606
#> iter 8 value 774.836293
#> iter 9 value 774.836222
#> iter 10 value 774.836169
#> iter 10 value 774.836168
#> iter 10 value 774.836160
#> final value 774.836160
#> converged
#> This is Run number 9
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.6909745 1.0868451 -3.040974 -11.1131549 1
#> 2 1 -6.20 -3.90 0.1503257 3.1449802 -6.049674 -0.7550198 2
#> 3 1 -14.20 -5.80 -0.9296206 -0.4196626 -15.129621 -6.2196626 2
#> 4 1 -2.10 -13.20 0.1293581 2.2839048 -1.970642 -10.9160952 1
#> 5 1 -1.70 -4.30 -0.3476424 1.2378285 -2.047642 -3.0621715 1
#> 6 1 -6.90 -1.55 0.7593131 -0.4419187 -6.140687 -1.9919187 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3920 -35800 9050
#> initial value 998.131940
#> iter 2 value 851.001999
#> iter 3 value 832.983518
#> iter 4 value 831.764257
#> iter 5 value 789.120672
#> iter 6 value 781.686178
#> iter 7 value 780.796413
#> iter 8 value 780.764223
#> iter 9 value 780.763688
#> iter 10 value 780.763551
#> iter 11 value 780.763385
#> iter 12 value 780.763273
#> iter 12 value 780.763273
#> iter 12 value 780.763273
#> final value 780.763273
#> converged
#> This is Run number 10
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.2878232 0.21470560 -2.637823 -11.985294 1
#> 2 1 -6.20 -3.90 0.1954157 1.81243376 -6.004584 -2.087566 2
#> 3 1 -14.20 -5.80 -0.5789778 0.40708226 -14.778978 -5.392918 2
#> 4 1 -2.10 -13.20 4.2857778 -0.36017762 2.185778 -13.560178 1
#> 5 1 -1.70 -4.30 -0.2196795 1.76443561 -1.919679 -2.535564 1
#> 6 1 -6.90 -1.55 0.4892240 -0.06706601 -6.410776 -1.617066 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4380 -37275 9275
#> initial value 998.131940
#> iter 2 value 830.624563
#> iter 3 value 812.196231
#> iter 4 value 811.384449
#> iter 5 value 771.887319
#> iter 6 value 764.075665
#> iter 7 value 763.246978
#> iter 8 value 763.209214
#> iter 9 value 763.208609
#> iter 10 value 763.208327
#> iter 11 value 763.208033
#> iter 12 value 763.207960
#> iter 12 value 763.207960
#> iter 12 value 763.207960
#> final value 763.207960
#> converged
#> This is Run number 11
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.3936919 -0.2443918 -1.956308 -12.444392 1
#> 2 1 -6.20 -3.90 -0.2718327 0.0466080 -6.471833 -3.853392 2
#> 3 1 -14.20 -5.80 -1.2377716 1.1402276 -15.437772 -4.659772 2
#> 4 1 -2.10 -13.20 4.3819161 -1.0371597 2.281916 -14.237160 1
#> 5 1 -1.70 -4.30 0.6550745 -0.3523469 -1.044925 -4.652347 1
#> 6 1 -6.90 -1.55 0.3616460 0.2859499 -6.538354 -1.264050 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4200 -38250 8450
#> initial value 998.131940
#> iter 2 value 822.511961
#> iter 3 value 818.363656
#> iter 4 value 813.532954
#> iter 5 value 763.923355
#> iter 6 value 754.322033
#> iter 7 value 752.769627
#> iter 8 value 752.746351
#> iter 9 value 752.746276
#> iter 10 value 752.746118
#> iter 10 value 752.746115
#> iter 10 value 752.746107
#> final value 752.746107
#> converged
#> This is Run number 12
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.1565560 4.2978838 -0.1934440 -7.9021162 1
#> 2 1 -6.20 -3.90 0.7194092 2.1767754 -5.4805908 -1.7232246 2
#> 3 1 -14.20 -5.80 2.1606670 -0.5126003 -12.0393330 -6.3126003 2
#> 4 1 -2.10 -13.20 -1.1897251 1.7594412 -3.2897251 -11.4405588 1
#> 5 1 -1.70 -4.30 1.0239231 0.6546142 -0.6760769 -3.6453858 1
#> 6 1 -6.90 -1.55 -1.1935798 0.6107404 -8.0935798 -0.9392596 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4440 -37700 8225
#> initial value 998.131940
#> iter 2 value 831.903199
#> iter 3 value 830.115835
#> iter 4 value 826.780464
#> iter 5 value 775.391236
#> iter 6 value 765.828773
#> iter 7 value 764.307418
#> iter 8 value 764.283799
#> iter 9 value 764.283629
#> iter 10 value 764.283507
#> iter 10 value 764.283503
#> iter 11 value 764.283458
#> iter 12 value 764.283374
#> iter 12 value 764.283368
#> iter 12 value 764.283368
#> final value 764.283368
#> converged
#> This is Run number 13
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.4740991 2.02404962 -2.824099 -10.175950 1
#> 2 1 -6.20 -3.90 1.5845029 0.28002640 -4.615497 -3.619974 2
#> 3 1 -14.20 -5.80 1.2377882 -0.70639653 -12.962212 -6.506397 2
#> 4 1 -2.10 -13.20 -0.4920876 0.49082851 -2.592088 -12.709171 1
#> 5 1 -1.70 -4.30 -0.4617310 0.04827574 -2.161731 -4.251724 1
#> 6 1 -6.90 -1.55 0.8715223 -1.29838773 -6.028478 -2.848388 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4700 -38850 8950
#> initial value 998.131940
#> iter 2 value 810.750095
#> iter 3 value 808.118962
#> iter 4 value 805.642437
#> iter 5 value 756.871744
#> iter 6 value 747.251102
#> iter 7 value 745.713749
#> iter 8 value 745.690615
#> iter 9 value 745.690413
#> iter 10 value 745.690210
#> iter 10 value 745.690205
#> iter 11 value 745.690171
#> iter 12 value 745.690157
#> iter 12 value 745.690154
#> iter 13 value 745.690139
#> iter 14 value 745.690127
#> iter 14 value 745.690125
#> iter 14 value 745.690125
#> final value 745.690125
#> converged
#> This is Run number 14
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.42455157 0.1152696 -1.9254484 -12.0847304 1
#> 2 1 -6.20 -3.90 0.08346348 0.8884457 -6.1165365 -3.0115543 2
#> 3 1 -14.20 -5.80 1.20013917 -0.4530278 -12.9998608 -6.2530278 2
#> 4 1 -2.10 -13.20 1.98972840 1.0847762 -0.1102716 -12.1152238 1
#> 5 1 -1.70 -4.30 0.11247627 0.5792154 -1.5875237 -3.7207846 1
#> 6 1 -6.90 -1.55 1.57090220 2.2902244 -5.3290978 0.7402244 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4420 -37350 8125
#> initial value 998.131940
#> iter 2 value 837.328108
#> iter 3 value 836.166848
#> iter 4 value 833.010943
#> iter 5 value 780.564460
#> iter 6 value 771.081929
#> iter 7 value 769.561564
#> iter 8 value 769.537529
#> iter 9 value 769.537244
#> iter 10 value 769.537120
#> iter 10 value 769.537111
#> iter 10 value 769.537100
#> final value 769.537100
#> converged
#> This is Run number 15
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.1918681 3.4090631 -2.1581319 -8.790937 1
#> 2 1 -6.20 -3.90 -0.2645194 0.3125024 -6.4645194 -3.587498 2
#> 3 1 -14.20 -5.80 0.4719808 2.2698821 -13.7280192 -3.530118 2
#> 4 1 -2.10 -13.20 -1.0987583 0.1187937 -3.1987583 -13.081206 1
#> 5 1 -1.70 -4.30 1.8079772 0.7633315 0.1079772 -3.536669 1
#> 6 1 -6.90 -1.55 2.1257787 -0.5221384 -4.7742213 -2.072138 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5040 -38075 8325
#> initial value 998.131940
#> iter 2 value 826.242674
#> iter 3 value 826.003131
#> iter 4 value 824.636608
#> iter 5 value 774.324871
#> iter 6 value 764.580289
#> iter 7 value 763.074809
#> iter 8 value 763.049968
#> iter 9 value 763.049748
#> iter 10 value 763.049634
#> iter 11 value 763.049606
#> iter 12 value 763.049274
#> iter 12 value 763.049274
#> iter 12 value 763.049274
#> final value 763.049274
#> converged
#> This is Run number 16
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.2651461 -0.4113575 -1.084854 -12.6113575 1
#> 2 1 -6.20 -3.90 1.3529913 1.5229075 -4.847009 -2.3770925 2
#> 3 1 -14.20 -5.80 0.3084988 0.5483560 -13.891501 -5.2516440 2
#> 4 1 -2.10 -13.20 0.5304605 -0.1648219 -1.569540 -13.3648219 1
#> 5 1 -1.70 -4.30 -0.2476335 0.8715403 -1.947633 -3.4284597 1
#> 6 1 -6.90 -1.55 0.9365203 0.5906034 -5.963480 -0.9593966 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4680 -36300 7650
#> initial value 998.131940
#> iter 2 value 854.173206
#> iter 3 value 841.432938
#> iter 4 value 840.281623
#> iter 5 value 797.653485
#> iter 6 value 789.628204
#> iter 7 value 788.153963
#> iter 8 value 788.102437
#> iter 9 value 788.101627
#> iter 10 value 788.101449
#> iter 11 value 788.101237
#> iter 12 value 788.101099
#> iter 12 value 788.101099
#> iter 12 value 788.101099
#> final value 788.101099
#> converged
#> This is Run number 17
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 6.1638485 0.4776054 3.8138485 -11.722395 1
#> 2 1 -6.20 -3.90 1.2891821 -0.9421834 -4.9108179 -4.842183 2
#> 3 1 -14.20 -5.80 0.8159298 0.2965880 -13.3840702 -5.503412 2
#> 4 1 -2.10 -13.20 0.4088749 1.7626748 -1.6911251 -11.437325 1
#> 5 1 -1.70 -4.30 1.8168295 0.1880587 0.1168295 -4.111941 1
#> 6 1 -6.90 -1.55 1.8250701 0.3183898 -5.0749299 -1.231610 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5020 -37950 7550
#> initial value 998.131940
#> iter 2 value 832.727257
#> iter 3 value 831.725068
#> iter 4 value 829.475310
#> iter 5 value 780.350914
#> iter 6 value 770.524082
#> iter 7 value 769.038864
#> iter 8 value 769.009817
#> iter 9 value 769.009538
#> iter 10 value 769.009427
#> iter 11 value 769.009414
#> iter 12 value 769.009110
#> iter 12 value 769.009110
#> iter 12 value 769.009110
#> final value 769.009110
#> converged
#> This is Run number 18
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.1713109 0.2794148 -3.521311 -11.920585 1
#> 2 1 -6.20 -3.90 0.2835647 1.1816846 -5.916435 -2.718315 2
#> 3 1 -14.20 -5.80 1.0865846 0.1951784 -13.113415 -5.604822 2
#> 4 1 -2.10 -13.20 -0.3939160 -0.3043081 -2.493916 -13.504308 1
#> 5 1 -1.70 -4.30 -0.1644935 -1.0311772 -1.864494 -5.331177 1
#> 6 1 -6.90 -1.55 3.4643930 4.2741223 -3.435607 2.724122 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4020 -35600 8675
#> initial value 998.131940
#> iter 2 value 856.112219
#> iter 3 value 839.539953
#> iter 4 value 838.313043
#> iter 5 value 795.027697
#> iter 6 value 787.528633
#> iter 7 value 786.523255
#> iter 8 value 786.489326
#> iter 9 value 786.488773
#> iter 10 value 786.488629
#> iter 11 value 786.488467
#> iter 12 value 786.488360
#> iter 12 value 786.488360
#> iter 12 value 786.488360
#> final value 786.488360
#> converged
#> This is Run number 19
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.37400935 -0.7450607 -3.724009 -12.945061 1
#> 2 1 -6.20 -3.90 -0.08352759 1.0874457 -6.283528 -2.812554 2
#> 3 1 -14.20 -5.80 1.40145401 -0.1174018 -12.798546 -5.917402 2
#> 4 1 -2.10 -13.20 -1.51563727 1.3599491 -3.615637 -11.840051 1
#> 5 1 -1.70 -4.30 0.44860060 0.3905686 -1.251399 -3.909431 1
#> 6 1 -6.90 -1.55 0.27158974 -0.6420536 -6.628410 -2.192054 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5260 -40225 8050
#> initial value 998.131940
#> iter 2 value 795.676754
#> iter 3 value 791.303413
#> iter 4 value 788.323962
#> iter 5 value 746.513628
#> iter 6 value 736.518658
#> iter 7 value 735.141203
#> iter 8 value 735.117266
#> iter 9 value 735.117056
#> iter 10 value 735.116628
#> iter 11 value 735.116609
#> iter 12 value 735.116474
#> iter 12 value 735.116474
#> iter 12 value 735.116474
#> final value 735.116474
#> converged
#> This is Run number 20
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.2144009 -0.86481610 -2.564401 -13.064816 1
#> 2 1 -6.20 -3.90 -1.3853106 -1.65350286 -7.585311 -5.553503 2
#> 3 1 -14.20 -5.80 0.1451558 -0.52504721 -14.054844 -6.325047 2
#> 4 1 -2.10 -13.20 0.8084614 -0.03173075 -1.291539 -13.231731 1
#> 5 1 -1.70 -4.30 0.6589040 -0.11177173 -1.041096 -4.411772 1
#> 6 1 -6.90 -1.55 -0.6975627 0.45258704 -7.597563 -1.097413 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4780 -36250 7250
#> initial value 998.131940
#> iter 2 value 857.111653
#> iter 3 value 845.559907
#> iter 4 value 844.274380
#> iter 5 value 801.199265
#> iter 6 value 793.157004
#> iter 7 value 791.458031
#> iter 8 value 791.398462
#> iter 9 value 791.397571
#> iter 10 value 791.397401
#> iter 11 value 791.397189
#> iter 12 value 791.397055
#> iter 12 value 791.397055
#> iter 12 value 791.397055
#> final value 791.397055
#> converged
#> This is Run number 21
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.3703675 1.1503162 0.02036752 -11.049684 1
#> 2 1 -6.20 -3.90 1.4733011 1.4447841 -4.72669887 -2.455216 2
#> 3 1 -14.20 -5.80 0.7403851 -0.5302634 -13.45961492 -6.330263 2
#> 4 1 -2.10 -13.20 -0.4780235 6.3332672 -2.57802349 -6.866733 1
#> 5 1 -1.70 -4.30 -0.8151027 -1.4223288 -2.51510272 -5.722329 1
#> 6 1 -6.90 -1.55 2.0824132 0.1129708 -4.81758677 -1.437029 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4580 -36925 8150
#> initial value 998.131940
#> iter 2 value 842.977619
#> iter 3 value 828.454046
#> iter 4 value 827.179798
#> iter 5 value 785.975479
#> iter 6 value 777.816126
#> iter 7 value 776.551710
#> iter 8 value 776.502040
#> iter 9 value 776.501156
#> iter 10 value 776.500984
#> iter 11 value 776.500800
#> iter 12 value 776.500657
#> iter 12 value 776.500657
#> iter 12 value 776.500657
#> final value 776.500657
#> converged
#> This is Run number 22
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.6900697 1.0958959 -1.659930 -11.104104 1
#> 2 1 -6.20 -3.90 1.1771276 5.0803128 -5.022872 1.180313 2
#> 3 1 -14.20 -5.80 1.5275729 3.5040715 -12.672427 -2.295928 2
#> 4 1 -2.10 -13.20 0.7674494 3.1030246 -1.332551 -10.096975 1
#> 5 1 -1.70 -4.30 0.4678916 2.6639779 -1.232108 -1.636022 1
#> 6 1 -6.90 -1.55 3.8644370 0.2558699 -3.035563 -1.294130 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4640 -36125 8275
#> initial value 998.131940
#> iter 2 value 852.575541
#> iter 3 value 838.159059
#> iter 4 value 837.565116
#> iter 5 value 795.577382
#> iter 6 value 787.719425
#> iter 7 value 786.603611
#> iter 8 value 786.567932
#> iter 9 value 786.567363
#> iter 10 value 786.567180
#> iter 11 value 786.566944
#> iter 12 value 786.566801
#> iter 12 value 786.566801
#> iter 12 value 786.566801
#> final value 786.566801
#> converged
#> This is Run number 23
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 3.0696373 0.1139559 0.71963728 -12.0860441 1
#> 2 1 -6.20 -3.90 1.0380117 0.2643139 -5.16198826 -3.6356861 2
#> 3 1 -14.20 -5.80 1.7228809 -1.4468334 -12.47711905 -7.2468334 2
#> 4 1 -2.10 -13.20 -0.8658669 1.3431095 -2.96586694 -11.8568905 1
#> 5 1 -1.70 -4.30 1.6014845 -0.7574144 -0.09851551 -5.0574144 1
#> 6 1 -6.90 -1.55 0.4443535 1.3386907 -6.45564646 -0.2113093 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4920 -36525 7425
#> initial value 998.131940
#> iter 2 value 852.647158
#> iter 3 value 840.822601
#> iter 4 value 839.848203
#> iter 5 value 797.714440
#> iter 6 value 789.572769
#> iter 7 value 787.985914
#> iter 8 value 787.930145
#> iter 9 value 787.929278
#> iter 10 value 787.929083
#> iter 11 value 787.928838
#> iter 12 value 787.928683
#> iter 12 value 787.928683
#> iter 12 value 787.928683
#> final value 787.928683
#> converged
#> This is Run number 24
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.5480181 -0.67530780 -1.801982 -12.8753078 1
#> 2 1 -6.20 -3.90 -1.0115325 0.78782907 -7.211533 -3.1121709 2
#> 3 1 -14.20 -5.80 -0.9401809 -0.05642427 -15.140181 -5.8564243 2
#> 4 1 -2.10 -13.20 0.5216900 2.68799285 -1.578310 -10.5120072 1
#> 5 1 -1.70 -4.30 0.2058140 0.81199836 -1.494186 -3.4880016 1
#> 6 1 -6.90 -1.55 0.4105592 1.16010664 -6.489441 -0.3898934 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3080 -36275 10075
#> initial value 998.131940
#> iter 2 value 836.322535
#> iter 3 value 812.585895
#> iter 4 value 809.787675
#> iter 5 value 766.755092
#> iter 6 value 759.803512
#> iter 7 value 759.018700
#> iter 8 value 758.977637
#> iter 9 value 758.977188
#> iter 10 value 758.977159
#> iter 11 value 758.977123
#> iter 12 value 758.977079
#> iter 12 value 758.977079
#> iter 12 value 758.977079
#> final value 758.977079
#> converged
#> This is Run number 25
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.3893017 1.9209584 -2.7393017 -10.279042 1
#> 2 1 -6.20 -3.90 1.2374886 -0.7597671 -4.9625114 -4.659767 2
#> 3 1 -14.20 -5.80 4.4373183 -0.1483760 -9.7626817 -5.948376 2
#> 4 1 -2.10 -13.20 0.2997054 0.4157365 -1.8002946 -12.784263 1
#> 5 1 -1.70 -4.30 0.9823897 1.3023428 -0.7176103 -2.997657 1
#> 6 1 -6.90 -1.55 -1.5504738 -0.3523872 -8.4504738 -1.902387 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4040 -37375 8550
#> initial value 998.131940
#> iter 2 value 833.958960
#> iter 3 value 831.711247
#> iter 4 value 827.450521
#> iter 5 value 774.246051
#> iter 6 value 764.880122
#> iter 7 value 763.297352
#> iter 8 value 763.274864
#> iter 9 value 763.274804
#> iter 10 value 763.274618
#> iter 10 value 763.274615
#> iter 10 value 763.274606
#> final value 763.274606
#> converged
#> This is Run number 26
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.007008881 1.4549374 -2.357009 -10.745063 1
#> 2 1 -6.20 -3.90 1.374385934 0.9222580 -4.825614 -2.977742 2
#> 3 1 -14.20 -5.80 -0.567117601 -0.6089608 -14.767118 -6.408961 2
#> 4 1 -2.10 -13.20 1.012107501 0.5314781 -1.087892 -12.668522 1
#> 5 1 -1.70 -4.30 -0.603949880 0.5813597 -2.303950 -3.718640 1
#> 6 1 -6.90 -1.55 -1.102216774 -1.4307725 -8.002217 -2.980772 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4520 -36500 8750
#> initial value 998.131940
#> iter 2 value 844.621456
#> iter 3 value 828.440266
#> iter 4 value 827.832743
#> iter 5 value 786.851474
#> iter 6 value 779.002893
#> iter 7 value 778.056973
#> iter 8 value 778.023430
#> iter 9 value 778.022858
#> iter 10 value 778.022675
#> iter 11 value 778.022422
#> iter 12 value 778.022265
#> iter 12 value 778.022265
#> iter 12 value 778.022265
#> final value 778.022265
#> converged
#> This is Run number 27
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.6862357 -0.37731581 0.3362357 -12.577316 1
#> 2 1 -6.20 -3.90 2.6588761 0.66005481 -3.5411239 -3.239945 2
#> 3 1 -14.20 -5.80 2.5184884 0.55342696 -11.6815116 -5.246573 2
#> 4 1 -2.10 -13.20 -0.2629038 -0.02022635 -2.3629038 -13.220226 1
#> 5 1 -1.70 -4.30 -0.2897550 -0.73905191 -1.9897550 -5.039052 1
#> 6 1 -6.90 -1.55 -0.4053292 -0.42239065 -7.3053292 -1.972391 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4020 -36350 9100
#> initial value 998.131940
#> iter 2 value 843.798578
#> iter 3 value 825.580600
#> iter 4 value 824.305292
#> iter 5 value 782.554496
#> iter 6 value 774.951378
#> iter 7 value 774.052306
#> iter 8 value 774.016304
#> iter 9 value 774.015690
#> iter 10 value 774.015651
#> iter 11 value 774.015475
#> iter 12 value 774.015252
#> iter 12 value 774.015252
#> iter 12 value 774.015252
#> final value 774.015252
#> converged
#> This is Run number 28
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 3.2749799 -0.66467520 0.9249799 -12.864675 1
#> 2 1 -6.20 -3.90 0.2139321 1.34579503 -5.9860679 -2.554205 2
#> 3 1 -14.20 -5.80 1.3861520 -0.46153021 -12.8138480 -6.261530 2
#> 4 1 -2.10 -13.20 0.1806948 0.01678434 -1.9193052 -13.183216 1
#> 5 1 -1.70 -4.30 1.8833165 2.67416799 0.1833165 -1.625832 1
#> 6 1 -6.90 -1.55 -0.2887903 3.10945865 -7.1887903 1.559459 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3840 -38475 8975
#> initial value 998.131940
#> iter 2 value 815.369378
#> iter 3 value 809.337321
#> iter 4 value 803.065800
#> iter 5 value 753.511607
#> iter 6 value 744.059730
#> iter 7 value 742.411057
#> iter 8 value 742.384355
#> iter 9 value 742.384262
#> iter 10 value 742.384231
#> iter 10 value 742.384229
#> iter 10 value 742.384229
#> final value 742.384229
#> converged
#> This is Run number 29
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.37262927 0.8670987 -2.722629 -11.3329013 1
#> 2 1 -6.20 -3.90 -0.06000197 0.6706381 -6.260002 -3.2293619 2
#> 3 1 -14.20 -5.80 0.43856037 0.6647895 -13.761440 -5.1352105 2
#> 4 1 -2.10 -13.20 -0.15682800 1.9586036 -2.256828 -11.2413964 1
#> 5 1 -1.70 -4.30 -0.49391714 0.8200100 -2.193917 -3.4799900 1
#> 6 1 -6.90 -1.55 -0.55802445 1.1719655 -7.458024 -0.3780345 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5380 -36850 7750
#> initial value 998.131940
#> iter 2 value 846.514471
#> iter 3 value 834.496451
#> iter 4 value 834.347603
#> iter 5 value 793.886815
#> iter 6 value 785.600122
#> iter 7 value 784.307860
#> iter 8 value 784.267126
#> iter 9 value 784.266542
#> iter 10 value 784.266343
#> iter 11 value 784.266059
#> iter 12 value 784.265883
#> iter 12 value 784.265883
#> iter 12 value 784.265883
#> final value 784.265883
#> converged
#> This is Run number 30
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.6983266 -0.5606535377 -0.65167343 -12.7606535 1
#> 2 1 -6.20 -3.90 2.3454175 -0.0003949978 -3.85458251 -3.9003950 1
#> 3 1 -14.20 -5.80 -0.7683467 0.7140527393 -14.96834665 -5.0859473 2
#> 4 1 -2.10 -13.20 2.0763598 -0.3413050988 -0.02364018 -13.5413051 1
#> 5 1 -1.70 -4.30 1.5126180 -0.0308160859 -0.18738200 -4.3308161 1
#> 6 1 -6.90 -1.55 0.2978253 0.6158008780 -6.60217471 -0.9341991 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4780 -37775 8550
#> initial value 998.131940
#> iter 2 value 828.934527
#> iter 3 value 828.821765
#> iter 4 value 827.122455
#> iter 5 value 775.196756
#> iter 6 value 765.608540
#> iter 7 value 764.078088
#> iter 8 value 764.054801
#> iter 9 value 764.054682
#> iter 10 value 764.054357
#> iter 11 value 764.054334
#> iter 12 value 764.054225
#> iter 12 value 764.054225
#> iter 12 value 764.054225
#> final value 764.054225
#> converged
#> This is Run number 31
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.2038101 0.2988100 -2.1461899 -11.901190 1
#> 2 1 -6.20 -3.90 0.6150782 0.3541169 -5.5849218 -3.545883 2
#> 3 1 -14.20 -5.80 0.2087358 0.6498554 -13.9912642 -5.150145 2
#> 4 1 -2.10 -13.20 1.9292007 -0.3884696 -0.1707993 -13.588470 1
#> 5 1 -1.70 -4.30 1.1095214 0.4415471 -0.5904786 -3.858453 1
#> 6 1 -6.90 -1.55 -0.2764128 0.3636535 -7.1764128 -1.186347 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4380 -36475 7675
#> initial value 998.131940
#> iter 2 value 851.615752
#> iter 3 value 851.513373
#> iter 4 value 848.587435
#> iter 5 value 794.120244
#> iter 6 value 784.881649
#> iter 7 value 783.377746
#> iter 8 value 783.352192
#> iter 9 value 783.352018
#> iter 10 value 783.351926
#> iter 10 value 783.351920
#> iter 11 value 783.351860
#> iter 12 value 783.351750
#> iter 12 value 783.351740
#> iter 12 value 783.351740
#> final value 783.351740
#> converged
#> This is Run number 32
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.6395857 -0.2143965 0.2895857 -12.4143965 1
#> 2 1 -6.20 -3.90 1.5886761 0.3125212 -4.6113239 -3.5874788 2
#> 3 1 -14.20 -5.80 -0.2723993 -1.5754728 -14.4723993 -7.3754728 2
#> 4 1 -2.10 -13.20 0.7339479 0.2318166 -1.3660521 -12.9681834 1
#> 5 1 -1.70 -4.30 -1.0516375 -0.4357972 -2.7516375 -4.7357972 1
#> 6 1 -6.90 -1.55 -1.2416690 0.7184026 -8.1416690 -0.8315974 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4780 -37325 7875
#> initial value 998.131940
#> iter 2 value 839.381605
#> iter 3 value 839.322146
#> iter 4 value 837.224483
#> iter 5 value 785.205412
#> iter 6 value 775.641244
#> iter 7 value 774.138505
#> iter 8 value 774.111379
#> iter 9 value 774.111017
#> iter 10 value 774.110810
#> iter 11 value 774.110772
#> iter 12 value 774.110691
#> iter 12 value 774.110691
#> iter 12 value 774.110691
#> final value 774.110691
#> converged
#> This is Run number 33
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.62198172 0.1192210 -0.7280183 -12.0807790 1
#> 2 1 -6.20 -3.90 0.69146605 1.0669748 -5.5085339 -2.8330252 2
#> 3 1 -14.20 -5.80 -0.39009408 -1.2766655 -14.5900941 -7.0766655 2
#> 4 1 -2.10 -13.20 4.35295631 0.5151864 2.2529563 -12.6848136 1
#> 5 1 -1.70 -4.30 0.02659975 1.8254432 -1.6734002 -2.4745568 1
#> 6 1 -6.90 -1.55 0.05662132 1.2343851 -6.8433787 -0.3156149 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3700 -36225 9200
#> initial value 998.131940
#> iter 2 value 844.355446
#> iter 3 value 825.144004
#> iter 4 value 823.217247
#> iter 5 value 780.588481
#> iter 6 value 773.101934
#> iter 7 value 772.179943
#> iter 8 value 772.141053
#> iter 9 value 772.140421
#> iter 9 value 772.140414
#> iter 9 value 772.140414
#> final value 772.140414
#> converged
#> This is Run number 34
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.4804763 0.4996805 -1.869524 -11.700319 1
#> 2 1 -6.20 -3.90 2.3704964 0.3812655 -3.829504 -3.518735 2
#> 3 1 -14.20 -5.80 2.3940746 -0.6394105 -11.805925 -6.439410 2
#> 4 1 -2.10 -13.20 -1.0328887 -0.4851286 -3.132889 -13.685129 1
#> 5 1 -1.70 -4.30 0.2677072 0.2764882 -1.432293 -4.023512 1
#> 6 1 -6.90 -1.55 -0.7486153 3.0485042 -7.648615 1.498504 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5100 -36250 7850
#> initial value 998.131940
#> iter 2 value 853.707124
#> iter 3 value 841.193921
#> iter 4 value 840.951064
#> iter 5 value 799.274498
#> iter 6 value 791.252344
#> iter 7 value 789.996333
#> iter 8 value 789.959274
#> iter 9 value 789.958762
#> iter 10 value 789.958582
#> iter 11 value 789.958330
#> iter 12 value 789.958182
#> iter 12 value 789.958182
#> iter 12 value 789.958182
#> final value 789.958182
#> converged
#> This is Run number 35
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.63579675 1.14568509 -1.714203 -11.054315 1
#> 2 1 -6.20 -3.90 -0.39858372 0.93945936 -6.598584 -2.960541 2
#> 3 1 -14.20 -5.80 2.26660274 -0.28238476 -11.933397 -6.082385 2
#> 4 1 -2.10 -13.20 0.58755458 -0.18785251 -1.512445 -13.387853 1
#> 5 1 -1.70 -4.30 -0.08175432 -0.05879871 -1.781754 -4.358799 1
#> 6 1 -6.90 -1.55 -0.80715466 -0.41908850 -7.707155 -1.969089 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5360 -37400 7925
#> initial value 998.131940
#> iter 2 value 838.104587
#> iter 3 value 825.407234
#> iter 4 value 825.180447
#> iter 5 value 785.864212
#> iter 6 value 777.414587
#> iter 7 value 776.189367
#> iter 8 value 776.145791
#> iter 9 value 776.145065
#> iter 10 value 776.144837
#> iter 11 value 776.144521
#> iter 12 value 776.144313
#> iter 12 value 776.144313
#> iter 12 value 776.144313
#> final value 776.144313
#> converged
#> This is Run number 36
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.3561211 0.01237756 -0.9938789 -12.187622 1
#> 2 1 -6.20 -3.90 -0.2871143 -0.02079995 -6.4871143 -3.920800 2
#> 3 1 -14.20 -5.80 4.2980215 -0.86093094 -9.9019785 -6.660931 2
#> 4 1 -2.10 -13.20 -0.2549352 1.25937829 -2.3549352 -11.940622 1
#> 5 1 -1.70 -4.30 0.5772472 0.54639164 -1.1227528 -3.753608 1
#> 6 1 -6.90 -1.55 2.0653982 -0.04400445 -4.8346018 -1.594004 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6020 -38500 6525
#> initial value 998.131940
#> iter 2 value 830.150507
#> iter 3 value 830.081442
#> iter 4 value 829.188354
#> iter 5 value 784.046956
#> iter 6 value 773.884648
#> iter 7 value 772.250724
#> iter 8 value 772.205243
#> iter 9 value 772.204970
#> iter 10 value 772.204546
#> iter 11 value 772.204522
#> iter 12 value 772.204406
#> iter 12 value 772.204406
#> iter 12 value 772.204406
#> final value 772.204406
#> converged
#> This is Run number 37
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.1310102 2.0336062685 -1.218990 -10.166394 1
#> 2 1 -6.20 -3.90 0.2290076 0.7067515962 -5.970992 -3.193248 2
#> 3 1 -14.20 -5.80 0.6564241 -0.0004879638 -13.543576 -5.800488 2
#> 4 1 -2.10 -13.20 0.9035120 0.2765372028 -1.196488 -12.923463 1
#> 5 1 -1.70 -4.30 0.4558847 0.4893635150 -1.244115 -3.810636 1
#> 6 1 -6.90 -1.55 1.0354170 -0.9631780882 -5.864583 -2.513178 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5180 -37700 7675
#> initial value 998.131940
#> iter 2 value 835.502991
#> iter 3 value 823.054663
#> iter 4 value 822.210782
#> iter 5 value 782.851450
#> iter 6 value 774.302289
#> iter 7 value 772.851316
#> iter 8 value 772.792130
#> iter 9 value 772.791057
#> iter 10 value 772.790842
#> iter 11 value 772.790589
#> iter 12 value 772.790395
#> iter 12 value 772.790395
#> iter 12 value 772.790395
#> final value 772.790395
#> converged
#> This is Run number 38
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.42817501 -0.39894103 -1.921825 -12.598941 1
#> 2 1 -6.20 -3.90 0.08118998 -0.61713647 -6.118810 -4.517136 2
#> 3 1 -14.20 -5.80 1.44285357 -0.46523310 -12.757146 -6.265233 2
#> 4 1 -2.10 -13.20 1.58995603 1.55947203 -0.510044 -11.640528 1
#> 5 1 -1.70 -4.30 -0.84971510 0.09245052 -2.549715 -4.207549 1
#> 6 1 -6.90 -1.55 0.91764723 -0.40349353 -5.982353 -1.953494 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4600 -38100 8125
#> initial value 998.131940
#> iter 2 value 827.007267
#> iter 3 value 824.771711
#> iter 4 value 821.509992
#> iter 5 value 771.786435
#> iter 6 value 762.086876
#> iter 7 value 760.587735
#> iter 8 value 760.563641
#> iter 9 value 760.563446
#> iter 10 value 760.563308
#> iter 10 value 760.563307
#> iter 11 value 760.563260
#> iter 12 value 760.563160
#> iter 12 value 760.563152
#> iter 12 value 760.563147
#> final value 760.563147
#> converged
#> This is Run number 39
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.2293600 -0.8876553 -2.579360 -13.0876553 1
#> 2 1 -6.20 -3.90 0.1966103 -1.5463738 -6.003390 -5.4463738 2
#> 3 1 -14.20 -5.80 0.9458235 1.0368767 -13.254176 -4.7631233 2
#> 4 1 -2.10 -13.20 -0.1769461 -0.4227397 -2.276946 -13.6227397 1
#> 5 1 -1.70 -4.30 2.1118930 -1.1196273 0.411893 -5.4196273 1
#> 6 1 -6.90 -1.55 1.6798599 2.0891961 -5.220140 0.5391961 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4440 -36475 7875
#> initial value 998.131940
#> iter 2 value 850.472860
#> iter 3 value 836.593603
#> iter 4 value 834.978310
#> iter 5 value 792.391997
#> iter 6 value 784.338409
#> iter 7 value 782.926301
#> iter 8 value 782.873361
#> iter 9 value 782.872499
#> iter 10 value 782.872352
#> iter 11 value 782.872204
#> iter 12 value 782.872090
#> iter 12 value 782.872090
#> iter 12 value 782.872090
#> final value 782.872090
#> converged
#> This is Run number 40
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.31330943 -0.3917061 -2.0366906 -12.591706 1
#> 2 1 -6.20 -3.90 -0.44968319 -1.0152068 -6.6496832 -4.915207 2
#> 3 1 -14.20 -5.80 -0.02694603 -0.4131738 -14.2269460 -6.213174 2
#> 4 1 -2.10 -13.20 -0.10255449 0.2843361 -2.2025545 -12.915664 1
#> 5 1 -1.70 -4.30 1.10133148 0.2175302 -0.5986685 -4.082470 1
#> 6 1 -6.90 -1.55 2.80880255 3.1015288 -4.0911974 1.551529 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5140 -37975 8325
#> initial value 998.131940
#> iter 2 value 827.660966
#> iter 3 value 813.281188
#> iter 4 value 812.793716
#> iter 5 value 774.601260
#> iter 6 value 766.120791
#> iter 7 value 765.030252
#> iter 8 value 764.983758
#> iter 9 value 764.982875
#> iter 10 value 764.982820
#> iter 11 value 764.982504
#> iter 12 value 764.982111
#> iter 12 value 764.982111
#> iter 12 value 764.982111
#> final value 764.982111
#> converged
#> This is Run number 41
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.8336767 1.2926512 -3.1836767 -10.9073488 1
#> 2 1 -6.20 -3.90 -0.7142264 0.4934506 -6.9142264 -3.4065494 2
#> 3 1 -14.20 -5.80 -0.6275591 1.1206589 -14.8275591 -4.6793411 2
#> 4 1 -2.10 -13.20 -0.5123700 0.9882496 -2.6123700 -12.2117504 1
#> 5 1 -1.70 -4.30 0.7354067 -0.8042403 -0.9645933 -5.1042403 1
#> 6 1 -6.90 -1.55 3.1833829 1.4034197 -3.7166171 -0.1465803 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4840 -37450 8450
#> initial value 998.131940
#> iter 2 value 834.093070
#> iter 3 value 819.014869
#> iter 4 value 818.316519
#> iter 5 value 778.865009
#> iter 6 value 770.598512
#> iter 7 value 769.521666
#> iter 8 value 769.477576
#> iter 9 value 769.476753
#> iter 9 value 769.476744
#> iter 9 value 769.476744
#> final value 769.476744
#> converged
#> This is Run number 42
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.7388208 3.9251731 -3.088821 -8.274827 1
#> 2 1 -6.20 -3.90 0.2972668 0.9915603 -5.902733 -2.908440 2
#> 3 1 -14.20 -5.80 -0.2661600 2.7051783 -14.466160 -3.094822 2
#> 4 1 -2.10 -13.20 0.7131473 0.3559195 -1.386853 -12.844081 1
#> 5 1 -1.70 -4.30 0.4587632 0.4930344 -1.241237 -3.806966 1
#> 6 1 -6.90 -1.55 2.3611070 0.4555440 -4.538893 -1.094456 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5280 -37300 7450
#> initial value 998.131940
#> iter 2 value 842.276553
#> iter 3 value 830.720991
#> iter 4 value 830.082702
#> iter 5 value 789.905678
#> iter 6 value 781.456213
#> iter 7 value 779.905338
#> iter 8 value 779.847309
#> iter 9 value 779.846348
#> iter 10 value 779.846121
#> iter 11 value 779.845832
#> iter 12 value 779.845637
#> iter 12 value 779.845637
#> iter 12 value 779.845637
#> final value 779.845637
#> converged
#> This is Run number 43
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 3.3392590 -0.17314272 0.989259 -12.3731427 1
#> 2 1 -6.20 -3.90 -0.4092820 2.90145662 -6.609282 -0.9985434 2
#> 3 1 -14.20 -5.80 3.0993024 -0.23225518 -11.100698 -6.0322552 2
#> 4 1 -2.10 -13.20 -0.6871393 0.32581572 -2.787139 -12.8741843 1
#> 5 1 -1.70 -4.30 -1.3140607 -0.32474045 -3.014061 -4.6247404 1
#> 6 1 -6.90 -1.55 -0.5506818 0.00384525 -7.450682 -1.5461548 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5100 -37375 7450
#> initial value 998.131940
#> iter 2 value 841.260581
#> iter 3 value 829.359060
#> iter 4 value 828.302067
#> iter 5 value 787.962052
#> iter 6 value 779.502699
#> iter 7 value 777.899749
#> iter 8 value 777.836301
#> iter 9 value 777.835217
#> iter 10 value 777.835018
#> iter 11 value 777.834785
#> iter 12 value 777.834613
#> iter 12 value 777.834613
#> iter 12 value 777.834613
#> final value 777.834613
#> converged
#> This is Run number 44
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.0561136 0.7667949 -1.293886 -11.4332051 1
#> 2 1 -6.20 -3.90 0.2904447 3.4802587 -5.909555 -0.4197413 2
#> 3 1 -14.20 -5.80 0.5007030 0.4527343 -13.699297 -5.3472657 2
#> 4 1 -2.10 -13.20 -1.0622565 -0.4565755 -3.162257 -13.6565755 1
#> 5 1 -1.70 -4.30 -0.4197725 -0.4633292 -2.119772 -4.7633292 1
#> 6 1 -6.90 -1.55 0.5183234 5.1021769 -6.381677 3.5521769 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4220 -36000 7525
#> initial value 998.131940
#> iter 2 value 858.408517
#> iter 3 value 858.371355
#> iter 4 value 855.211237
#> iter 5 value 799.505498
#> iter 6 value 790.456593
#> iter 7 value 788.959034
#> iter 8 value 788.934299
#> iter 9 value 788.934229
#> iter 10 value 788.934008
#> iter 10 value 788.934007
#> iter 11 value 788.933975
#> iter 12 value 788.933914
#> iter 12 value 788.933906
#> iter 12 value 788.933904
#> final value 788.933904
#> converged
#> This is Run number 45
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.9770879 -0.5331898 -1.372912 -12.733190 1
#> 2 1 -6.20 -3.90 0.6188149 0.9935593 -5.581185 -2.906441 2
#> 3 1 -14.20 -5.80 1.3031484 -1.2303248 -12.896852 -7.030325 2
#> 4 1 -2.10 -13.20 -0.3870820 0.6134700 -2.487082 -12.586530 1
#> 5 1 -1.70 -4.30 3.4573002 -0.2934759 1.757300 -4.593476 1
#> 6 1 -6.90 -1.55 0.5435977 -0.9309058 -6.356402 -2.480906 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3940 -35400 8500
#> initial value 998.131940
#> iter 2 value 859.622019
#> iter 3 value 843.478845
#> iter 4 value 842.025135
#> iter 5 value 797.994798
#> iter 6 value 790.526816
#> iter 7 value 789.448592
#> iter 8 value 789.412644
#> iter 9 value 789.412079
#> iter 10 value 789.411946
#> iter 11 value 789.411806
#> iter 12 value 789.411711
#> iter 12 value 789.411711
#> iter 12 value 789.411711
#> final value 789.411711
#> converged
#> This is Run number 46
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 8.0946745 -0.39534642 5.744674 -12.5953464 1
#> 2 1 -6.20 -3.90 -0.5413074 -0.28762967 -6.741307 -4.1876297 2
#> 3 1 -14.20 -5.80 -1.1400700 -0.04888199 -15.340070 -5.8488820 2
#> 4 1 -2.10 -13.20 -0.1074818 -0.90853832 -2.207482 -14.1085383 1
#> 5 1 -1.70 -4.30 0.0373976 2.65389998 -1.662602 -1.6461000 2
#> 6 1 -6.90 -1.55 -0.5826485 2.44500364 -7.482649 0.8950036 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5380 -39325 7275
#> initial value 998.131940
#> iter 2 value 814.218426
#> iter 3 value 811.497369
#> iter 4 value 808.803130
#> iter 5 value 765.139770
#> iter 6 value 754.925747
#> iter 7 value 753.508775
#> iter 8 value 753.480105
#> iter 9 value 753.479719
#> iter 10 value 753.479677
#> iter 10 value 753.479676
#> iter 11 value 753.479640
#> iter 12 value 753.479513
#> iter 12 value 753.479509
#> iter 13 value 753.479496
#> iter 13 value 753.479494
#> iter 13 value 753.479493
#> final value 753.479493
#> converged
#> This is Run number 47
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.0046455 -1.1623668 -3.3546455 -13.362367 1
#> 2 1 -6.20 -3.90 0.7514134 0.5142024 -5.4485866 -3.385798 2
#> 3 1 -14.20 -5.80 0.3465487 0.6153043 -13.8534513 -5.184696 2
#> 4 1 -2.10 -13.20 1.2504921 -0.1115016 -0.8495079 -13.311502 1
#> 5 1 -1.70 -4.30 -0.5127211 1.5830428 -2.2127211 -2.716957 1
#> 6 1 -6.90 -1.55 1.7555586 3.1278597 -5.1444414 1.577860 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4840 -37475 8425
#> initial value 998.131940
#> iter 2 value 833.913655
#> iter 3 value 818.897168
#> iter 4 value 818.163935
#> iter 5 value 778.717338
#> iter 6 value 770.436612
#> iter 7 value 769.345531
#> iter 8 value 769.300585
#> iter 9 value 769.299742
#> iter 9 value 769.299735
#> iter 9 value 769.299735
#> final value 769.299735
#> converged
#> This is Run number 48
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.79058067 0.7202817 -3.140581 -11.479718 1
#> 2 1 -6.20 -3.90 0.79204040 0.1129894 -5.407960 -3.787011 2
#> 3 1 -14.20 -5.80 0.85399183 1.5300737 -13.346008 -4.269926 2
#> 4 1 -2.10 -13.20 -0.22768638 0.8309363 -2.327686 -12.369064 1
#> 5 1 -1.70 -4.30 6.26732611 0.9631317 4.567326 -3.336868 1
#> 6 1 -6.90 -1.55 0.04578162 -0.3114252 -6.854218 -1.861425 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4940 -37925 7775
#> initial value 998.131940
#> iter 2 value 831.743323
#> iter 3 value 830.815168
#> iter 4 value 828.595191
#> iter 5 value 778.903110
#> iter 6 value 769.127999
#> iter 7 value 767.642800
#> iter 8 value 767.615278
#> iter 9 value 767.614868
#> iter 10 value 767.614679
#> iter 11 value 767.614657
#> iter 12 value 767.614570
#> iter 12 value 767.614570
#> iter 12 value 767.614570
#> final value 767.614570
#> converged
#> This is Run number 49
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.30682651 0.3126437 -0.04317349 -11.887356 1
#> 2 1 -6.20 -3.90 2.62194660 1.4702864 -3.57805340 -2.429714 2
#> 3 1 -14.20 -5.80 0.24474927 0.6753785 -13.95525073 -5.124621 2
#> 4 1 -2.10 -13.20 2.46406130 -0.7541648 0.36406130 -13.954165 1
#> 5 1 -1.70 -4.30 -1.48412757 0.5572091 -3.18412757 -3.742791 1
#> 6 1 -6.90 -1.55 -0.09641577 -0.1128043 -6.99641577 -1.662804 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4360 -36500 8225
#> initial value 998.131940
#> iter 2 value 847.947902
#> iter 3 value 832.956590
#> iter 4 value 831.500810
#> iter 5 value 789.306615
#> iter 6 value 781.326888
#> iter 7 value 780.088309
#> iter 8 value 780.041383
#> iter 9 value 780.040579
#> iter 10 value 780.040424
#> iter 11 value 780.040266
#> iter 12 value 780.040144
#> iter 12 value 780.040144
#> iter 12 value 780.040144
#> final value 780.040144
#> converged
#> This is Run number 50
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.703579024 -0.9510993 -0.646421 -13.1510993 1
#> 2 1 -6.20 -3.90 -0.008326799 0.7815381 -6.208327 -3.1184619 2
#> 3 1 -14.20 -5.80 0.808150589 0.6003857 -13.391849 -5.1996143 2
#> 4 1 -2.10 -13.20 -0.136086526 2.4637606 -2.236087 -10.7362394 1
#> 5 1 -1.70 -4.30 -0.305163828 1.7509572 -2.005164 -2.5490428 1
#> 6 1 -6.90 -1.55 0.185886476 1.2428984 -6.714114 -0.3071016 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4140 -36400 8475
#> initial value 998.131940
#> iter 2 value 847.474333
#> iter 3 value 831.355690
#> iter 4 value 829.675559
#> iter 5 value 787.199726
#> iter 6 value 779.339296
#> iter 7 value 778.186698
#> iter 8 value 778.141966
#> iter 9 value 778.141201
#> iter 10 value 778.141066
#> iter 11 value 778.140938
#> iter 12 value 778.140833
#> iter 12 value 778.140833
#> iter 12 value 778.140833
#> final value 778.140833
#> converged
#> This is Run number 51
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.98194900 0.50973468 -1.368051 -11.6902653 1
#> 2 1 -6.20 -3.90 -0.36553577 1.50277704 -6.565536 -2.3972230 2
#> 3 1 -14.20 -5.80 -0.14931099 3.59693518 -14.349311 -2.2030648 2
#> 4 1 -2.10 -13.20 0.19822848 0.40146056 -1.901772 -12.7985394 1
#> 5 1 -1.70 -4.30 -0.03639585 -0.01177724 -1.736396 -4.3117772 1
#> 6 1 -6.90 -1.55 1.22512314 2.53600584 -5.674877 0.9860058 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4560 -37200 7875
#> initial value 998.131940
#> iter 2 value 840.973282
#> iter 3 value 840.327073
#> iter 4 value 837.556467
#> iter 5 value 785.121194
#> iter 6 value 775.628088
#> iter 7 value 774.122135
#> iter 8 value 774.096429
#> iter 9 value 774.096090
#> iter 10 value 774.095952
#> iter 11 value 774.095939
#> iter 12 value 774.095864
#> iter 12 value 774.095864
#> iter 12 value 774.095864
#> final value 774.095864
#> converged
#> This is Run number 52
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.1222335 -0.52915171 -2.227766 -12.729152 1
#> 2 1 -6.20 -3.90 2.1135934 -0.06660978 -4.086407 -3.966610 2
#> 3 1 -14.20 -5.80 3.1754112 0.68444905 -11.024589 -5.115551 2
#> 4 1 -2.10 -13.20 -0.6841028 -0.63325480 -2.784103 -13.833255 1
#> 5 1 -1.70 -4.30 0.1287893 0.18839710 -1.571211 -4.111603 1
#> 6 1 -6.90 -1.55 -0.6705420 4.97460520 -7.570542 3.424605 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3280 -36875 10200
#> initial value 998.131940
#> iter 2 value 827.826419
#> iter 3 value 827.302910
#> iter 4 value 822.101520
#> iter 5 value 762.706874
#> iter 6 value 753.782524
#> iter 7 value 751.925158
#> iter 8 value 751.886775
#> iter 9 value 751.886733
#> iter 9 value 751.886730
#> iter 9 value 751.886730
#> final value 751.886730
#> converged
#> This is Run number 53
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.74947912 0.01250242 0.3994791 -12.187498 1
#> 2 1 -6.20 -3.90 -1.09408501 -0.40845736 -7.2940850 -4.308457 2
#> 3 1 -14.20 -5.80 0.06814824 1.81261473 -14.1318518 -3.987385 2
#> 4 1 -2.10 -13.20 -1.26604008 0.31517105 -3.3660401 -12.884829 1
#> 5 1 -1.70 -4.30 0.91460636 0.73359870 -0.7853936 -3.566401 1
#> 6 1 -6.90 -1.55 0.15480907 -0.24158386 -6.7451909 -1.791584 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4420 -39025 8400
#> initial value 998.131940
#> iter 2 value 811.658210
#> iter 3 value 806.453678
#> iter 4 value 801.548884
#> iter 5 value 754.974336
#> iter 6 value 745.234252
#> iter 7 value 743.727283
#> iter 8 value 743.703415
#> iter 9 value 743.703300
#> iter 10 value 743.703145
#> iter 10 value 743.703135
#> iter 10 value 743.703135
#> final value 743.703135
#> converged
#> This is Run number 54
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.51372700 0.7989452 -1.836273 -11.401055 1
#> 2 1 -6.20 -3.90 0.40590012 1.2053960 -5.794100 -2.694604 2
#> 3 1 -14.20 -5.80 0.08897046 -1.0653002 -14.111030 -6.865300 2
#> 4 1 -2.10 -13.20 -1.52647558 1.1804794 -3.626476 -12.019521 1
#> 5 1 -1.70 -4.30 0.39127006 -1.2260929 -1.308730 -5.526093 1
#> 6 1 -6.90 -1.55 0.39037691 -0.2882428 -6.509623 -1.838243 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4720 -37775 7750
#> initial value 998.131940
#> iter 2 value 833.915055
#> iter 3 value 832.381270
#> iter 4 value 829.449940
#> iter 5 value 779.331643
#> iter 6 value 769.624438
#> iter 7 value 768.133087
#> iter 8 value 768.106738
#> iter 9 value 768.106386
#> iter 10 value 768.106287
#> iter 10 value 768.106283
#> iter 11 value 768.106257
#> iter 12 value 768.106184
#> iter 12 value 768.106181
#> iter 12 value 768.106178
#> final value 768.106178
#> converged
#> This is Run number 55
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.19327923 1.2215320 -1.156721 -10.978468 1
#> 2 1 -6.20 -3.90 2.26838942 2.4169136 -3.931611 -1.483086 2
#> 3 1 -14.20 -5.80 -0.24473387 0.2727369 -14.444734 -5.527263 2
#> 4 1 -2.10 -13.20 -0.12440643 2.5800021 -2.224406 -10.619998 1
#> 5 1 -1.70 -4.30 -0.09188671 0.7590902 -1.791887 -3.540910 1
#> 6 1 -6.90 -1.55 1.54910607 -0.2135422 -5.350894 -1.763542 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5180 -36200 7100
#> initial value 998.131940
#> iter 2 value 858.622824
#> iter 3 value 848.148348
#> iter 4 value 847.561718
#> iter 5 value 804.901921
#> iter 6 value 796.871217
#> iter 7 value 795.165635
#> iter 8 value 795.111488
#> iter 9 value 795.110742
#> iter 10 value 795.110534
#> iter 11 value 795.110246
#> iter 12 value 795.110089
#> iter 12 value 795.110089
#> iter 12 value 795.110089
#> final value 795.110089
#> converged
#> This is Run number 56
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.06679665 -1.01650683 -2.2832034 -13.216507 1
#> 2 1 -6.20 -3.90 2.70837623 0.11359293 -3.4916238 -3.786407 1
#> 3 1 -14.20 -5.80 0.28956855 0.05244931 -13.9104315 -5.747551 2
#> 4 1 -2.10 -13.20 -1.13139743 0.46590643 -3.2313974 -12.734094 1
#> 5 1 -1.70 -4.30 1.33135036 -0.03279888 -0.3686496 -4.332799 1
#> 6 1 -6.90 -1.55 0.11170111 4.15743107 -6.7882989 2.607431 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4660 -38025 7450
#> initial value 998.131940
#> iter 2 value 832.112239
#> iter 3 value 829.148075
#> iter 4 value 825.252427
#> iter 5 value 776.771792
#> iter 6 value 766.944614
#> iter 7 value 765.448549
#> iter 8 value 765.421769
#> iter 9 value 765.421556
#> iter 10 value 765.421506
#> iter 10 value 765.421505
#> iter 11 value 765.421488
#> iter 12 value 765.421438
#> iter 12 value 765.421436
#> iter 12 value 765.421433
#> final value 765.421433
#> converged
#> This is Run number 57
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.9152459 1.3086786 -3.265246 -10.891321 1
#> 2 1 -6.20 -3.90 2.2545075 0.1260269 -3.945493 -3.773973 2
#> 3 1 -14.20 -5.80 -0.5405821 0.3233013 -14.740582 -5.476699 2
#> 4 1 -2.10 -13.20 -0.3358695 0.7498803 -2.435869 -12.450120 1
#> 5 1 -1.70 -4.30 0.3615463 -0.3853142 -1.338454 -4.685314 1
#> 6 1 -6.90 -1.55 2.2002336 3.1676627 -4.699766 1.617663 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4880 -38100 7675
#> initial value 998.131940
#> iter 2 value 829.847077
#> iter 3 value 828.143604
#> iter 4 value 825.385899
#> iter 5 value 776.562955
#> iter 6 value 766.735330
#> iter 7 value 765.257041
#> iter 8 value 765.229984
#> iter 9 value 765.229607
#> iter 10 value 765.229485
#> iter 10 value 765.229482
#> iter 11 value 765.229457
#> iter 12 value 765.229382
#> iter 12 value 765.229379
#> iter 12 value 765.229376
#> final value 765.229376
#> converged
#> This is Run number 58
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.2239443 0.2591357 -2.126056 -11.940864 1
#> 2 1 -6.20 -3.90 -0.7100291 0.4965561 -6.910029 -3.403444 2
#> 3 1 -14.20 -5.80 1.0560323 3.0649659 -13.143968 -2.735034 2
#> 4 1 -2.10 -13.20 0.8632542 -1.1615996 -1.236746 -14.361600 1
#> 5 1 -1.70 -4.30 -0.8380725 1.4809453 -2.538073 -2.819055 1
#> 6 1 -6.90 -1.55 0.6282001 -0.7188565 -6.271800 -2.268857 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5500 -38750 8350
#> initial value 998.131940
#> iter 2 value 816.307454
#> iter 3 value 815.876855
#> iter 4 value 815.276526
#> iter 5 value 767.540077
#> iter 6 value 757.583179
#> iter 7 value 756.097847
#> iter 8 value 756.073573
#> iter 9 value 756.073407
#> iter 10 value 756.073027
#> iter 11 value 756.072947
#> iter 12 value 756.072815
#> iter 12 value 756.072815
#> iter 12 value 756.072815
#> final value 756.072815
#> converged
#> This is Run number 59
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.2413716 1.6783906 -2.5913716 -10.5216094 1
#> 2 1 -6.20 -3.90 2.1052818 0.4999755 -4.0947182 -3.4000245 2
#> 3 1 -14.20 -5.80 -1.2109782 0.1597809 -15.4109782 -5.6402191 2
#> 4 1 -2.10 -13.20 1.2620759 0.8817886 -0.8379241 -12.3182114 1
#> 5 1 -1.70 -4.30 0.1492418 0.3312733 -1.5507582 -3.9687267 1
#> 6 1 -6.90 -1.55 -0.6768452 1.7362861 -7.5768452 0.1862861 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4540 -36425 8025
#> initial value 998.131940
#> iter 2 value 850.264790
#> iter 3 value 836.220121
#> iter 4 value 835.042206
#> iter 5 value 792.855482
#> iter 6 value 784.847363
#> iter 7 value 783.548253
#> iter 8 value 783.501353
#> iter 9 value 783.500569
#> iter 10 value 783.500395
#> iter 11 value 783.500198
#> iter 12 value 783.500062
#> iter 12 value 783.500062
#> iter 12 value 783.500062
#> final value 783.500062
#> converged
#> This is Run number 60
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.9403374 -0.89843536 -3.2903374 -13.098435 1
#> 2 1 -6.20 -3.90 1.8100131 0.31054109 -4.3899869 -3.589459 2
#> 3 1 -14.20 -5.80 0.9700724 1.04086594 -13.2299276 -4.759134 2
#> 4 1 -2.10 -13.20 1.3108147 -1.35465609 -0.7891853 -14.554656 1
#> 5 1 -1.70 -4.30 0.2377307 -0.90326217 -1.4622693 -5.203262 1
#> 6 1 -6.90 -1.55 0.1550381 -0.02513497 -6.7449619 -1.575135 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4960 -38325 7325
#> initial value 998.131940
#> iter 2 value 828.659437
#> iter 3 value 826.252404
#> iter 4 value 823.062892
#> iter 5 value 775.813092
#> iter 6 value 765.858210
#> iter 7 value 764.379274
#> iter 8 value 764.350739
#> iter 9 value 764.350501
#> iter 10 value 764.350336
#> iter 10 value 764.350335
#> iter 11 value 764.350313
#> iter 12 value 764.350279
#> iter 12 value 764.350279
#> iter 12 value 764.350276
#> final value 764.350276
#> converged
#> This is Run number 61
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.3606790 -0.4836395 -1.989321 -12.683639 1
#> 2 1 -6.20 -3.90 1.2360164 0.7274717 -4.963984 -3.172528 2
#> 3 1 -14.20 -5.80 -0.9873912 1.0959163 -15.187391 -4.704084 2
#> 4 1 -2.10 -13.20 -0.2012224 -0.6221022 -2.301222 -13.822102 1
#> 5 1 -1.70 -4.30 3.5924705 1.9395643 1.892470 -2.360436 1
#> 6 1 -6.90 -1.55 -1.0628638 -0.5837008 -7.962864 -2.133701 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5520 -39450 7900
#> initial value 998.131940
#> iter 2 value 808.652731
#> iter 3 value 806.755819
#> iter 4 value 805.322503
#> iter 5 value 760.821745
#> iter 6 value 750.710600
#> iter 7 value 749.295291
#> iter 8 value 749.269313
#> iter 9 value 749.268939
#> iter 10 value 749.268759
#> iter 11 value 749.268731
#> iter 12 value 749.268411
#> iter 12 value 749.268411
#> iter 12 value 749.268411
#> final value 749.268411
#> converged
#> This is Run number 62
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.05554581 -0.1883352 -2.2944542 -12.388335 1
#> 2 1 -6.20 -3.90 2.14079827 -0.6942596 -4.0592017 -4.594260 1
#> 3 1 -14.20 -5.80 1.67514876 -0.2747328 -12.5248512 -6.074733 2
#> 4 1 -2.10 -13.20 -0.67376439 0.9152453 -2.7737644 -12.284755 1
#> 5 1 -1.70 -4.30 1.26531454 0.3944486 -0.4346855 -3.905551 1
#> 6 1 -6.90 -1.55 -0.47477404 -0.6525285 -7.3747740 -2.202529 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4260 -36750 7500
#> initial value 998.131940
#> iter 2 value 848.946136
#> iter 3 value 847.155311
#> iter 4 value 843.271386
#> iter 5 value 790.199813
#> iter 6 value 780.830378
#> iter 7 value 779.307465
#> iter 8 value 779.282190
#> iter 9 value 779.282056
#> iter 10 value 779.281946
#> iter 10 value 779.281946
#> iter 11 value 779.281922
#> iter 12 value 779.281904
#> iter 12 value 779.281904
#> iter 12 value 779.281900
#> final value 779.281900
#> converged
#> This is Run number 63
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.7049117 0.83650472 -1.6450883 -11.3634953 1
#> 2 1 -6.20 -3.90 1.2413823 3.14874439 -4.9586177 -0.7512556 2
#> 3 1 -14.20 -5.80 0.7515753 0.04476255 -13.4484247 -5.7552375 2
#> 4 1 -2.10 -13.20 1.7082685 -0.60583605 -0.3917315 -13.8058361 1
#> 5 1 -1.70 -4.30 0.9144838 1.33293480 -0.7855162 -2.9670652 1
#> 6 1 -6.90 -1.55 3.3565398 0.87857828 -3.5434602 -0.6714217 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4840 -38200 9225
#> initial value 998.131940
#> iter 2 value 818.311397
#> iter 3 value 818.072991
#> iter 4 value 816.931939
#> iter 5 value 765.113829
#> iter 6 value 755.550308
#> iter 7 value 753.984050
#> iter 8 value 753.962499
#> iter 9 value 753.962267
#> iter 10 value 753.962114
#> iter 10 value 753.962114
#> iter 11 value 753.962069
#> iter 11 value 753.962066
#> iter 12 value 753.962053
#> iter 12 value 753.962046
#> iter 12 value 753.962046
#> final value 753.962046
#> converged
#> This is Run number 64
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.74224034 1.1042593 -1.607760 -11.095741 1
#> 2 1 -6.20 -3.90 0.11250293 -0.8977172 -6.087497 -4.797717 2
#> 3 1 -14.20 -5.80 -0.40348622 0.4970745 -14.603486 -5.302926 2
#> 4 1 -2.10 -13.20 0.08981291 -0.4154599 -2.010187 -13.615460 1
#> 5 1 -1.70 -4.30 1.34411399 0.1835940 -0.355886 -4.116406 1
#> 6 1 -6.90 -1.55 2.38868673 -0.2847194 -4.511313 -1.834719 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5000 -39175 7900
#> initial value 998.131940
#> iter 2 value 812.819943
#> iter 3 value 809.516865
#> iter 4 value 806.380262
#> iter 5 value 761.021080
#> iter 6 value 751.033668
#> iter 7 value 749.602087
#> iter 8 value 749.577446
#> iter 9 value 749.577327
#> iter 10 value 749.576927
#> iter 10 value 749.576924
#> iter 11 value 749.576868
#> iter 12 value 749.576841
#> iter 12 value 749.576835
#> iter 12 value 749.576835
#> final value 749.576835
#> converged
#> This is Run number 65
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.08691641 -0.02878832 -2.26308359 -12.228788 1
#> 2 1 -6.20 -3.90 -0.91774016 1.34660555 -7.11774016 -2.553394 2
#> 3 1 -14.20 -5.80 1.37308501 -0.23456203 -12.82691499 -6.034562 2
#> 4 1 -2.10 -13.20 0.18093148 1.44403306 -1.91906852 -11.755967 1
#> 5 1 -1.70 -4.30 1.71474876 2.58269500 0.01474876 -1.717305 1
#> 6 1 -6.90 -1.55 0.20839467 -0.28189139 -6.69160533 -1.831891 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4040 -36825 8375
#> initial value 998.131940
#> iter 2 value 842.480456
#> iter 3 value 841.443751
#> iter 4 value 837.639787
#> iter 5 value 782.770535
#> iter 6 value 773.534759
#> iter 7 value 771.971682
#> iter 8 value 771.949357
#> iter 9 value 771.949269
#> iter 10 value 771.949142
#> iter 10 value 771.949134
#> iter 11 value 771.949105
#> iter 12 value 771.949057
#> iter 12 value 771.949048
#> iter 12 value 771.949047
#> final value 771.949047
#> converged
#> This is Run number 66
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.05593889 1.4049648 -2.294061 -10.795035 1
#> 2 1 -6.20 -3.90 -0.37450786 -0.4704617 -6.574508 -4.370462 2
#> 3 1 -14.20 -5.80 0.37534751 -0.5989741 -13.824652 -6.398974 2
#> 4 1 -2.10 -13.20 -0.83005334 -0.3126427 -2.930053 -13.512643 1
#> 5 1 -1.70 -4.30 0.43988701 0.2521451 -1.260113 -4.047855 1
#> 6 1 -6.90 -1.55 1.42117014 -0.1803194 -5.478830 -1.730319 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4380 -36700 7400
#> initial value 998.131940
#> iter 2 value 850.259110
#> iter 3 value 848.971779
#> iter 4 value 845.483840
#> iter 5 value 792.449196
#> iter 6 value 783.084643
#> iter 7 value 781.568142
#> iter 8 value 781.541896
#> iter 9 value 781.541818
#> iter 10 value 781.541629
#> iter 10 value 781.541629
#> iter 11 value 781.541610
#> iter 12 value 781.541551
#> iter 12 value 781.541551
#> iter 12 value 781.541548
#> final value 781.541548
#> converged
#> This is Run number 67
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.1303160 2.2271925 -2.4803160 -9.9728075 1
#> 2 1 -6.20 -3.90 4.4813891 2.6635557 -1.7186109 -1.2364443 2
#> 3 1 -14.20 -5.80 2.2320284 -0.5483224 -11.9679716 -6.3483224 2
#> 4 1 -2.10 -13.20 1.6570825 -0.2070998 -0.4429175 -13.4070998 1
#> 5 1 -1.70 -4.30 -0.1750784 0.4829291 -1.8750784 -3.8170709 1
#> 6 1 -6.90 -1.55 -0.2696483 1.3620277 -7.1696483 -0.1879723 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3720 -37575 8875
#> initial value 998.131940
#> iter 2 value 828.675389
#> iter 3 value 824.678385
#> iter 4 value 819.010998
#> iter 5 value 766.051896
#> iter 6 value 756.732432
#> iter 7 value 755.069437
#> iter 8 value 755.045403
#> iter 9 value 755.045349
#> iter 10 value 755.045297
#> iter 10 value 755.045296
#> iter 11 value 755.045284
#> iter 11 value 755.045279
#> iter 11 value 755.045279
#> final value 755.045279
#> converged
#> This is Run number 68
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 3.3833380 0.86922487 1.033338 -11.330775 1
#> 2 1 -6.20 -3.90 0.8437777 0.00852502 -5.356222 -3.891475 2
#> 3 1 -14.20 -5.80 0.5613912 0.11544104 -13.638609 -5.684559 2
#> 4 1 -2.10 -13.20 -1.3817953 -0.65112548 -3.481795 -13.851125 1
#> 5 1 -1.70 -4.30 0.3651437 -0.50626862 -1.334856 -4.806269 1
#> 6 1 -6.90 -1.55 -1.3438314 2.58832529 -8.243831 1.038325 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3940 -35175 9450
#> initial value 998.131940
#> iter 2 value 855.792320
#> iter 3 value 836.815291
#> iter 4 value 836.277056
#> iter 5 value 793.999774
#> iter 6 value 786.930148
#> iter 7 value 786.234393
#> iter 8 value 786.213842
#> iter 9 value 786.213554
#> iter 10 value 786.213422
#> iter 11 value 786.213222
#> iter 12 value 786.213119
#> iter 12 value 786.213119
#> iter 12 value 786.213119
#> final value 786.213119
#> converged
#> This is Run number 69
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.4651999 0.3885999 -2.815200 -11.811400 1
#> 2 1 -6.20 -3.90 1.1080846 -0.5256243 -5.091915 -4.425624 2
#> 3 1 -14.20 -5.80 2.0956649 2.4927948 -12.104335 -3.307205 2
#> 4 1 -2.10 -13.20 1.3005730 -0.5364762 -0.799427 -13.736476 1
#> 5 1 -1.70 -4.30 -0.4120258 -0.6109967 -2.112026 -4.910997 1
#> 6 1 -6.90 -1.55 -0.2608904 0.4550302 -7.160890 -1.094970 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4400 -36775 8150
#> initial value 998.131940
#> iter 2 value 844.855215
#> iter 3 value 830.022989
#> iter 4 value 828.389904
#> iter 5 value 786.543782
#> iter 6 value 778.446270
#> iter 7 value 777.151138
#> iter 8 value 777.099923
#> iter 9 value 777.099038
#> iter 10 value 777.098891
#> iter 11 value 777.098752
#> iter 12 value 777.098636
#> iter 12 value 777.098636
#> iter 12 value 777.098636
#> final value 777.098636
#> converged
#> This is Run number 70
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.8165725 0.9626176 -3.1665725 -11.237382 1
#> 2 1 -6.20 -3.90 1.1118690 0.5078099 -5.0881310 -3.392190 2
#> 3 1 -14.20 -5.80 2.0329138 0.7559811 -12.1670862 -5.044019 2
#> 4 1 -2.10 -13.20 2.9823756 -1.1659006 0.8823756 -14.365901 1
#> 5 1 -1.70 -4.30 2.8614145 -0.1327276 1.1614145 -4.432728 1
#> 6 1 -6.90 -1.55 1.2917455 0.3822399 -5.6082545 -1.167760 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4660 -36975 6600
#> initial value 998.131940
#> iter 2 value 851.020828
#> iter 3 value 848.611774
#> iter 4 value 844.971960
#> iter 5 value 794.612407
#> iter 6 value 785.045825
#> iter 7 value 783.435321
#> iter 8 value 783.402730
#> iter 9 value 783.402692
#> iter 10 value 783.402645
#> iter 10 value 783.402642
#> iter 10 value 783.402642
#> final value 783.402642
#> converged
#> This is Run number 71
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.3976929 0.9177073 -2.7476929 -11.282293 1
#> 2 1 -6.20 -3.90 2.7823111 0.5875632 -3.4176889 -3.312437 2
#> 3 1 -14.20 -5.80 0.3129113 0.4492086 -13.8870887 -5.350791 2
#> 4 1 -2.10 -13.20 -0.5796708 2.1342480 -2.6796708 -11.065752 1
#> 5 1 -1.70 -4.30 1.2523503 -0.9882201 -0.4476497 -5.288220 1
#> 6 1 -6.90 -1.55 0.8617463 -0.5378500 -6.0382537 -2.087850 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4720 -39200 8825
#> initial value 998.131940
#> iter 2 value 806.385411
#> iter 3 value 802.788700
#> iter 4 value 799.838408
#> iter 5 value 752.711387
#> iter 6 value 743.042890
#> iter 7 value 741.529469
#> iter 8 value 741.505839
#> iter 9 value 741.505630
#> iter 10 value 741.505417
#> iter 10 value 741.505411
#> iter 10 value 741.505410
#> final value 741.505410
#> converged
#> This is Run number 72
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.5039744 3.74164899 -1.84602559 -8.4583510 1
#> 2 1 -6.20 -3.90 0.6014584 1.09783691 -5.59854157 -2.8021631 2
#> 3 1 -14.20 -5.80 -0.7142847 0.05776387 -14.91428468 -5.7422361 2
#> 4 1 -2.10 -13.20 2.0433677 -0.80199150 -0.05663231 -14.0019915 1
#> 5 1 -1.70 -4.30 0.1146474 1.99534585 -1.58535256 -2.3046542 1
#> 6 1 -6.90 -1.55 2.5278417 2.13058140 -4.37215827 0.5805814 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3780 -36925 8600
#> initial value 998.131940
#> iter 2 value 839.409943
#> iter 3 value 837.209696
#> iter 4 value 832.400696
#> iter 5 value 777.476360
#> iter 6 value 768.266911
#> iter 7 value 766.648901
#> iter 8 value 766.626719
#> iter 9 value 766.626676
#> iter 10 value 766.626555
#> iter 10 value 766.626550
#> iter 10 value 766.626545
#> final value 766.626545
#> converged
#> This is Run number 73
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.4494958 1.7345651 -3.7994958 -10.465435 1
#> 2 1 -6.20 -3.90 0.3442363 1.0075835 -5.8557637 -2.892417 2
#> 3 1 -14.20 -5.80 1.2978076 3.4928670 -12.9021924 -2.307133 2
#> 4 1 -2.10 -13.20 -0.5748624 -0.1875035 -2.6748624 -13.387504 1
#> 5 1 -1.70 -4.30 0.8694614 -0.4563697 -0.8305386 -4.756370 1
#> 6 1 -6.90 -1.55 -0.2704916 0.4798187 -7.1704916 -1.070181 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4320 -37150 7175
#> initial value 998.131940
#> iter 2 value 845.474908
#> iter 3 value 842.184350
#> iter 4 value 837.692625
#> iter 5 value 786.745469
#> iter 6 value 777.161731
#> iter 7 value 775.610103
#> iter 8 value 775.582905
#> iter 9 value 775.582871
#> iter 10 value 775.582813
#> iter 10 value 775.582810
#> iter 10 value 775.582801
#> final value 775.582801
#> converged
#> This is Run number 74
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.4055048 0.6363696 -0.9444952 -11.563630 1
#> 2 1 -6.20 -3.90 -0.8410177 -0.6075035 -7.0410177 -4.507503 2
#> 3 1 -14.20 -5.80 0.5864629 0.8108504 -13.6135371 -4.989150 2
#> 4 1 -2.10 -13.20 -0.7713636 4.6759420 -2.8713636 -8.524058 1
#> 5 1 -1.70 -4.30 0.2133817 1.8492769 -1.4866183 -2.450723 1
#> 6 1 -6.90 -1.55 1.8425574 0.3298618 -5.0574426 -1.220138 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4620 -37475 8700
#> initial value 998.131940
#> iter 2 value 832.019744
#> iter 3 value 815.771456
#> iter 4 value 814.825325
#> iter 5 value 775.292606
#> iter 6 value 767.139963
#> iter 7 value 766.124507
#> iter 8 value 766.080129
#> iter 9 value 766.079306
#> iter 10 value 766.079220
#> iter 11 value 766.078980
#> iter 12 value 766.078715
#> iter 12 value 766.078715
#> iter 12 value 766.078715
#> final value 766.078715
#> converged
#> This is Run number 75
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.04937408 -0.39690198 -2.399374 -12.596902 1
#> 2 1 -6.20 -3.90 -1.27871756 0.88952995 -7.478718 -3.010470 2
#> 3 1 -14.20 -5.80 0.89763527 -0.07210279 -13.302365 -5.872103 2
#> 4 1 -2.10 -13.20 0.18292648 -0.10810404 -1.917074 -13.308104 1
#> 5 1 -1.70 -4.30 -0.22566958 -0.84315770 -1.925670 -5.143158 1
#> 6 1 -6.90 -1.55 -1.35869959 0.58450903 -8.258700 -0.965491 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3780 -36775 8800
#> initial value 998.131940
#> iter 2 value 840.068799
#> iter 3 value 838.857927
#> iter 4 value 834.507321
#> iter 5 value 778.460092
#> iter 6 value 769.335728
#> iter 7 value 767.704145
#> iter 8 value 767.682167
#> iter 9 value 767.682117
#> iter 10 value 767.682003
#> iter 10 value 767.682002
#> iter 10 value 767.682002
#> final value 767.682002
#> converged
#> This is Run number 76
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.4519911 0.61047138 -1.898009 -11.589529 1
#> 2 1 -6.20 -3.90 -0.2928155 1.27601586 -6.492815 -2.623984 2
#> 3 1 -14.20 -5.80 1.3831303 2.81239788 -12.816870 -2.987602 2
#> 4 1 -2.10 -13.20 0.5743638 1.89840165 -1.525636 -11.301598 1
#> 5 1 -1.70 -4.30 -1.1256945 0.48999387 -2.825695 -3.810006 1
#> 6 1 -6.90 -1.55 -0.0161102 0.08131718 -6.916110 -1.468683 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4420 -38725 8250
#> initial value 998.131940
#> iter 2 value 817.068573
#> iter 3 value 812.457111
#> iter 4 value 807.734063
#> iter 5 value 760.297454
#> iter 6 value 750.542999
#> iter 7 value 749.037400
#> iter 8 value 749.013823
#> iter 9 value 749.013736
#> iter 10 value 749.013544
#> iter 10 value 749.013534
#> iter 10 value 749.013523
#> final value 749.013523
#> converged
#> This is Run number 77
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.7092839 -0.7296749 -1.640716 -12.929675 1
#> 2 1 -6.20 -3.90 0.6129858 1.0979546 -5.587014 -2.802045 2
#> 3 1 -14.20 -5.80 -0.4285098 -0.9858998 -14.628510 -6.785900 2
#> 4 1 -2.10 -13.20 -0.2134370 1.2988319 -2.313437 -11.901168 1
#> 5 1 -1.70 -4.30 -0.2862218 0.3581475 -1.986222 -3.941853 1
#> 6 1 -6.90 -1.55 -0.6343464 -0.3393799 -7.534346 -1.889380 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4760 -37125 8250
#> initial value 998.131940
#> iter 2 value 839.755472
#> iter 3 value 825.226355
#> iter 4 value 824.349966
#> iter 5 value 783.968283
#> iter 6 value 775.750450
#> iter 7 value 774.570434
#> iter 8 value 774.524300
#> iter 9 value 774.523459
#> iter 10 value 774.523263
#> iter 11 value 774.523026
#> iter 12 value 774.522855
#> iter 12 value 774.522855
#> iter 12 value 774.522855
#> final value 774.522855
#> converged
#> This is Run number 78
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.2608798 -1.11279258 -1.089120 -13.3127926 1
#> 2 1 -6.20 -3.90 -0.3279171 2.94484766 -6.527917 -0.9551523 2
#> 3 1 -14.20 -5.80 1.9931025 0.25163443 -12.206898 -5.5483656 2
#> 4 1 -2.10 -13.20 0.2185614 0.71829931 -1.881439 -12.4817007 1
#> 5 1 -1.70 -4.30 -1.0710554 0.05103286 -2.771055 -4.2489671 1
#> 6 1 -6.90 -1.55 2.8050428 -0.84598798 -4.094957 -2.3959880 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4240 -36225 8775
#> initial value 998.131940
#> iter 2 value 847.812074
#> iter 3 value 831.118040
#> iter 4 value 830.109929
#> iter 5 value 788.211325
#> iter 6 value 780.498499
#> iter 7 value 779.524584
#> iter 8 value 779.489161
#> iter 9 value 779.488550
#> iter 10 value 779.488389
#> iter 11 value 779.488189
#> iter 12 value 779.488056
#> iter 12 value 779.488056
#> iter 12 value 779.488056
#> final value 779.488056
#> converged
#> This is Run number 79
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.3399326 1.2372152 -2.68993256 -10.962785 1
#> 2 1 -6.20 -3.90 -0.4568115 0.7409915 -6.65681154 -3.159009 2
#> 3 1 -14.20 -5.80 4.8352628 -0.9642566 -9.36473716 -6.764257 2
#> 4 1 -2.10 -13.20 0.9231170 0.5452014 -1.17688299 -12.654799 1
#> 5 1 -1.70 -4.30 1.6846959 -0.7585376 -0.01530415 -5.058538 1
#> 6 1 -6.90 -1.55 1.9289033 0.5238088 -4.97109674 -1.026191 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4740 -37125 8325
#> initial value 998.131940
#> iter 2 value 839.271032
#> iter 3 value 824.493233
#> iter 4 value 823.644758
#> iter 5 value 783.327214
#> iter 6 value 775.131054
#> iter 7 value 773.986059
#> iter 8 value 773.941167
#> iter 9 value 773.940345
#> iter 10 value 773.940149
#> iter 11 value 773.939909
#> iter 12 value 773.939737
#> iter 12 value 773.939737
#> iter 12 value 773.939737
#> final value 773.939737
#> converged
#> This is Run number 80
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 5.0662042 -0.19352523 2.7162042 -12.393525 1
#> 2 1 -6.20 -3.90 -0.3584616 -0.10399107 -6.5584616 -4.003991 2
#> 3 1 -14.20 -5.80 0.1611421 0.11054841 -14.0388579 -5.689452 2
#> 4 1 -2.10 -13.20 2.6498533 -1.38669236 0.5498533 -14.586692 1
#> 5 1 -1.70 -4.30 0.7553165 -1.22336938 -0.9446835 -5.523369 1
#> 6 1 -6.90 -1.55 -0.5841141 -0.08842405 -7.4841141 -1.638424 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5060 -37600 7075
#> initial value 998.131940
#> iter 2 value 840.250016
#> iter 3 value 839.364399
#> iter 4 value 836.983802
#> iter 5 value 787.671916
#> iter 6 value 777.898411
#> iter 7 value 776.373204
#> iter 8 value 776.340978
#> iter 9 value 776.340855
#> iter 10 value 776.340445
#> iter 10 value 776.340445
#> iter 11 value 776.340421
#> iter 12 value 776.340404
#> iter 12 value 776.340404
#> iter 12 value 776.340400
#> final value 776.340400
#> converged
#> This is Run number 81
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.3142708 -0.3536049 -1.035729 -12.5536049 1
#> 2 1 -6.20 -3.90 0.7193266 0.9760824 -5.480673 -2.9239176 2
#> 3 1 -14.20 -5.80 -0.2945289 0.5374173 -14.494529 -5.2625827 2
#> 4 1 -2.10 -13.20 -1.4992786 0.7774192 -3.599279 -12.4225808 1
#> 5 1 -1.70 -4.30 2.8189908 0.4188651 1.118991 -3.8811349 1
#> 6 1 -6.90 -1.55 -0.6367349 1.0924987 -7.536735 -0.4575013 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4660 -38175 7100
#> initial value 998.131940
#> iter 2 value 831.910454
#> iter 3 value 827.862946
#> iter 4 value 823.299517
#> iter 5 value 776.145148
#> iter 6 value 766.205683
#> iter 7 value 764.682313
#> iter 8 value 764.653548
#> iter 9 value 764.653476
#> iter 10 value 764.653433
#> iter 10 value 764.653432
#> iter 10 value 764.653430
#> final value 764.653430
#> converged
#> This is Run number 82
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.18164345 -0.1033646 -2.168357 -12.303365 1
#> 2 1 -6.20 -3.90 0.85906048 -1.0061318 -5.340940 -4.906132 2
#> 3 1 -14.20 -5.80 0.08271827 -0.8723209 -14.117282 -6.672321 2
#> 4 1 -2.10 -13.20 3.50633784 0.7939991 1.406338 -12.406001 1
#> 5 1 -1.70 -4.30 -0.20138580 -0.9616517 -1.901386 -5.261652 1
#> 6 1 -6.90 -1.55 0.40847472 -0.3435611 -6.491525 -1.893561 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5240 -39000 7375
#> initial value 998.131940
#> iter 2 value 818.545887
#> iter 3 value 816.018234
#> iter 4 value 813.272554
#> iter 5 value 768.260275
#> iter 6 value 758.135678
#> iter 7 value 756.699858
#> iter 8 value 756.671518
#> iter 9 value 756.671137
#> iter 10 value 756.671057
#> iter 10 value 756.671057
#> iter 11 value 756.671023
#> iter 12 value 756.670923
#> iter 12 value 756.670923
#> iter 12 value 756.670917
#> final value 756.670917
#> converged
#> This is Run number 83
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.006557373 2.35812781 -2.343443 -9.841872 1
#> 2 1 -6.20 -3.90 -0.570835146 1.04128380 -6.770835 -2.858716 2
#> 3 1 -14.20 -5.80 0.666473890 1.62960017 -13.533526 -4.170400 2
#> 4 1 -2.10 -13.20 0.628472938 1.23254962 -1.471527 -11.967450 1
#> 5 1 -1.70 -4.30 6.773680751 1.58148590 5.073681 -2.718514 1
#> 6 1 -6.90 -1.55 -0.610179733 -0.03501699 -7.510180 -1.585017 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4600 -35175 7575
#> initial value 998.131940
#> iter 2 value 868.444370
#> iter 3 value 856.209917
#> iter 4 value 855.446727
#> iter 5 value 811.042523
#> iter 6 value 803.484509
#> iter 7 value 802.090879
#> iter 8 value 802.051597
#> iter 9 value 802.051076
#> iter 10 value 802.050911
#> iter 11 value 802.050691
#> iter 12 value 802.050578
#> iter 12 value 802.050578
#> iter 12 value 802.050578
#> final value 802.050578
#> converged
#> This is Run number 84
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.7410103 0.9308367 -1.608990 -11.269163 1
#> 2 1 -6.20 -3.90 0.2023885 -1.1993718 -5.997611 -5.099372 2
#> 3 1 -14.20 -5.80 6.5631674 2.7665919 -7.636833 -3.033408 2
#> 4 1 -2.10 -13.20 0.2260080 -0.3893936 -1.873992 -13.589394 1
#> 5 1 -1.70 -4.30 -0.2491636 -0.1650799 -1.949164 -4.465080 1
#> 6 1 -6.90 -1.55 3.1025138 -0.4356947 -3.797486 -1.985695 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4120 -36325 7950
#> initial value 998.131940
#> iter 2 value 851.706422
#> iter 3 value 851.424004
#> iter 4 value 848.010123
#> iter 5 value 792.374803
#> iter 6 value 783.247393
#> iter 7 value 781.726859
#> iter 8 value 781.703535
#> iter 9 value 781.703289
#> iter 10 value 781.703225
#> iter 10 value 781.703218
#> iter 11 value 781.703202
#> iter 12 value 781.703154
#> iter 12 value 781.703149
#> iter 12 value 781.703149
#> final value 781.703149
#> converged
#> This is Run number 85
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.15685920 1.6181790 -0.1931408 -10.581821 1
#> 2 1 -6.20 -3.90 0.46672790 -0.5924700 -5.7332721 -4.492470 2
#> 3 1 -14.20 -5.80 -0.32280936 0.7126463 -14.5228094 -5.087354 2
#> 4 1 -2.10 -13.20 -0.25683466 0.5463735 -2.3568347 -12.653627 1
#> 5 1 -1.70 -4.30 0.08682804 -0.7854899 -1.6131720 -5.085490 1
#> 6 1 -6.90 -1.55 1.00940826 0.1061092 -5.8905917 -1.443891 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4420 -39225 6775
#> initial value 998.131940
#> iter 2 value 818.003724
#> iter 3 value 808.752365
#> iter 4 value 801.533124
#> iter 5 value 758.677619
#> iter 6 value 748.357946
#> iter 7 value 746.817670
#> iter 8 value 746.784597
#> iter 9 value 746.784494
#> iter 10 value 746.784477
#> iter 10 value 746.784469
#> iter 11 value 746.784455
#> iter 11 value 746.784452
#> iter 11 value 746.784450
#> final value 746.784450
#> converged
#> This is Run number 86
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.3010769 -0.9141604 -2.6510769 -13.114160 1
#> 2 1 -6.20 -3.90 0.1023188 0.8035392 -6.0976812 -3.096461 2
#> 3 1 -14.20 -5.80 -0.2459610 -0.1114015 -14.4459610 -5.911402 2
#> 4 1 -2.10 -13.20 0.4101373 0.5824786 -1.6898627 -12.617521 1
#> 5 1 -1.70 -4.30 1.4802254 -0.9604515 -0.2197746 -5.260452 1
#> 6 1 -6.90 -1.55 2.0798398 0.1295004 -4.8201602 -1.420500 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5220 -37050 6750
#> initial value 998.131940
#> iter 2 value 849.418370
#> iter 3 value 839.474163
#> iter 4 value 838.177804
#> iter 5 value 796.663048
#> iter 6 value 788.310262
#> iter 7 value 786.256936
#> iter 8 value 786.177593
#> iter 9 value 786.176371
#> iter 10 value 786.176345
#> iter 11 value 786.176117
#> iter 12 value 786.175818
#> iter 12 value 786.175818
#> iter 12 value 786.175818
#> final value 786.175818
#> converged
#> This is Run number 87
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.2281456 0.07351175 -1.1218544 -12.126488 1
#> 2 1 -6.20 -3.90 1.5385527 0.00620283 -4.6614473 -3.893797 2
#> 3 1 -14.20 -5.80 -0.2672927 2.42437809 -14.4672927 -3.375622 2
#> 4 1 -2.10 -13.20 -0.2231812 1.63727386 -2.3231812 -11.562726 1
#> 5 1 -1.70 -4.30 1.2463589 0.24978596 -0.4536411 -4.050214 1
#> 6 1 -6.90 -1.55 0.6295867 -1.34875019 -6.2704133 -2.898750 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4600 -38650 8575
#> initial value 998.131940
#> iter 2 value 816.185596
#> iter 3 value 813.204255
#> iter 4 value 809.970548
#> iter 5 value 761.322245
#> iter 6 value 751.639968
#> iter 7 value 750.124991
#> iter 8 value 750.101974
#> iter 9 value 750.101845
#> iter 10 value 750.101566
#> iter 10 value 750.101565
#> iter 11 value 750.101550
#> iter 12 value 750.101498
#> iter 12 value 750.101498
#> iter 12 value 750.101494
#> final value 750.101494
#> converged
#> This is Run number 88
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.3899620 3.6925034 -2.739962 -8.507497 1
#> 2 1 -6.20 -3.90 1.9221369 0.3410687 -4.277863 -3.558931 2
#> 3 1 -14.20 -5.80 2.5180977 0.8891951 -11.681902 -4.910805 2
#> 4 1 -2.10 -13.20 0.8369726 1.2324104 -1.263027 -11.967590 1
#> 5 1 -1.70 -4.30 -0.5723168 -0.3453459 -2.272317 -4.645346 1
#> 6 1 -6.90 -1.55 1.7238869 3.7486137 -5.176113 2.198614 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4660 -36750 8750
#> initial value 998.131940
#> iter 2 value 841.423991
#> iter 3 value 825.403712
#> iter 4 value 824.930412
#> iter 5 value 784.559152
#> iter 6 value 776.612530
#> iter 7 value 775.679787
#> iter 8 value 775.646194
#> iter 9 value 775.645622
#> iter 10 value 775.645429
#> iter 11 value 775.645149
#> iter 12 value 775.644977
#> iter 12 value 775.644977
#> iter 12 value 775.644977
#> final value 775.644977
#> converged
#> This is Run number 89
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.8252059 3.2157923 0.4752059 -8.984208 1
#> 2 1 -6.20 -3.90 -1.6099043 2.0010008 -7.8099043 -1.898999 2
#> 3 1 -14.20 -5.80 -0.4744442 0.2704471 -14.6744442 -5.529553 2
#> 4 1 -2.10 -13.20 -0.4882044 -0.3979737 -2.5882044 -13.597974 1
#> 5 1 -1.70 -4.30 -0.3199300 -0.9464690 -2.0199300 -5.246469 1
#> 6 1 -6.90 -1.55 -0.7328442 -0.7353443 -7.6328442 -2.285344 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4240 -37500 9300
#> initial value 998.131940
#> iter 2 value 827.275275
#> iter 3 value 827.058454
#> iter 4 value 824.532562
#> iter 5 value 769.781233
#> iter 6 value 760.483775
#> iter 7 value 758.859056
#> iter 8 value 758.836213
#> iter 9 value 758.836080
#> iter 10 value 758.835983
#> iter 10 value 758.835979
#> iter 11 value 758.835957
#> iter 11 value 758.835948
#> iter 11 value 758.835946
#> final value 758.835946
#> converged
#> This is Run number 90
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.49891682 2.0281329 -1.851083 -10.171867 1
#> 2 1 -6.20 -3.90 -0.40957352 2.0659096 -6.609574 -1.834090 2
#> 3 1 -14.20 -5.80 1.00185344 0.2533755 -13.198147 -5.546624 2
#> 4 1 -2.10 -13.20 -0.40556423 0.2048927 -2.505564 -12.995107 1
#> 5 1 -1.70 -4.30 -0.64828977 1.3893261 -2.348290 -2.910674 1
#> 6 1 -6.90 -1.55 -0.00287213 -0.2826485 -6.902872 -1.832648 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4420 -36100 8075
#> initial value 998.131940
#> iter 2 value 854.033442
#> iter 3 value 839.757460
#> iter 4 value 838.555263
#> iter 5 value 795.747354
#> iter 6 value 787.878810
#> iter 7 value 786.613038
#> iter 8 value 786.569092
#> iter 9 value 786.568378
#> iter 10 value 786.568212
#> iter 11 value 786.568023
#> iter 12 value 786.567897
#> iter 12 value 786.567897
#> iter 12 value 786.567897
#> final value 786.567897
#> converged
#> This is Run number 91
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.04731083 1.2046841 -2.397311 -10.9953159 1
#> 2 1 -6.20 -3.90 -0.50858903 -0.2590025 -6.708589 -4.1590025 2
#> 3 1 -14.20 -5.80 -1.42204082 0.3560212 -15.622041 -5.4439788 2
#> 4 1 -2.10 -13.20 3.96125219 -0.2783707 1.861252 -13.4783707 1
#> 5 1 -1.70 -4.30 -0.47344109 0.2934525 -2.173441 -4.0065475 1
#> 6 1 -6.90 -1.55 0.29926013 1.1701623 -6.600740 -0.3798377 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4840 -39125 8300
#> initial value 998.131940
#> iter 2 value 811.033137
#> iter 3 value 807.597655
#> iter 4 value 804.449714
#> iter 5 value 758.119461
#> iter 6 value 748.275491
#> iter 7 value 746.812537
#> iter 8 value 746.789105
#> iter 9 value 746.788968
#> iter 10 value 746.788596
#> iter 10 value 746.788591
#> iter 11 value 746.788569
#> iter 12 value 746.788528
#> iter 12 value 746.788527
#> iter 12 value 746.788522
#> final value 746.788522
#> converged
#> This is Run number 92
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.70951345 -0.7903765 -1.64048655 -12.990377 1
#> 2 1 -6.20 -3.90 -0.04594059 -0.6133461 -6.24594059 -4.513346 2
#> 3 1 -14.20 -5.80 1.75782510 -0.1693818 -12.44217490 -5.969382 2
#> 4 1 -2.10 -13.20 -0.31131070 3.3526483 -2.41131070 -9.847352 1
#> 5 1 -1.70 -4.30 1.73733633 1.1470262 0.03733633 -3.152974 1
#> 6 1 -6.90 -1.55 0.33397542 3.1130814 -6.56602458 1.563081 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5220 -37775 7700
#> initial value 998.131940
#> iter 2 value 834.314337
#> iter 3 value 821.844110
#> iter 4 value 821.067774
#> iter 5 value 781.940916
#> iter 6 value 773.367865
#> iter 7 value 771.940261
#> iter 8 value 771.881778
#> iter 9 value 771.880709
#> iter 10 value 771.880489
#> iter 11 value 771.880227
#> iter 12 value 771.880026
#> iter 12 value 771.880026
#> iter 12 value 771.880026
#> final value 771.880026
#> converged
#> This is Run number 93
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.002544636 3.01269958 -2.352545 -9.1873004 1
#> 2 1 -6.20 -3.90 0.461620685 -0.57228098 -5.738379 -4.4722810 2
#> 3 1 -14.20 -5.80 -0.104974303 1.87082085 -14.304974 -3.9291792 2
#> 4 1 -2.10 -13.20 0.917834504 0.03849098 -1.182165 -13.1615090 1
#> 5 1 -1.70 -4.30 -1.047649137 1.06059458 -2.747649 -3.2394054 1
#> 6 1 -6.90 -1.55 2.266104335 0.79433077 -4.633896 -0.7556692 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5240 -39025 7300
#> initial value 998.131940
#> iter 2 value 818.593263
#> iter 3 value 815.915283
#> iter 4 value 813.027616
#> iter 5 value 768.271419
#> iter 6 value 758.128104
#> iter 7 value 756.690588
#> iter 8 value 756.661966
#> iter 9 value 756.661623
#> iter 10 value 756.661524
#> iter 10 value 756.661522
#> iter 11 value 756.661497
#> iter 12 value 756.661419
#> iter 12 value 756.661417
#> iter 12 value 756.661412
#> final value 756.661412
#> converged
#> This is Run number 94
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.07649172 -0.4126947 -2.4264917 -12.612695 1
#> 2 1 -6.20 -3.90 0.91224528 0.3568797 -5.2877547 -3.543120 2
#> 3 1 -14.20 -5.80 -0.51983325 -0.3146800 -14.7198332 -6.114680 2
#> 4 1 -2.10 -13.20 1.03192599 0.2935649 -1.0680740 -12.906435 1
#> 5 1 -1.70 -4.30 1.62874650 1.0643130 -0.0712535 -3.235687 1
#> 6 1 -6.90 -1.55 -0.70073712 6.7215510 -7.6007371 5.171551 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5020 -38850 7450
#> initial value 998.131940
#> iter 2 value 820.317754
#> iter 3 value 817.229385
#> iter 4 value 813.856785
#> iter 5 value 768.247771
#> iter 6 value 758.194501
#> iter 7 value 756.748091
#> iter 8 value 756.721008
#> iter 9 value 756.720699
#> iter 10 value 756.720675
#> iter 10 value 756.720672
#> iter 11 value 756.720645
#> iter 12 value 756.720554
#> iter 12 value 756.720553
#> iter 13 value 756.720540
#> iter 14 value 756.720528
#> iter 14 value 756.720527
#> iter 14 value 756.720527
#> final value 756.720527
#> converged
#> This is Run number 95
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.75476506 1.1376200 -0.5952349 -11.062380 1
#> 2 1 -6.20 -3.90 0.37143699 -0.4064870 -5.8285630 -4.306487 2
#> 3 1 -14.20 -5.80 0.05597248 1.8895934 -14.1440275 -3.910407 2
#> 4 1 -2.10 -13.20 -1.57002365 0.7956458 -3.6700237 -12.404354 1
#> 5 1 -1.70 -4.30 1.02477855 2.7510652 -0.6752215 -1.548935 1
#> 6 1 -6.90 -1.55 0.27774933 -1.4798926 -6.6222507 -3.029893 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4180 -37950 8700
#> initial value 998.131940
#> iter 2 value 825.118573
#> iter 3 value 822.218489
#> iter 4 value 818.088146
#> iter 5 value 766.677225
#> iter 6 value 757.197793
#> iter 7 value 755.620741
#> iter 8 value 755.597842
#> iter 9 value 755.597757
#> iter 10 value 755.597589
#> iter 10 value 755.597589
#> iter 10 value 755.597582
#> final value 755.597582
#> converged
#> This is Run number 96
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.99460283 0.6204715 -3.3446028 -11.579529 1
#> 2 1 -6.20 -3.90 0.27052160 2.0403030 -5.9294784 -1.859697 2
#> 3 1 -14.20 -5.80 0.06212584 0.4919944 -14.1378742 -5.308006 2
#> 4 1 -2.10 -13.20 -0.28130468 -0.7168769 -2.3813047 -13.916877 1
#> 5 1 -1.70 -4.30 2.07091585 0.8318879 0.3709159 -3.468112 1
#> 6 1 -6.90 -1.55 1.75504684 -1.0429918 -5.1449532 -2.592992 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4240 -34975 7900
#> initial value 998.131940
#> iter 2 value 868.696169
#> iter 3 value 855.026244
#> iter 4 value 853.943908
#> iter 5 value 809.123841
#> iter 6 value 801.699248
#> iter 7 value 800.440198
#> iter 8 value 800.403533
#> iter 9 value 800.403021
#> iter 10 value 800.402872
#> iter 11 value 800.402691
#> iter 12 value 800.402591
#> iter 12 value 800.402591
#> iter 12 value 800.402591
#> final value 800.402591
#> converged
#> This is Run number 97
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.6804658 7.8234856 -0.66953424 -4.376514 1
#> 2 1 -6.20 -3.90 -1.1723727 2.2616485 -7.37237269 -1.638352 2
#> 3 1 -14.20 -5.80 0.5888012 0.2182166 -13.61119883 -5.581783 2
#> 4 1 -2.10 -13.20 2.1592152 -0.4703820 0.05921521 -13.670382 1
#> 5 1 -1.70 -4.30 -0.1667923 2.4902909 -1.86679234 -1.809709 2
#> 6 1 -6.90 -1.55 3.5732289 0.1049713 -3.32677109 -1.445029 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3880 -35475 9075
#> initial value 998.131940
#> iter 2 value 854.786382
#> iter 3 value 836.758096
#> iter 4 value 835.665082
#> iter 5 value 792.683592
#> iter 6 value 785.376819
#> iter 7 value 784.518924
#> iter 8 value 784.489941
#> iter 9 value 784.489473
#> iter 10 value 784.489337
#> iter 11 value 784.489169
#> iter 12 value 784.489063
#> iter 12 value 784.489063
#> iter 12 value 784.489063
#> final value 784.489063
#> converged
#> This is Run number 98
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.5462102 -1.1871589 -2.8962102 -13.387159 1
#> 2 1 -6.20 -3.90 0.7099834 2.1583818 -5.4900166 -1.741618 2
#> 3 1 -14.20 -5.80 -0.2238515 -1.4977059 -14.4238515 -7.297706 2
#> 4 1 -2.10 -13.20 0.5999046 2.8819350 -1.5000954 -10.318065 1
#> 5 1 -1.70 -4.30 0.9987987 0.4645474 -0.7012013 -3.835453 1
#> 6 1 -6.90 -1.55 -0.1866644 -0.7704091 -7.0866644 -2.320409 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4760 -37900 7825
#> initial value 998.131940
#> iter 2 value 831.737854
#> iter 3 value 830.213381
#> iter 4 value 827.407609
#> iter 5 value 777.559280
#> iter 6 value 767.825921
#> iter 7 value 766.337915
#> iter 8 value 766.311793
#> iter 9 value 766.311410
#> iter 10 value 766.311377
#> iter 10 value 766.311371
#> iter 10 value 766.311371
#> final value 766.311371
#> converged
#> This is Run number 99
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.3315898832 2.05543660 -0.01841012 -10.144563 1
#> 2 1 -6.20 -3.90 4.7108183578 -0.22771780 -1.48918164 -4.127718 1
#> 3 1 -14.20 -5.80 -0.3416886667 -0.08102251 -14.54168867 -5.881023 2
#> 4 1 -2.10 -13.20 0.0009812646 -0.64774726 -2.09901874 -13.847747 1
#> 5 1 -1.70 -4.30 0.0158874385 2.67469882 -1.68411256 -1.625301 2
#> 6 1 -6.90 -1.55 0.8868829836 0.47373977 -6.01311702 -1.076260 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5080 -38100 8125
#> initial value 998.131940
#> iter 2 value 827.160706
#> iter 3 value 826.778951
#> iter 4 value 825.297884
#> iter 5 value 775.491644
#> iter 6 value 765.702107
#> iter 7 value 764.208502
#> iter 8 value 764.182275
#> iter 9 value 764.181846
#> iter 10 value 764.181686
#> iter 11 value 764.181624
#> iter 12 value 764.181527
#> iter 12 value 764.181527
#> iter 12 value 764.181527
#> final value 764.181527
#> converged
#> This is Run number 100
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.2749904 2.4036846 -2.624990392 -9.796315 1
#> 2 1 -6.20 -3.90 1.1747567 2.4109400 -5.025243267 -1.489060 2
#> 3 1 -14.20 -5.80 0.8599178 -0.6658785 -13.340082201 -6.465879 2
#> 4 1 -2.10 -13.20 3.3923544 -0.4249671 1.292354434 -13.624967 1
#> 5 1 -1.70 -4.30 1.7075315 -0.5737491 0.007531473 -4.873749 1
#> 6 1 -6.90 -1.55 0.4773335 -0.2693873 -6.422666472 -1.819387 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5080 -36025 8325
#> initial value 998.131940
#> iter 2 value 853.590373
#> iter 3 value 839.779287
#> iter 4 value 839.735559
#> iter 5 value 798.398646
#> iter 6 value 790.565956
#> iter 7 value 789.582415
#> iter 8 value 789.557102
#> iter 9 value 789.556798
#> iter 10 value 789.556685
#> iter 11 value 789.556483
#> iter 12 value 789.556357
#> iter 12 value 789.556357
#> iter 12 value 789.556357
#> final value 789.556357
#> converged
#> This is Run number 101
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.4079910 -0.8162012 -1.94200896 -13.0162012 1
#> 2 1 -6.20 -3.90 0.1914849 1.4814915 -6.00851506 -2.4185085 2
#> 3 1 -14.20 -5.80 3.6540535 -0.3954948 -10.54594652 -6.1954948 2
#> 4 1 -2.10 -13.20 0.5519237 1.2387365 -1.54807631 -11.9612635 1
#> 5 1 -1.70 -4.30 1.7658721 4.0701144 0.06587208 -0.2298856 1
#> 6 1 -6.90 -1.55 0.3501438 -1.2284613 -6.54985618 -2.7784613 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4440 -37700 8075
#> initial value 998.131940
#> iter 2 value 832.838065
#> iter 3 value 830.771989
#> iter 4 value 827.224463
#> iter 5 value 776.194040
#> iter 6 value 766.601257
#> iter 7 value 765.087081
#> iter 8 value 765.063059
#> iter 9 value 765.062831
#> iter 10 value 765.062673
#> iter 10 value 765.062672
#> iter 11 value 765.062655
#> iter 12 value 765.062623
#> iter 12 value 765.062623
#> iter 12 value 765.062622
#> final value 765.062622
#> converged
#> This is Run number 102
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.4812427 0.05158502 -3.8312427 -12.148415 1
#> 2 1 -6.20 -3.90 2.3049594 0.81413303 -3.8950406 -3.085867 2
#> 3 1 -14.20 -5.80 -0.1459469 -0.31402692 -14.3459469 -6.114027 2
#> 4 1 -2.10 -13.20 1.0471054 0.92633216 -1.0528946 -12.273668 1
#> 5 1 -1.70 -4.30 2.1909172 0.25721334 0.4909172 -4.042787 1
#> 6 1 -6.90 -1.55 -0.6036608 -1.53812679 -7.5036608 -3.088127 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5240 -38825 6850
#> initial value 998.131940
#> iter 2 value 823.982573
#> iter 3 value 821.040668
#> iter 4 value 817.704584
#> iter 5 value 773.195450
#> iter 6 value 763.019507
#> iter 7 value 761.524643
#> iter 8 value 761.492486
#> iter 9 value 761.492462
#> iter 10 value 761.492272
#> iter 10 value 761.492270
#> iter 11 value 761.492221
#> iter 11 value 761.492211
#> iter 11 value 761.492210
#> final value 761.492210
#> converged
#> This is Run number 103
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.4537448 0.5306759 -0.8962552 -11.669324 1
#> 2 1 -6.20 -3.90 2.0038873 0.7907346 -4.1961127 -3.109265 2
#> 3 1 -14.20 -5.80 0.9048046 1.1175996 -13.2951954 -4.682400 2
#> 4 1 -2.10 -13.20 0.4674015 0.7068261 -1.6325985 -12.493174 1
#> 5 1 -1.70 -4.30 0.7021442 1.8859523 -0.9978558 -2.414048 1
#> 6 1 -6.90 -1.55 -0.3290045 -0.9432886 -7.2290045 -2.493289 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4840 -38075 7275
#> initial value 998.131940
#> iter 2 value 832.464692
#> iter 3 value 829.957257
#> iter 4 value 826.501729
#> iter 5 value 778.507509
#> iter 6 value 768.622799
#> iter 7 value 767.127165
#> iter 8 value 767.098667
#> iter 9 value 767.098497
#> iter 9 value 767.098488
#> iter 9 value 767.098488
#> final value 767.098488
#> converged
#> This is Run number 104
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.40140541 0.7093695 -2.751405 -11.4906305 1
#> 2 1 -6.20 -3.90 1.90602588 -0.4218238 -4.293974 -4.3218238 1
#> 3 1 -14.20 -5.80 1.15946145 3.5923799 -13.040539 -2.2076201 2
#> 4 1 -2.10 -13.20 -0.08381045 0.9720079 -2.183810 -12.2279921 1
#> 5 1 -1.70 -4.30 -0.01500206 0.8907941 -1.715002 -3.4092059 1
#> 6 1 -6.90 -1.55 -0.52757926 2.4772321 -7.427579 0.9272321 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4940 -35150 7100
#> initial value 998.131940
#> iter 2 value 871.478534
#> iter 3 value 860.992859
#> iter 4 value 860.463363
#> iter 5 value 815.861088
#> iter 6 value 808.285567
#> iter 7 value 806.686941
#> iter 8 value 806.643973
#> iter 9 value 806.643460
#> iter 10 value 806.643289
#> iter 11 value 806.643046
#> iter 12 value 806.642932
#> iter 12 value 806.642932
#> iter 12 value 806.642932
#> final value 806.642932
#> converged
#> This is Run number 105
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.5000914 -0.30229569 -1.849909 -12.502296 1
#> 2 1 -6.20 -3.90 1.3090386 -0.69365525 -4.890961 -4.593655 2
#> 3 1 -14.20 -5.80 -1.3005179 -0.99797290 -15.500518 -6.797973 2
#> 4 1 -2.10 -13.20 0.3932459 0.05412133 -1.706754 -13.145879 1
#> 5 1 -1.70 -4.30 0.5934903 3.30139397 -1.106510 -0.998606 2
#> 6 1 -6.90 -1.55 -0.4097989 -0.72167328 -7.309799 -2.271673 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4620 -36650 8350
#> initial value 998.131940
#> iter 2 value 845.348771
#> iter 3 value 830.468515
#> iter 4 value 829.646273
#> iter 5 value 788.437234
#> iter 6 value 780.413280
#> iter 7 value 779.288065
#> iter 8 value 779.247129
#> iter 9 value 779.246413
#> iter 10 value 779.246223
#> iter 11 value 779.245991
#> iter 12 value 779.245833
#> iter 12 value 779.245833
#> iter 12 value 779.245833
#> final value 779.245833
#> converged
#> This is Run number 106
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 3.4489183 -0.8182376 1.098918 -13.018238 1
#> 2 1 -6.20 -3.90 2.1715747 2.4147744 -4.028425 -1.485226 2
#> 3 1 -14.20 -5.80 0.7769808 1.5580908 -13.423019 -4.241909 2
#> 4 1 -2.10 -13.20 -0.6056746 0.6472338 -2.705675 -12.552766 1
#> 5 1 -1.70 -4.30 2.9298958 1.9208159 1.229896 -2.379184 1
#> 6 1 -6.90 -1.55 0.7805345 -0.5311440 -6.119465 -2.081144 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4900 -37725 7875
#> initial value 998.131940
#> iter 2 value 833.927016
#> iter 3 value 833.427321
#> iter 4 value 831.379188
#> iter 5 value 780.762018
#> iter 6 value 771.061512
#> iter 7 value 769.567631
#> iter 8 value 769.540379
#> iter 9 value 769.539960
#> iter 10 value 769.539789
#> iter 11 value 769.539753
#> iter 12 value 769.539663
#> iter 12 value 769.539663
#> iter 12 value 769.539663
#> final value 769.539663
#> converged
#> This is Run number 107
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.03161072 -0.6483865 -2.318389 -12.8483865 1
#> 2 1 -6.20 -3.90 -0.83412787 -0.8700861 -7.034128 -4.7700861 2
#> 3 1 -14.20 -5.80 0.81627812 1.1674127 -13.383722 -4.6325873 2
#> 4 1 -2.10 -13.20 0.32777239 -0.5539485 -1.772228 -13.7539485 1
#> 5 1 -1.70 -4.30 0.23990160 2.3436375 -1.460098 -1.9563625 1
#> 6 1 -6.90 -1.55 1.66923123 0.8466937 -5.230769 -0.7033063 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5800 -39200 8300
#> initial value 998.131940
#> iter 2 value 809.819226
#> iter 3 value 809.115534
#> iter 4 value 808.820495
#> iter 5 value 762.987148
#> iter 6 value 752.913973
#> iter 7 value 751.449182
#> iter 8 value 751.425478
#> iter 9 value 751.425287
#> iter 10 value 751.424868
#> iter 11 value 751.424780
#> iter 12 value 751.424679
#> iter 12 value 751.424679
#> iter 12 value 751.424679
#> final value 751.424679
#> converged
#> This is Run number 108
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.2108041 1.0967799 -2.139196 -11.1032201 1
#> 2 1 -6.20 -3.90 0.4956491 -0.2418877 -5.704351 -4.1418877 2
#> 3 1 -14.20 -5.80 0.7063748 -0.1584985 -13.493625 -5.9584985 2
#> 4 1 -2.10 -13.20 0.7124667 -0.4456100 -1.387533 -13.6456100 1
#> 5 1 -1.70 -4.30 0.2598926 -0.7813890 -1.440107 -5.0813890 1
#> 6 1 -6.90 -1.55 -0.9386438 1.3496515 -7.838644 -0.2003485 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4840 -37200 8425
#> initial value 998.131940
#> iter 2 value 837.647995
#> iter 3 value 822.742205
#> iter 4 value 822.142081
#> iter 5 value 782.276052
#> iter 6 value 774.070759
#> iter 7 value 772.997513
#> iter 8 value 772.956073
#> iter 9 value 772.955320
#> iter 10 value 772.955114
#> iter 11 value 772.954838
#> iter 12 value 772.954651
#> iter 12 value 772.954651
#> iter 12 value 772.954651
#> final value 772.954651
#> converged
#> This is Run number 109
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.4600599 1.4704877 -2.810060 -10.729512 1
#> 2 1 -6.20 -3.90 2.5049667 0.5602735 -3.695033 -3.339726 2
#> 3 1 -14.20 -5.80 -0.5291462 -0.2513481 -14.729146 -6.051348 2
#> 4 1 -2.10 -13.20 -0.3335472 -1.4429086 -2.433547 -14.642909 1
#> 5 1 -1.70 -4.30 -0.6569452 0.3729968 -2.356945 -3.927003 1
#> 6 1 -6.90 -1.55 0.7496052 0.2483555 -6.150395 -1.301644 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4900 -37225 8000
#> initial value 998.131940
#> iter 2 value 840.008831
#> iter 3 value 826.387453
#> iter 4 value 825.518935
#> iter 5 value 785.231876
#> iter 6 value 776.911707
#> iter 7 value 775.619076
#> iter 8 value 775.568739
#> iter 9 value 775.567833
#> iter 10 value 775.567629
#> iter 11 value 775.567388
#> iter 12 value 775.567211
#> iter 12 value 775.567211
#> iter 12 value 775.567211
#> final value 775.567211
#> converged
#> This is Run number 110
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.2036090 0.7283846 -2.1463910 -11.4716154 1
#> 2 1 -6.20 -3.90 0.4676617 0.2784334 -5.7323383 -3.6215666 2
#> 3 1 -14.20 -5.80 0.1859984 0.1470979 -14.0140016 -5.6529021 2
#> 4 1 -2.10 -13.20 -0.3001097 2.0874261 -2.4001097 -11.1125739 1
#> 5 1 -1.70 -4.30 1.2791438 -0.3651491 -0.4208562 -4.6651491 1
#> 6 1 -6.90 -1.55 0.9454083 1.6593665 -5.9545917 0.1093665 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4340 -36700 8550
#> initial value 998.131940
#> iter 2 value 843.242397
#> iter 3 value 827.202216
#> iter 4 value 825.910783
#> iter 5 value 784.446618
#> iter 6 value 776.494698
#> iter 7 value 775.398651
#> iter 8 value 775.355386
#> iter 9 value 775.354612
#> iter 10 value 775.354453
#> iter 11 value 775.354278
#> iter 12 value 775.354144
#> iter 12 value 775.354144
#> iter 12 value 775.354144
#> final value 775.354144
#> converged
#> This is Run number 111
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.8473046 -0.02600532 -3.197305 -12.226005 1
#> 2 1 -6.20 -3.90 0.9876186 -1.22564925 -5.212381 -5.125649 2
#> 3 1 -14.20 -5.80 1.9564033 -0.62091324 -12.243597 -6.420913 2
#> 4 1 -2.10 -13.20 -0.4117944 -0.92077981 -2.511794 -14.120780 1
#> 5 1 -1.70 -4.30 0.0789743 2.31062567 -1.621026 -1.989374 1
#> 6 1 -6.90 -1.55 -0.9954379 0.30736517 -7.895438 -1.242635 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5080 -37175 6875
#> initial value 998.131940
#> iter 2 value 847.092228
#> iter 3 value 846.758717
#> iter 4 value 844.602380
#> iter 5 value 794.290087
#> iter 6 value 784.662819
#> iter 7 value 783.103648
#> iter 8 value 783.069596
#> iter 9 value 783.069455
#> iter 10 value 783.069089
#> iter 10 value 783.069089
#> iter 11 value 783.069074
#> iter 12 value 783.069033
#> iter 12 value 783.069033
#> iter 12 value 783.069031
#> final value 783.069031
#> converged
#> This is Run number 112
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.32851519 1.1561615 -2.678515 -11.043839 1
#> 2 1 -6.20 -3.90 0.07855314 1.1513832 -6.121447 -2.748617 2
#> 3 1 -14.20 -5.80 -1.38328018 1.4413701 -15.583280 -4.358630 2
#> 4 1 -2.10 -13.20 0.81934598 1.6632724 -1.280654 -11.536728 1
#> 5 1 -1.70 -4.30 -0.73046403 2.1756354 -2.430464 -2.124365 2
#> 6 1 -6.90 -1.55 1.79683636 -0.5629719 -5.103164 -2.112972 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4420 -36800 8650
#> initial value 998.131940
#> iter 2 value 841.319488
#> iter 3 value 825.109759
#> iter 4 value 824.051122
#> iter 5 value 783.065683
#> iter 6 value 775.106269
#> iter 7 value 774.068757
#> iter 8 value 774.027742
#> iter 9 value 774.027001
#> iter 10 value 774.026831
#> iter 11 value 774.026624
#> iter 12 value 774.026475
#> iter 12 value 774.026475
#> iter 12 value 774.026475
#> final value 774.026475
#> converged
#> This is Run number 113
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.67908208 -0.6172328 -3.029082 -12.8172328 1
#> 2 1 -6.20 -3.90 -0.17856471 0.2350492 -6.378565 -3.6649508 2
#> 3 1 -14.20 -5.80 0.24288854 3.4118086 -13.957111 -2.3881914 2
#> 4 1 -2.10 -13.20 0.70465092 2.1744507 -1.395349 -11.0255493 1
#> 5 1 -1.70 -4.30 0.02635375 1.4552814 -1.673646 -2.8447186 1
#> 6 1 -6.90 -1.55 0.09274352 0.7452774 -6.807256 -0.8047226 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3980 -35975 7550
#> initial value 998.131940
#> iter 2 value 858.355060
#> iter 3 value 857.217708
#> iter 4 value 853.269406
#> iter 5 value 797.407201
#> iter 6 value 788.367794
#> iter 7 value 786.849729
#> iter 8 value 786.826365
#> iter 9 value 786.826258
#> iter 10 value 786.826165
#> iter 10 value 786.826165
#> iter 11 value 786.826143
#> iter 12 value 786.826129
#> iter 12 value 786.826129
#> iter 12 value 786.826128
#> final value 786.826128
#> converged
#> This is Run number 114
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.21211488 0.0002347488 -2.562115 -12.199765 1
#> 2 1 -6.20 -3.90 0.54538410 0.1543775376 -5.654616 -3.745622 2
#> 3 1 -14.20 -5.80 1.14179789 -0.6938781477 -13.058202 -6.493878 2
#> 4 1 -2.10 -13.20 -0.92658971 0.8548961868 -3.026590 -12.345104 1
#> 5 1 -1.70 -4.30 -0.71589547 -1.1728768929 -2.415895 -5.472877 1
#> 6 1 -6.90 -1.55 -0.03692229 -0.2732348157 -6.936922 -1.823235 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4120 -35175 9100
#> initial value 998.131940
#> iter 2 value 858.439609
#> iter 3 value 840.955349
#> iter 4 value 840.470566
#> iter 5 value 797.888984
#> iter 6 value 790.669628
#> iter 7 value 789.886996
#> iter 8 value 789.865183
#> iter 9 value 789.864869
#> iter 10 value 789.864736
#> iter 11 value 789.864545
#> iter 12 value 789.864444
#> iter 12 value 789.864444
#> iter 12 value 789.864444
#> final value 789.864444
#> converged
#> This is Run number 115
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.0877371 0.5322919 -3.437737 -11.667708 1
#> 2 1 -6.20 -3.90 -1.0644939 -0.4748330 -7.264494 -4.374833 2
#> 3 1 -14.20 -5.80 0.1388093 0.7215145 -14.061191 -5.078485 2
#> 4 1 -2.10 -13.20 0.8783040 -1.2465353 -1.221696 -14.446535 1
#> 5 1 -1.70 -4.30 0.4531047 -0.5759108 -1.246895 -4.875911 1
#> 6 1 -6.90 -1.55 -0.4005852 -0.3492541 -7.300585 -1.899254 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4340 -37525 8100
#> initial value 998.131940
#> iter 2 value 835.030800
#> iter 3 value 832.976787
#> iter 4 value 829.244684
#> iter 5 value 777.548338
#> iter 6 value 768.019109
#> iter 7 value 766.494836
#> iter 8 value 766.471117
#> iter 9 value 766.470917
#> iter 10 value 766.470771
#> iter 10 value 766.470770
#> iter 11 value 766.470751
#> iter 12 value 766.470723
#> iter 12 value 766.470723
#> iter 12 value 766.470718
#> final value 766.470718
#> converged
#> This is Run number 116
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.5140125 -1.36609455 -2.864012 -13.566095 1
#> 2 1 -6.20 -3.90 0.5196158 0.17772103 -5.680384 -3.722279 2
#> 3 1 -14.20 -5.80 2.0144796 0.82693930 -12.185520 -4.973061 2
#> 4 1 -2.10 -13.20 -0.6178215 0.75858402 -2.717822 -12.441416 1
#> 5 1 -1.70 -4.30 -0.6795010 -0.04639285 -2.379501 -4.346393 1
#> 6 1 -6.90 -1.55 0.1580696 0.07871844 -6.741930 -1.471282 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4280 -38475 9225
#> initial value 998.131940
#> iter 2 value 814.059877
#> iter 3 value 810.974415
#> iter 4 value 807.456986
#> iter 5 value 756.781021
#> iter 6 value 747.340702
#> iter 7 value 745.733679
#> iter 8 value 745.708610
#> iter 9 value 745.708435
#> iter 10 value 745.708349
#> iter 10 value 745.708347
#> iter 10 value 745.708346
#> final value 745.708346
#> converged
#> This is Run number 117
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.09137498 3.6127809 -2.4413750 -8.5872191 1
#> 2 1 -6.20 -3.90 0.11303570 -0.2336817 -6.0869643 -4.1336817 2
#> 3 1 -14.20 -5.80 0.18366531 3.7779450 -14.0163347 -2.0220550 2
#> 4 1 -2.10 -13.20 -0.43863862 -0.1814993 -2.5386386 -13.3814993 1
#> 5 1 -1.70 -4.30 2.09093679 -0.6909362 0.3909368 -4.9909362 1
#> 6 1 -6.90 -1.55 -0.24385128 0.8031512 -7.1438513 -0.7468488 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4520 -37150 7625
#> initial value 998.131940
#> iter 2 value 843.098724
#> iter 3 value 841.898313
#> iter 4 value 838.707941
#> iter 5 value 786.695234
#> iter 6 value 777.186229
#> iter 7 value 775.679939
#> iter 8 value 775.653690
#> iter 9 value 775.653460
#> iter 10 value 775.653284
#> iter 10 value 775.653283
#> iter 11 value 775.653255
#> iter 12 value 775.653225
#> iter 12 value 775.653225
#> iter 12 value 775.653217
#> final value 775.653217
#> converged
#> This is Run number 118
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.7345434 -0.9716435 0.3845434 -13.1716435 1
#> 2 1 -6.20 -3.90 2.6798949 -0.4213632 -3.5201051 -4.3213632 1
#> 3 1 -14.20 -5.80 -0.2692402 -0.4905069 -14.4692402 -6.2905069 2
#> 4 1 -2.10 -13.20 -0.6984046 0.5068236 -2.7984046 -12.6931764 1
#> 5 1 -1.70 -4.30 0.5454713 0.1233905 -1.1545287 -4.1766095 1
#> 6 1 -6.90 -1.55 -0.9141432 2.3300929 -7.8141432 0.7800929 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5520 -37075 6150
#> initial value 998.131940
#> iter 2 value 851.968660
#> iter 3 value 843.755045
#> iter 4 value 842.522639
#> iter 5 value 800.924950
#> iter 6 value 792.633830
#> iter 7 value 790.167799
#> iter 8 value 790.071787
#> iter 9 value 790.070333
#> iter 10 value 790.070250
#> iter 11 value 790.069994
#> iter 12 value 790.069742
#> iter 12 value 790.069742
#> iter 12 value 790.069742
#> final value 790.069742
#> converged
#> This is Run number 119
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.0366815 -0.09483435 -0.3133185 -12.294834 1
#> 2 1 -6.20 -3.90 0.1135647 0.87455300 -6.0864353 -3.025447 2
#> 3 1 -14.20 -5.80 -0.7157262 -1.27910309 -14.9157262 -7.079103 2
#> 4 1 -2.10 -13.20 0.2852741 0.02788709 -1.8147259 -13.172113 1
#> 5 1 -1.70 -4.30 -0.3721056 0.20768438 -2.0721056 -4.092316 1
#> 6 1 -6.90 -1.55 -0.2523304 -0.26971477 -7.1523304 -1.819715 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4760 -39125 7250
#> initial value 998.131940
#> iter 2 value 817.237940
#> iter 3 value 811.744572
#> iter 4 value 806.499551
#> iter 5 value 762.577763
#> iter 6 value 752.455199
#> iter 7 value 750.990088
#> iter 8 value 750.962768
#> iter 9 value 750.962742
#> iter 10 value 750.962661
#> iter 10 value 750.962660
#> iter 10 value 750.962654
#> final value 750.962654
#> converged
#> This is Run number 120
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.24027988 0.5732353 -1.109720 -11.626765 1
#> 2 1 -6.20 -3.90 -0.48024159 -0.4890192 -6.680242 -4.389019 2
#> 3 1 -14.20 -5.80 -0.38233676 -0.2497660 -14.582337 -6.049766 2
#> 4 1 -2.10 -13.20 -0.64242042 -0.5240717 -2.742420 -13.724072 1
#> 5 1 -1.70 -4.30 -0.09939448 2.2864335 -1.799394 -2.013567 1
#> 6 1 -6.90 -1.55 1.33511071 -1.1720366 -5.564889 -2.722037 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3400 -36150 8950
#> initial value 998.131940
#> iter 2 value 846.639551
#> iter 3 value 845.781297
#> iter 4 value 840.673805
#> iter 5 value 781.963073
#> iter 6 value 773.082551
#> iter 7 value 771.388196
#> iter 8 value 771.366187
#> iter 9 value 771.366155
#> iter 10 value 771.366114
#> iter 11 value 771.366097
#> iter 11 value 771.366093
#> iter 11 value 771.366093
#> final value 771.366093
#> converged
#> This is Run number 121
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.04222054 -0.2485311 -2.392221 -12.4485311 1
#> 2 1 -6.20 -3.90 -1.03776776 2.6307776 -7.237768 -1.2692224 2
#> 3 1 -14.20 -5.80 0.58557080 -1.1741697 -13.614429 -6.9741697 2
#> 4 1 -2.10 -13.20 0.34353713 1.4942259 -1.756463 -11.7057741 1
#> 5 1 -1.70 -4.30 0.51756185 2.9132265 -1.182438 -1.3867735 1
#> 6 1 -6.90 -1.55 -0.19531985 0.7059419 -7.095320 -0.8440581 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5340 -37175 6775
#> initial value 998.131940
#> iter 2 value 847.612138
#> iter 3 value 837.776639
#> iter 4 value 836.702336
#> iter 5 value 795.650996
#> iter 6 value 787.253424
#> iter 7 value 785.231997
#> iter 8 value 785.154154
#> iter 9 value 785.152942
#> iter 10 value 785.152926
#> iter 11 value 785.152663
#> iter 12 value 785.152311
#> iter 12 value 785.152311
#> iter 12 value 785.152311
#> final value 785.152311
#> converged
#> This is Run number 122
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.0016892 2.3143741 -1.3483108 -9.885626 1
#> 2 1 -6.20 -3.90 1.6101777 1.2950576 -4.5898223 -2.604942 2
#> 3 1 -14.20 -5.80 1.9642354 -0.2866202 -12.2357646 -6.086620 2
#> 4 1 -2.10 -13.20 1.2871474 1.0206118 -0.8128526 -12.179388 1
#> 5 1 -1.70 -4.30 1.1514761 0.5088446 -0.5485239 -3.791155 1
#> 6 1 -6.90 -1.55 0.8105237 -0.3219842 -6.0894763 -1.871984 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4980 -38725 7325
#> initial value 998.131940
#> iter 2 value 822.853584
#> iter 3 value 819.655096
#> iter 4 value 816.069924
#> iter 5 value 770.295687
#> iter 6 value 760.245544
#> iter 7 value 758.785174
#> iter 8 value 758.757404
#> iter 9 value 758.757151
#> iter 10 value 758.757124
#> iter 10 value 758.757120
#> iter 10 value 758.757117
#> final value 758.757117
#> converged
#> This is Run number 123
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.1505136 5.677472 -2.5005136 -6.522528 1
#> 2 1 -6.20 -3.90 3.1014103 -1.040188 -3.0985897 -4.940188 1
#> 3 1 -14.20 -5.80 0.9785421 1.629698 -13.2214579 -4.170302 2
#> 4 1 -2.10 -13.20 2.5095816 2.671151 0.4095816 -10.528849 1
#> 5 1 -1.70 -4.30 0.5502141 1.907676 -1.1497859 -2.392324 1
#> 6 1 -6.90 -1.55 -0.6353017 1.189380 -7.5353017 -0.360620 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4540 -35825 7625
#> initial value 998.131940
#> iter 2 value 860.231791
#> iter 3 value 847.487802
#> iter 4 value 846.292879
#> iter 5 value 802.670157
#> iter 6 value 794.836996
#> iter 7 value 793.374416
#> iter 8 value 793.326133
#> iter 9 value 793.325412
#> iter 10 value 793.325246
#> iter 11 value 793.325043
#> iter 12 value 793.324920
#> iter 12 value 793.324920
#> iter 12 value 793.324920
#> final value 793.324920
#> converged
#> This is Run number 124
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.9123980 0.38570156 -3.262398 -11.814298 1
#> 2 1 -6.20 -3.90 1.5498398 -0.09666985 -4.650160 -3.996670 2
#> 3 1 -14.20 -5.80 -1.3184796 -0.01495153 -15.518480 -5.814952 2
#> 4 1 -2.10 -13.20 -1.4884834 0.19432379 -3.588483 -13.005676 1
#> 5 1 -1.70 -4.30 -0.4161544 0.60705575 -2.116154 -3.692944 1
#> 6 1 -6.90 -1.55 0.1930911 0.20397130 -6.706909 -1.346029 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4100 -35750 8150
#> initial value 998.131940
#> iter 2 value 857.706440
#> iter 3 value 842.715591
#> iter 4 value 841.057462
#> iter 5 value 797.154901
#> iter 6 value 789.448607
#> iter 7 value 788.193302
#> iter 8 value 788.149515
#> iter 9 value 788.148832
#> iter 10 value 788.148700
#> iter 11 value 788.148568
#> iter 12 value 788.148471
#> iter 12 value 788.148471
#> iter 12 value 788.148471
#> final value 788.148471
#> converged
#> This is Run number 125
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.7573370 0.3504043 -1.592663 -11.849596 1
#> 2 1 -6.20 -3.90 -0.4384079 1.3770454 -6.638408 -2.522955 2
#> 3 1 -14.20 -5.80 -0.8598882 1.3788316 -15.059888 -4.421168 2
#> 4 1 -2.10 -13.20 -0.5838965 0.5965356 -2.683897 -12.603464 1
#> 5 1 -1.70 -4.30 -0.5884171 -0.4921006 -2.288417 -4.792101 1
#> 6 1 -6.90 -1.55 0.2653371 1.2149100 -6.634663 -0.335090 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4760 -37225 7175
#> initial value 998.131940
#> iter 2 value 844.736737
#> iter 3 value 843.548964
#> iter 4 value 840.610099
#> iter 5 value 789.840495
#> iter 6 value 780.231657
#> iter 7 value 778.710434
#> iter 8 value 778.680882
#> iter 9 value 778.680793
#> iter 10 value 778.680467
#> iter 10 value 778.680467
#> iter 11 value 778.680437
#> iter 11 value 778.680433
#> iter 11 value 778.680432
#> final value 778.680432
#> converged
#> This is Run number 126
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.6756415 0.7055207 -3.0256415 -11.494479 1
#> 2 1 -6.20 -3.90 0.3086389 0.6147182 -5.8913611 -3.285282 2
#> 3 1 -14.20 -5.80 -0.2258853 0.2674702 -14.4258853 -5.532530 2
#> 4 1 -2.10 -13.20 -0.2322854 0.5821128 -2.3322854 -12.617887 1
#> 5 1 -1.70 -4.30 1.8727015 0.9561527 0.1727015 -3.343847 1
#> 6 1 -6.90 -1.55 1.3664775 -0.8963681 -5.5335225 -2.446368 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5220 -36125 7750
#> initial value 998.131940
#> iter 2 value 855.878662
#> iter 3 value 843.854416
#> iter 4 value 843.718269
#> iter 5 value 801.873280
#> iter 6 value 793.881447
#> iter 7 value 792.606571
#> iter 8 value 792.571120
#> iter 9 value 792.570679
#> iter 10 value 792.570522
#> iter 11 value 792.570287
#> iter 12 value 792.570150
#> iter 12 value 792.570150
#> iter 12 value 792.570150
#> final value 792.570150
#> converged
#> This is Run number 127
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.18239791 5.014974 -2.532398 -7.185026 1
#> 2 1 -6.20 -3.90 -0.09821512 1.093688 -6.298215 -2.806312 2
#> 3 1 -14.20 -5.80 1.70352244 1.032816 -12.496478 -4.767184 2
#> 4 1 -2.10 -13.20 -0.39841541 2.254206 -2.498415 -10.945794 1
#> 5 1 -1.70 -4.30 -1.34278337 1.479273 -3.042783 -2.820727 2
#> 6 1 -6.90 -1.55 0.94808958 -1.994770 -5.951910 -3.544770 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4820 -38050 8150
#> initial value 998.131940
#> iter 2 value 827.656968
#> iter 3 value 826.516513
#> iter 4 value 824.225901
#> iter 5 value 774.178354
#> iter 6 value 764.457903
#> iter 7 value 762.963210
#> iter 8 value 762.938271
#> iter 9 value 762.937932
#> iter 10 value 762.937729
#> iter 11 value 762.937705
#> iter 12 value 762.937623
#> iter 12 value 762.937623
#> iter 12 value 762.937623
#> final value 762.937623
#> converged
#> This is Run number 128
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 3.1651854 0.1840418 0.8151854 -12.0159582 1
#> 2 1 -6.20 -3.90 -0.4119567 1.5007353 -6.6119567 -2.3992647 2
#> 3 1 -14.20 -5.80 1.3404447 -0.5106557 -12.8595553 -6.3106557 2
#> 4 1 -2.10 -13.20 -0.7945385 3.4739843 -2.8945385 -9.7260157 1
#> 5 1 -1.70 -4.30 0.5125475 0.5148778 -1.1874525 -3.7851222 1
#> 6 1 -6.90 -1.55 -0.2390756 0.6835191 -7.1390756 -0.8664809 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5040 -38375 8250
#> initial value 998.131940
#> iter 2 value 822.437503
#> iter 3 value 821.473704
#> iter 4 value 819.788360
#> iter 5 value 770.696397
#> iter 6 value 760.886765
#> iter 7 value 759.398912
#> iter 8 value 759.374124
#> iter 9 value 759.373895
#> iter 10 value 759.373687
#> iter 10 value 759.373685
#> iter 10 value 759.373683
#> final value 759.373683
#> converged
#> This is Run number 129
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.030228998 -0.81525133 -2.319771 -13.015251 1
#> 2 1 -6.20 -3.90 -0.002161270 0.46314506 -6.202161 -3.436855 2
#> 3 1 -14.20 -5.80 -0.005469986 3.18949727 -14.205470 -2.610503 2
#> 4 1 -2.10 -13.20 -1.801684136 -0.36667101 -3.901684 -13.566671 1
#> 5 1 -1.70 -4.30 -1.152923130 0.24832529 -2.852923 -4.051675 1
#> 6 1 -6.90 -1.55 -0.134797343 0.03610368 -7.034797 -1.513896 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4980 -37875 7950
#> initial value 998.131940
#> iter 2 value 831.398350
#> iter 3 value 830.960214
#> iter 4 value 829.141569
#> iter 5 value 778.892601
#> iter 6 value 769.149129
#> iter 7 value 767.656557
#> iter 8 value 767.629426
#> iter 9 value 767.628970
#> iter 10 value 767.628849
#> iter 11 value 767.628809
#> iter 12 value 767.628684
#> iter 12 value 767.628684
#> iter 12 value 767.628684
#> final value 767.628684
#> converged
#> This is Run number 130
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.5125512 0.5868629 0.1625512 -11.61313705 1
#> 2 1 -6.20 -3.90 -0.1876644 3.3903967 -6.3876644 -0.50960325 2
#> 3 1 -14.20 -5.80 0.3928805 -0.8712741 -13.8071195 -6.67127413 2
#> 4 1 -2.10 -13.20 -0.2093922 -1.1212865 -2.3093922 -14.32128651 1
#> 5 1 -1.70 -4.30 0.1461210 1.6551210 -1.5538790 -2.64487902 1
#> 6 1 -6.90 -1.55 0.3450829 1.4968477 -6.5549171 -0.05315232 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5120 -39025 7450
#> initial value 998.131940
#> iter 2 value 817.736729
#> iter 3 value 814.728745
#> iter 4 value 811.574235
#> iter 5 value 766.560236
#> iter 6 value 756.464096
#> iter 7 value 755.030437
#> iter 8 value 755.003261
#> iter 9 value 755.002919
#> iter 10 value 755.002882
#> iter 10 value 755.002879
#> iter 11 value 755.002849
#> iter 12 value 755.002742
#> iter 12 value 755.002735
#> iter 13 value 755.002720
#> iter 13 value 755.002720
#> iter 13 value 755.002719
#> final value 755.002719
#> converged
#> This is Run number 131
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.2060631 -0.01558264 -2.556063 -12.2155826 1
#> 2 1 -6.20 -3.90 0.7707421 0.77263842 -5.429258 -3.1273616 2
#> 3 1 -14.20 -5.80 1.6044850 1.24227409 -12.595515 -4.5577259 2
#> 4 1 -2.10 -13.20 -1.2009451 0.69290972 -3.300945 -12.5070903 1
#> 5 1 -1.70 -4.30 3.1853672 1.64548808 1.485367 -2.6545119 1
#> 6 1 -6.90 -1.55 2.4732815 2.01945264 -4.426718 0.4694526 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5440 -38275 6150
#> initial value 998.131940
#> iter 2 value 835.402757
#> iter 3 value 833.206642
#> iter 4 value 830.291329
#> iter 5 value 785.227006
#> iter 6 value 775.168278
#> iter 7 value 773.476424
#> iter 8 value 773.433453
#> iter 9 value 773.433372
#> iter 10 value 773.433341
#> iter 10 value 773.433332
#> iter 10 value 773.433332
#> final value 773.433332
#> converged
#> This is Run number 132
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.9666891 -0.3345445 -0.3833109 -12.534544 1
#> 2 1 -6.20 -3.90 0.3052846 1.6229937 -5.8947154 -2.277006 2
#> 3 1 -14.20 -5.80 -0.4057516 3.5136987 -14.6057516 -2.286301 2
#> 4 1 -2.10 -13.20 0.5944379 0.8094452 -1.5055621 -12.390555 1
#> 5 1 -1.70 -4.30 -0.1204873 3.1016291 -1.8204873 -1.198371 2
#> 6 1 -6.90 -1.55 2.2216167 2.5777421 -4.6783833 1.027742 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5620 -38500 6550
#> initial value 998.131940
#> iter 2 value 830.215398
#> iter 3 value 828.997923
#> iter 4 value 826.987284
#> iter 5 value 781.797237
#> iter 6 value 771.660622
#> iter 7 value 770.079535
#> iter 8 value 770.040349
#> iter 9 value 770.040211
#> iter 10 value 770.039934
#> iter 10 value 770.039934
#> iter 11 value 770.039920
#> iter 12 value 770.039869
#> iter 12 value 770.039869
#> iter 12 value 770.039864
#> final value 770.039864
#> converged
#> This is Run number 133
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.8296372 6.78312244 -3.1796372 -5.416878 1
#> 2 1 -6.20 -3.90 1.3798955 1.40186349 -4.8201045 -2.498137 2
#> 3 1 -14.20 -5.80 -0.1950692 0.04042476 -14.3950692 -5.759575 2
#> 4 1 -2.10 -13.20 2.9033421 1.47087436 0.8033421 -11.729126 1
#> 5 1 -1.70 -4.30 1.1291111 0.30111061 -0.5708889 -3.998889 1
#> 6 1 -6.90 -1.55 0.5369565 -0.15209997 -6.3630435 -1.702100 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5680 -41450 8950
#> initial value 998.131940
#> iter 2 value 769.549423
#> iter 3 value 764.266537
#> iter 4 value 763.046060
#> iter 5 value 724.028308
#> iter 6 value 714.649269
#> iter 7 value 713.202737
#> iter 8 value 713.170499
#> iter 9 value 713.170160
#> iter 10 value 713.169964
#> iter 11 value 713.169819
#> iter 12 value 713.169790
#> iter 12 value 713.169790
#> iter 12 value 713.169790
#> final value 713.169790
#> converged
#> This is Run number 134
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.9047207 1.4634517 -1.4452793 -10.736548 1
#> 2 1 -6.20 -3.90 0.5698449 -0.2955863 -5.6301551 -4.195586 2
#> 3 1 -14.20 -5.80 -0.9076158 -0.2627875 -15.1076158 -6.062787 2
#> 4 1 -2.10 -13.20 1.6993564 1.0076115 -0.4006436 -12.192388 1
#> 5 1 -1.70 -4.30 -0.2463560 -0.7759151 -1.9463560 -5.075915 1
#> 6 1 -6.90 -1.55 2.2631300 -0.1042252 -4.6368700 -1.654225 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4260 -37125 8625
#> initial value 998.131940
#> iter 2 value 837.048821
#> iter 3 value 836.745326
#> iter 4 value 833.840122
#> iter 5 value 779.375516
#> iter 6 value 770.062500
#> iter 7 value 768.496760
#> iter 8 value 768.474441
#> iter 9 value 768.474361
#> iter 10 value 768.474109
#> iter 10 value 768.474108
#> iter 10 value 768.474102
#> final value 768.474102
#> converged
#> This is Run number 135
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.00087328 -0.1231122 -1.3491267 -12.323112 1
#> 2 1 -6.20 -3.90 0.17767438 0.1621301 -6.0223256 -3.737870 2
#> 3 1 -14.20 -5.80 -0.05462735 0.9400620 -14.2546273 -4.859938 2
#> 4 1 -2.10 -13.20 0.87181329 -0.9300294 -1.2281867 -14.130029 1
#> 5 1 -1.70 -4.30 0.90455918 -0.6954916 -0.7954408 -4.995492 1
#> 6 1 -6.90 -1.55 2.42433845 0.5299663 -4.4756615 -1.020034 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5020 -38125 7775
#> initial value 998.131940
#> iter 2 value 828.935460
#> iter 3 value 827.879282
#> iter 4 value 825.755609
#> iter 5 value 776.766571
#> iter 6 value 766.928224
#> iter 7 value 765.450075
#> iter 8 value 765.422453
#> iter 9 value 765.422013
#> iter 10 value 765.421851
#> iter 11 value 765.421827
#> iter 12 value 765.421719
#> iter 12 value 765.421719
#> iter 12 value 765.421719
#> final value 765.421719
#> converged
#> This is Run number 136
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.6430989 -0.4755804 -3.993099 -12.675580 1
#> 2 1 -6.20 -3.90 0.2748011 0.6350398 -5.925199 -3.264960 2
#> 3 1 -14.20 -5.80 -0.1934580 0.9159575 -14.393458 -4.884043 2
#> 4 1 -2.10 -13.20 0.4094289 -0.9723584 -1.690571 -14.172358 1
#> 5 1 -1.70 -4.30 -1.0324143 0.9206890 -2.732414 -3.379311 1
#> 6 1 -6.90 -1.55 0.4380969 0.4666273 -6.461903 -1.083373 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4680 -38425 7975
#> initial value 998.131940
#> iter 2 value 823.315184
#> iter 3 value 820.406064
#> iter 4 value 816.879183
#> iter 5 value 768.691853
#> iter 6 value 758.880773
#> iter 7 value 757.401071
#> iter 8 value 757.376619
#> iter 9 value 757.376431
#> iter 10 value 757.376274
#> iter 10 value 757.376274
#> iter 11 value 757.376237
#> iter 12 value 757.376144
#> iter 12 value 757.376142
#> iter 12 value 757.376137
#> final value 757.376137
#> converged
#> This is Run number 137
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.9561977 0.5583094 -1.393802 -11.641691 1
#> 2 1 -6.20 -3.90 -0.5205921 -1.2038903 -6.720592 -5.103890 2
#> 3 1 -14.20 -5.80 -0.3548745 2.8513641 -14.554874 -2.948636 2
#> 4 1 -2.10 -13.20 0.4397753 0.5957704 -1.660225 -12.604230 1
#> 5 1 -1.70 -4.30 0.4915706 2.8890493 -1.208429 -1.410951 1
#> 6 1 -6.90 -1.55 1.5699834 0.1340258 -5.330017 -1.415974 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4940 -36800 8475
#> initial value 998.131940
#> iter 2 value 842.664165
#> iter 3 value 827.938383
#> iter 4 value 827.675112
#> iter 5 value 787.477294
#> iter 6 value 779.390695
#> iter 7 value 778.392237
#> iter 8 value 778.358841
#> iter 9 value 778.358297
#> iter 10 value 778.358098
#> iter 11 value 778.357809
#> iter 12 value 778.357634
#> iter 12 value 778.357634
#> iter 12 value 778.357634
#> final value 778.357634
#> converged
#> This is Run number 138
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.70526404 0.4645009 -3.055264 -11.735499 1
#> 2 1 -6.20 -3.90 3.25032451 0.8835938 -2.949675 -3.016406 1
#> 3 1 -14.20 -5.80 -0.14790538 2.0205617 -14.347905 -3.779438 2
#> 4 1 -2.10 -13.20 -0.46639417 -0.4347895 -2.566394 -13.634790 1
#> 5 1 -1.70 -4.30 -0.06023598 2.6715640 -1.760236 -1.628436 2
#> 6 1 -6.90 -1.55 -0.65016575 0.2658678 -7.550166 -1.284132 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3780 -35975 9000
#> initial value 998.131940
#> iter 2 value 849.012180
#> iter 3 value 830.740112
#> iter 4 value 828.998365
#> iter 5 value 786.006982
#> iter 6 value 778.506680
#> iter 7 value 777.549484
#> iter 8 value 777.512130
#> iter 9 value 777.511511
#> iter 10 value 777.511396
#> iter 11 value 777.511282
#> iter 12 value 777.511191
#> iter 12 value 777.511191
#> iter 12 value 777.511191
#> final value 777.511191
#> converged
#> This is Run number 139
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.6179669 0.4138802 0.2679669 -11.7861198 1
#> 2 1 -6.20 -3.90 0.5167349 0.5897659 -5.6832651 -3.3102341 2
#> 3 1 -14.20 -5.80 0.9242489 0.2471655 -13.2757511 -5.5528345 2
#> 4 1 -2.10 -13.20 -0.4122460 -0.8206181 -2.5122460 -14.0206181 1
#> 5 1 -1.70 -4.30 -0.5957727 1.1843824 -2.2957727 -3.1156176 1
#> 6 1 -6.90 -1.55 1.3258765 0.5762152 -5.5741235 -0.9737848 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4660 -36975 9725
#> initial value 998.131940
#> iter 2 value 831.467443
#> iter 3 value 812.173084
#> iter 4 value 812.114170
#> iter 5 value 773.622420
#> iter 6 value 766.098383
#> iter 7 value 765.473737
#> iter 8 value 765.450868
#> iter 9 value 765.450491
#> iter 10 value 765.450399
#> iter 11 value 765.450314
#> iter 12 value 765.449597
#> iter 12 value 765.449597
#> iter 12 value 765.449597
#> final value 765.449597
#> converged
#> This is Run number 140
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.9020177 0.6346227 -0.4479823 -11.56537732 1
#> 2 1 -6.20 -3.90 0.5507520 -1.0641570 -5.6492480 -4.96415703 2
#> 3 1 -14.20 -5.80 2.3930554 0.7945792 -11.8069446 -5.00542078 2
#> 4 1 -2.10 -13.20 -0.8874251 1.9348575 -2.9874251 -11.26514254 1
#> 5 1 -1.70 -4.30 -0.9854361 2.6974936 -2.6854361 -1.60250643 2
#> 6 1 -6.90 -1.55 -0.6140004 1.6050605 -7.5140004 0.05506046 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4300 -34775 8050
#> initial value 998.131940
#> iter 2 value 870.164350
#> iter 3 value 856.293449
#> iter 4 value 855.545627
#> iter 5 value 810.941549
#> iter 6 value 803.629706
#> iter 7 value 802.478291
#> iter 8 value 802.447748
#> iter 9 value 802.447341
#> iter 10 value 802.447198
#> iter 11 value 802.447014
#> iter 12 value 802.446919
#> iter 12 value 802.446919
#> iter 12 value 802.446919
#> final value 802.446919
#> converged
#> This is Run number 141
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.14278495 0.3770386 -3.492785 -11.8229614 1
#> 2 1 -6.20 -3.90 0.27670620 0.1870049 -5.923294 -3.7129951 2
#> 3 1 -14.20 -5.80 0.44130386 0.8183340 -13.758696 -4.9816660 2
#> 4 1 -2.10 -13.20 -1.21620150 0.7979969 -3.316201 -12.4020031 1
#> 5 1 -1.70 -4.30 0.03407753 -0.6738035 -1.665922 -4.9738035 1
#> 6 1 -6.90 -1.55 -0.68220666 1.3679736 -7.582207 -0.1820264 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4920 -37500 8625
#> initial value 998.131940
#> iter 2 value 832.272898
#> iter 3 value 816.808748
#> iter 4 value 816.371791
#> iter 5 value 777.391662
#> iter 6 value 769.157645
#> iter 7 value 768.182523
#> iter 8 value 768.143212
#> iter 9 value 768.142506
#> iter 10 value 768.142431
#> iter 11 value 768.142107
#> iter 12 value 768.141761
#> iter 12 value 768.141761
#> iter 12 value 768.141761
#> final value 768.141761
#> converged
#> This is Run number 142
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.50553038 0.4630404 -0.8444696 -11.73695960 1
#> 2 1 -6.20 -3.90 1.66739524 -0.5079506 -4.5326048 -4.40795059 2
#> 3 1 -14.20 -5.80 1.28493694 -0.6124031 -12.9150631 -6.41240310 2
#> 4 1 -2.10 -13.20 -1.05449759 -0.5518868 -3.1544976 -13.75188683 1
#> 5 1 -1.70 -4.30 -0.02537667 -0.3351633 -1.7253767 -4.63516330 1
#> 6 1 -6.90 -1.55 -0.80031321 1.6022778 -7.7003132 0.05227783 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4000 -35400 8625
#> initial value 998.131940
#> iter 2 value 858.861888
#> iter 3 value 842.487832
#> iter 4 value 841.290578
#> iter 5 value 797.668529
#> iter 6 value 790.233658
#> iter 7 value 789.222911
#> iter 8 value 789.190067
#> iter 9 value 789.189544
#> iter 10 value 789.189402
#> iter 11 value 789.189241
#> iter 12 value 789.189138
#> iter 12 value 789.189138
#> iter 12 value 789.189138
#> final value 789.189138
#> converged
#> This is Run number 143
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.6184714 -0.3382554 -2.968471 -12.538255 1
#> 2 1 -6.20 -3.90 0.7646971 -0.1450559 -5.435303 -4.045056 2
#> 3 1 -14.20 -5.80 0.3458026 3.0456260 -13.854197 -2.754374 2
#> 4 1 -2.10 -13.20 2.2147020 0.2873064 0.114702 -12.912694 1
#> 5 1 -1.70 -4.30 0.1519505 -1.0078894 -1.548049 -5.307889 1
#> 6 1 -6.90 -1.55 1.6379028 -1.3691748 -5.262097 -2.919175 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4160 -38350 7825
#> initial value 998.131940
#> iter 2 value 824.913023
#> iter 3 value 818.903891
#> iter 4 value 812.780168
#> iter 5 value 765.037637
#> iter 6 value 755.237644
#> iter 7 value 753.698102
#> iter 8 value 753.673340
#> iter 9 value 753.673307
#> iter 10 value 753.673248
#> iter 10 value 753.673247
#> iter 10 value 753.673246
#> final value 753.673246
#> converged
#> This is Run number 144
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.2182593 1.2888106 -1.131741 -10.911189 1
#> 2 1 -6.20 -3.90 0.6360745 -0.3381205 -5.563925 -4.238121 2
#> 3 1 -14.20 -5.80 0.1174086 1.2771071 -14.082591 -4.522893 2
#> 4 1 -2.10 -13.20 0.2748342 1.0887117 -1.825166 -12.111288 1
#> 5 1 -1.70 -4.30 -0.2984017 3.0752814 -1.998402 -1.224719 2
#> 6 1 -6.90 -1.55 -0.3388118 -0.3731255 -7.238812 -1.923126 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4620 -38300 7275
#> initial value 998.131940
#> iter 2 value 829.147149
#> iter 3 value 824.935211
#> iter 4 value 820.262398
#> iter 5 value 773.221522
#> iter 6 value 763.284370
#> iter 7 value 761.778191
#> iter 8 value 761.750796
#> iter 9 value 761.750689
#> iter 9 value 761.750681
#> iter 9 value 761.750676
#> final value 761.750676
#> converged
#> This is Run number 145
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.3268659 0.9699766 -1.0231341 -11.230023 1
#> 2 1 -6.20 -3.90 1.1918663 -0.6035578 -5.0081337 -4.503558 2
#> 3 1 -14.20 -5.80 1.3489218 -0.6402207 -12.8510782 -6.440221 2
#> 4 1 -2.10 -13.20 -0.3665130 -1.2909765 -2.4665130 -14.490976 1
#> 5 1 -1.70 -4.30 1.1160538 -0.4540840 -0.5839462 -4.754084 1
#> 6 1 -6.90 -1.55 0.3425307 -0.3704554 -6.5574693 -1.920455 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4740 -38375 7575
#> initial value 998.131940
#> iter 2 value 826.440486
#> iter 3 value 823.278824
#> iter 4 value 819.469422
#> iter 5 value 771.968843
#> iter 6 value 762.071114
#> iter 7 value 760.594723
#> iter 8 value 760.568589
#> iter 9 value 760.568336
#> iter 10 value 760.568295
#> iter 10 value 760.568293
#> iter 11 value 760.568271
#> iter 12 value 760.568201
#> iter 12 value 760.568196
#> iter 12 value 760.568191
#> final value 760.568191
#> converged
#> This is Run number 146
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.5394223 -0.2071462 -2.889422 -12.407146 1
#> 2 1 -6.20 -3.90 0.9522201 -0.4635620 -5.247780 -4.363562 2
#> 3 1 -14.20 -5.80 -0.3490752 1.1948801 -14.549075 -4.605120 2
#> 4 1 -2.10 -13.20 0.2681402 0.1396095 -1.831860 -13.060391 1
#> 5 1 -1.70 -4.30 -0.7466344 -0.4892025 -2.446634 -4.789202 1
#> 6 1 -6.90 -1.55 1.2767406 0.1893781 -5.623259 -1.360622 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5120 -38525 7700
#> initial value 998.131940
#> iter 2 value 823.650084
#> iter 3 value 822.032440
#> iter 4 value 819.787231
#> iter 5 value 772.380340
#> iter 6 value 762.424207
#> iter 7 value 760.965158
#> iter 8 value 760.937604
#> iter 9 value 760.937142
#> iter 10 value 760.937061
#> iter 11 value 760.937050
#> iter 12 value 760.936870
#> iter 12 value 760.936870
#> iter 12 value 760.936870
#> final value 760.936870
#> converged
#> This is Run number 147
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.1194239 0.7065336 -2.469424 -11.4934664 1
#> 2 1 -6.20 -3.90 0.5714252 3.0361653 -5.628575 -0.8638347 2
#> 3 1 -14.20 -5.80 -1.6576921 4.7963905 -15.857692 -1.0036095 2
#> 4 1 -2.10 -13.20 -0.1748776 -1.0945564 -2.274878 -14.2945564 1
#> 5 1 -1.70 -4.30 -0.4038719 -1.2277812 -2.103872 -5.5277812 1
#> 6 1 -6.90 -1.55 2.6436938 0.9061712 -4.256306 -0.6438288 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4320 -36625 7850
#> initial value 998.131940
#> iter 2 value 848.593339
#> iter 3 value 848.242790
#> iter 4 value 845.142501
#> iter 5 value 790.778112
#> iter 6 value 781.507868
#> iter 7 value 779.996119
#> iter 8 value 779.971461
#> iter 9 value 779.971194
#> iter 10 value 779.971045
#> iter 10 value 779.971037
#> iter 11 value 779.971022
#> iter 12 value 779.970995
#> iter 12 value 779.970993
#> iter 12 value 779.970993
#> final value 779.970993
#> converged
#> This is Run number 148
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.4262273 -0.09221380 -1.9237727 -12.292214 1
#> 2 1 -6.20 -3.90 -0.1090225 -0.02209498 -6.3090225 -3.922095 2
#> 3 1 -14.20 -5.80 1.0906531 1.71616611 -13.1093469 -4.083834 2
#> 4 1 -2.10 -13.20 1.9494685 -0.85593687 -0.1505315 -14.055937 1
#> 5 1 -1.70 -4.30 1.9366725 -0.62195367 0.2366725 -4.921954 1
#> 6 1 -6.90 -1.55 -1.2505745 -0.53042159 -8.1505745 -2.080422 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4460 -38175 8200
#> initial value 998.131940
#> iter 2 value 825.384956
#> iter 3 value 822.398736
#> iter 4 value 818.535317
#> iter 5 value 769.011261
#> iter 6 value 759.331659
#> iter 7 value 757.820634
#> iter 8 value 757.797106
#> iter 8 value 757.797105
#> final value 757.797105
#> converged
#> This is Run number 149
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.10483817 4.44348215 -2.245162 -7.7565178 1
#> 2 1 -6.20 -3.90 -0.01301967 -1.39831999 -6.213020 -5.2983200 2
#> 3 1 -14.20 -5.80 2.68002284 1.58479132 -11.519977 -4.2152087 2
#> 4 1 -2.10 -13.20 -0.06636276 0.19714875 -2.166363 -13.0028512 1
#> 5 1 -1.70 -4.30 -0.89227643 -0.02349833 -2.592276 -4.3234983 1
#> 6 1 -6.90 -1.55 -1.01066435 1.12761058 -7.910664 -0.4223894 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4600 -36950 8325
#> initial value 998.131940
#> iter 2 value 841.550310
#> iter 3 value 826.572962
#> iter 4 value 825.513733
#> iter 5 value 784.645025
#> iter 6 value 776.519908
#> iter 7 value 775.353038
#> iter 8 value 775.307357
#> iter 9 value 775.306530
#> iter 10 value 775.306348
#> iter 11 value 775.306139
#> iter 12 value 775.305984
#> iter 12 value 775.305984
#> iter 12 value 775.305984
#> final value 775.305984
#> converged
#> This is Run number 150
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.5189499 1.177245 -2.868950 -11.022755 1
#> 2 1 -6.20 -3.90 -0.5969797 0.681197 -6.796980 -3.218803 2
#> 3 1 -14.20 -5.80 0.5800566 -1.161793 -13.619943 -6.961793 2
#> 4 1 -2.10 -13.20 -0.6853525 1.421181 -2.785353 -11.778819 1
#> 5 1 -1.70 -4.30 -0.9593668 1.158412 -2.659367 -3.141588 1
#> 6 1 -6.90 -1.55 -0.5064684 -0.152482 -7.406468 -1.702482 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4700 -35875 7000
#> initial value 998.131940
#> iter 2 value 863.145124
#> iter 3 value 852.175156
#> iter 4 value 850.713457
#> iter 5 value 806.541348
#> iter 6 value 798.635861
#> iter 7 value 796.812716
#> iter 8 value 796.750468
#> iter 9 value 796.749589
#> iter 10 value 796.749439
#> iter 11 value 796.749247
#> iter 12 value 796.749130
#> iter 12 value 796.749130
#> iter 12 value 796.749130
#> final value 796.749130
#> converged
#> This is Run number 151
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.7441344 0.20432689 -3.0941344 -11.995673 1
#> 2 1 -6.20 -3.90 -0.5318303 -0.24182888 -6.7318303 -4.141829 2
#> 3 1 -14.20 -5.80 -0.7929602 -0.59529334 -14.9929602 -6.395293 2
#> 4 1 -2.10 -13.20 -0.3592985 0.01398475 -2.4592985 -13.186015 1
#> 5 1 -1.70 -4.30 1.9341122 -1.09345624 0.2341122 -5.393456 1
#> 6 1 -6.90 -1.55 0.7748980 0.07166224 -6.1251020 -1.478338 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4060 -36350 8100
#> initial value 998.131940
#> iter 2 value 850.414803
#> iter 3 value 850.145300
#> iter 4 value 846.644174
#> iter 5 value 790.728724
#> iter 6 value 781.616661
#> iter 7 value 780.083904
#> iter 8 value 780.061170
#> iter 9 value 780.060932
#> iter 10 value 780.060902
#> iter 10 value 780.060895
#> iter 11 value 780.060882
#> iter 12 value 780.060851
#> iter 12 value 780.060846
#> iter 13 value 780.060826
#> iter 13 value 780.060825
#> iter 13 value 780.060825
#> final value 780.060825
#> converged
#> This is Run number 152
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.93230329 1.3069402 -1.417697 -10.893060 1
#> 2 1 -6.20 -3.90 0.07570483 2.2447643 -6.124295 -1.655236 2
#> 3 1 -14.20 -5.80 -0.79042720 0.4042427 -14.990427 -5.395757 2
#> 4 1 -2.10 -13.20 1.27540399 0.4691054 -0.824596 -12.730895 1
#> 5 1 -1.70 -4.30 0.06185483 0.1486429 -1.638145 -4.151357 1
#> 6 1 -6.90 -1.55 0.47701449 0.3032351 -6.422986 -1.246765 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4600 -37325 7250
#> initial value 998.131940
#> iter 2 value 842.895373
#> iter 3 value 840.877081
#> iter 4 value 837.322036
#> iter 5 value 786.775051
#> iter 6 value 777.144147
#> iter 7 value 775.623138
#> iter 8 value 775.595142
#> iter 9 value 775.595084
#> iter 10 value 775.594883
#> iter 10 value 775.594883
#> iter 11 value 775.594856
#> iter 12 value 775.594824
#> iter 12 value 775.594822
#> iter 12 value 775.594819
#> final value 775.594819
#> converged
#> This is Run number 153
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.1118740 0.04302934 -0.2381260 -12.1569707 1
#> 2 1 -6.20 -3.90 0.1858324 2.25471676 -6.0141676 -1.6452832 2
#> 3 1 -14.20 -5.80 0.4138544 0.93022643 -13.7861456 -4.8697736 2
#> 4 1 -2.10 -13.20 0.4979159 -0.82537069 -1.6020841 -14.0253707 1
#> 5 1 -1.70 -4.30 1.0204545 0.00400891 -0.6795455 -4.2959911 1
#> 6 1 -6.90 -1.55 0.3199941 2.37460107 -6.5800059 0.8246011 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4680 -38075 8275
#> initial value 998.131940
#> iter 2 value 826.458819
#> iter 3 value 824.873127
#> iter 4 value 822.184859
#> iter 5 value 771.984770
#> iter 6 value 762.308981
#> iter 7 value 760.804265
#> iter 8 value 760.780355
#> iter 9 value 760.780203
#> iter 10 value 760.779923
#> iter 10 value 760.779913
#> iter 11 value 760.779876
#> iter 12 value 760.779818
#> iter 13 value 760.779800
#> iter 14 value 760.779787
#> iter 14 value 760.779786
#> iter 14 value 760.779786
#> final value 760.779786
#> converged
#> This is Run number 154
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.1735392 0.2238088 -2.523539 -11.9761912 1
#> 2 1 -6.20 -3.90 1.5232323 -0.6347377 -4.676768 -4.5347377 2
#> 3 1 -14.20 -5.80 -0.3944713 1.7222367 -14.594471 -4.0777633 2
#> 4 1 -2.10 -13.20 0.1301620 0.9069740 -1.969838 -12.2930260 1
#> 5 1 -1.70 -4.30 -0.6919609 -0.6884563 -2.391961 -4.9884563 1
#> 6 1 -6.90 -1.55 1.9993664 0.9811121 -4.900634 -0.5688879 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3620 -35750 7675
#> initial value 998.131940
#> iter 2 value 860.011147
#> iter 3 value 857.760542
#> iter 4 value 852.940924
#> iter 5 value 795.938604
#> iter 6 value 786.987105
#> iter 7 value 785.431473
#> iter 8 value 785.409650
#> iter 9 value 785.409582
#> iter 10 value 785.409569
#> iter 10 value 785.409568
#> iter 11 value 785.409551
#> iter 11 value 785.409545
#> iter 11 value 785.409545
#> final value 785.409545
#> converged
#> This is Run number 155
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.05910728 0.1062182 -2.2908927 -12.093782 1
#> 2 1 -6.20 -3.90 0.77823749 2.7720667 -5.4217625 -1.127933 2
#> 3 1 -14.20 -5.80 -0.38819841 0.4615471 -14.5881984 -5.338453 2
#> 4 1 -2.10 -13.20 2.47880267 0.6437724 0.3788027 -12.556228 1
#> 5 1 -1.70 -4.30 -0.06780830 0.7259937 -1.7678083 -3.574006 1
#> 6 1 -6.90 -1.55 0.54705140 -1.5298314 -6.3529486 -3.079831 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4520 -36775 7775
#> initial value 998.131940
#> iter 2 value 847.206680
#> iter 3 value 833.610987
#> iter 4 value 831.869614
#> iter 5 value 789.752415
#> iter 6 value 781.566132
#> iter 7 value 780.083773
#> iter 8 value 780.026007
#> iter 9 value 780.025059
#> iter 10 value 780.024918
#> iter 11 value 780.024785
#> iter 12 value 780.024675
#> iter 12 value 780.024675
#> iter 12 value 780.024675
#> final value 780.024675
#> converged
#> This is Run number 156
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.3987670 1.1128905 0.0487670 -11.0871095 1
#> 2 1 -6.20 -3.90 1.3249180 3.2559825 -4.8750820 -0.6440175 2
#> 3 1 -14.20 -5.80 0.7266445 0.6275957 -13.4733555 -5.1724043 2
#> 4 1 -2.10 -13.20 1.8858861 -0.5076787 -0.2141139 -13.7076787 1
#> 5 1 -1.70 -4.30 -1.1072024 0.9881830 -2.8072024 -3.3118170 1
#> 6 1 -6.90 -1.55 -0.1339105 -0.6612467 -7.0339105 -2.2112467 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4220 -36800 9400
#> initial value 998.131940
#> iter 2 value 835.966053
#> iter 3 value 817.010710
#> iter 4 value 816.221308
#> iter 5 value 775.992142
#> iter 6 value 768.374918
#> iter 7 value 767.590411
#> iter 8 value 767.556999
#> iter 9 value 767.556480
#> iter 10 value 767.556233
#> iter 11 value 767.555952
#> iter 12 value 767.555864
#> iter 12 value 767.555864
#> iter 12 value 767.555864
#> final value 767.555864
#> converged
#> This is Run number 157
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.00133360 0.7250452 -3.351334 -11.474955 1
#> 2 1 -6.20 -3.90 1.32483969 -0.5722736 -4.875160 -4.472274 2
#> 3 1 -14.20 -5.80 3.76193506 -0.6517790 -10.438065 -6.451779 2
#> 4 1 -2.10 -13.20 -0.40508367 -1.0466148 -2.505084 -14.246615 1
#> 5 1 -1.70 -4.30 -0.08607824 -0.2089949 -1.786078 -4.508995 1
#> 6 1 -6.90 -1.55 1.21400011 -0.6583055 -5.686000 -2.208306 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4800 -37575 7725
#> initial value 998.131940
#> iter 2 value 836.865202
#> iter 3 value 836.081766
#> iter 4 value 833.630529
#> iter 5 value 782.827732
#> iter 6 value 773.164587
#> iter 7 value 771.669999
#> iter 8 value 771.642610
#> iter 9 value 771.642277
#> iter 10 value 771.642056
#> iter 11 value 771.642041
#> iter 12 value 771.641958
#> iter 12 value 771.641958
#> iter 12 value 771.641958
#> final value 771.641958
#> converged
#> This is Run number 158
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.2262026 -1.15549088 -2.1237974 -13.3554909 1
#> 2 1 -6.20 -3.90 1.0801639 -0.08596342 -5.1198361 -3.9859634 2
#> 3 1 -14.20 -5.80 -0.4135929 0.05136822 -14.6135929 -5.7486318 2
#> 4 1 -2.10 -13.20 2.3278307 0.24184901 0.2278307 -12.9581510 1
#> 5 1 -1.70 -4.30 -1.0083953 -1.01760029 -2.7083953 -5.3176003 1
#> 6 1 -6.90 -1.55 0.2789943 0.76871232 -6.6210057 -0.7812877 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4620 -38100 9550
#> initial value 998.131940
#> iter 2 value 817.288632
#> iter 3 value 817.012449
#> iter 4 value 815.601064
#> iter 5 value 762.577260
#> iter 6 value 753.137092
#> iter 7 value 751.537094
#> iter 8 value 751.513401
#> iter 9 value 751.513125
#> iter 10 value 751.513059
#> iter 10 value 751.513054
#> iter 10 value 751.513054
#> final value 751.513054
#> converged
#> This is Run number 159
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.07245271 1.25780196 -2.2775473 -10.942198 1
#> 2 1 -6.20 -3.90 6.53503360 -0.71170499 0.3350336 -4.611705 1
#> 3 1 -14.20 -5.80 0.31310655 1.49439987 -13.8868934 -4.305600 2
#> 4 1 -2.10 -13.20 -0.24615156 0.46540807 -2.3461516 -12.734592 1
#> 5 1 -1.70 -4.30 -0.74498466 0.43484514 -2.4449847 -3.865155 1
#> 6 1 -6.90 -1.55 -0.35131285 0.07263078 -7.2513129 -1.477369 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4960 -38450 7325
#> initial value 998.131940
#> iter 2 value 826.857298
#> iter 3 value 824.174968
#> iter 4 value 820.838961
#> iter 5 value 774.050432
#> iter 6 value 764.064300
#> iter 7 value 762.590604
#> iter 8 value 762.562349
#> iter 9 value 762.562099
#> iter 10 value 762.561963
#> iter 10 value 762.561961
#> iter 11 value 762.561930
#> iter 12 value 762.561918
#> iter 12 value 762.561915
#> iter 12 value 762.561914
#> final value 762.561914
#> converged
#> This is Run number 160
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.04834075 1.09825245 -2.398341 -11.101748 1
#> 2 1 -6.20 -3.90 -0.91037302 0.52440778 -7.110373 -3.375592 2
#> 3 1 -14.20 -5.80 0.77242498 0.71300595 -13.427575 -5.086994 2
#> 4 1 -2.10 -13.20 1.03378136 -0.12358753 -1.066219 -13.323588 1
#> 5 1 -1.70 -4.30 -0.24506491 -0.06326804 -1.945065 -4.363268 1
#> 6 1 -6.90 -1.55 -0.32490719 0.49525795 -7.224907 -1.054742 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4700 -36375 9475
#> initial value 998.131940
#> iter 2 value 841.187094
#> iter 3 value 823.031033
#> iter 4 value 823.004025
#> iter 5 value 783.427527
#> iter 6 value 775.943641
#> iter 7 value 775.306695
#> iter 8 value 775.288096
#> iter 9 value 775.287835
#> iter 10 value 775.287654
#> iter 11 value 775.287459
#> iter 12 value 775.287233
#> iter 12 value 775.287233
#> iter 12 value 775.287233
#> final value 775.287233
#> converged
#> This is Run number 161
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.62570058 -0.95140642 -3.975701 -13.1514064 1
#> 2 1 -6.20 -3.90 0.15981822 1.63403047 -6.040182 -2.2659695 2
#> 3 1 -14.20 -5.80 2.13912022 -0.35134300 -12.060880 -6.1513430 2
#> 4 1 -2.10 -13.20 0.33524543 0.06297275 -1.764755 -13.1370272 1
#> 5 1 -1.70 -4.30 0.68088243 -0.52887235 -1.019118 -4.8288724 1
#> 6 1 -6.90 -1.55 0.09791027 1.04335937 -6.802090 -0.5066406 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4440 -38000 7950
#> initial value 998.131940
#> iter 2 value 829.399207
#> iter 3 value 826.310634
#> iter 4 value 822.205419
#> iter 5 value 772.611132
#> iter 6 value 762.914154
#> iter 7 value 761.407274
#> iter 8 value 761.383080
#> iter 9 value 761.382925
#> iter 10 value 761.382877
#> iter 10 value 761.382876
#> iter 11 value 761.382818
#> iter 12 value 761.382738
#> iter 12 value 761.382734
#> iter 12 value 761.382730
#> final value 761.382730
#> converged
#> This is Run number 162
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.77560294 -0.24331461 -1.574397 -12.4433146 1
#> 2 1 -6.20 -3.90 2.10168883 2.68390914 -4.098311 -1.2160909 2
#> 3 1 -14.20 -5.80 0.39630188 0.57629627 -13.803698 -5.2237037 2
#> 4 1 -2.10 -13.20 0.35223200 2.01269927 -1.747768 -11.1873007 1
#> 5 1 -1.70 -4.30 -0.17545349 0.01336572 -1.875453 -4.2866343 1
#> 6 1 -6.90 -1.55 -0.02831735 1.87836770 -6.928317 0.3283677 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4660 -36425 7700
#> initial value 998.131940
#> iter 2 value 852.270784
#> iter 3 value 839.310978
#> iter 4 value 838.085084
#> iter 5 value 795.670147
#> iter 6 value 787.602968
#> iter 7 value 786.141315
#> iter 8 value 786.088920
#> iter 9 value 786.088080
#> iter 10 value 786.087905
#> iter 11 value 786.087703
#> iter 12 value 786.087566
#> iter 12 value 786.087566
#> iter 12 value 786.087566
#> final value 786.087566
#> converged
#> This is Run number 163
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.4658568 0.03428582 -1.884143 -12.165714 1
#> 2 1 -6.20 -3.90 0.2090581 0.28736439 -5.990942 -3.612636 2
#> 3 1 -14.20 -5.80 0.9799107 -0.07213880 -13.220089 -5.872139 2
#> 4 1 -2.10 -13.20 -1.1382323 -0.85766352 -3.238232 -14.057664 1
#> 5 1 -1.70 -4.30 -0.6392738 1.42697422 -2.339274 -2.873026 1
#> 6 1 -6.90 -1.55 0.9944834 -0.73961935 -5.905517 -2.289619 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4620 -36675 7650
#> initial value 998.131940
#> iter 2 value 849.303845
#> iter 3 value 836.277816
#> iter 4 value 834.731881
#> iter 5 value 792.523380
#> iter 6 value 784.353274
#> iter 7 value 782.826779
#> iter 8 value 782.768907
#> iter 9 value 782.767969
#> iter 10 value 782.767814
#> iter 11 value 782.767651
#> iter 12 value 782.767529
#> iter 12 value 782.767529
#> iter 12 value 782.767529
#> final value 782.767529
#> converged
#> This is Run number 164
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.46099091 1.5191108 -0.8890091 -10.680889 1
#> 2 1 -6.20 -3.90 -0.75573702 0.8462783 -6.9557370 -3.053722 2
#> 3 1 -14.20 -5.80 -0.02606664 -1.3521430 -14.2260666 -7.152143 2
#> 4 1 -2.10 -13.20 0.27134613 1.0087575 -1.8286539 -12.191243 1
#> 5 1 -1.70 -4.30 0.68906728 1.6275686 -1.0109327 -2.672431 1
#> 6 1 -6.90 -1.55 0.83559305 -0.6068052 -6.0644070 -2.156805 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4680 -36175 6825
#> initial value 998.131940
#> iter 2 value 860.283268
#> iter 3 value 860.222741
#> iter 4 value 857.676147
#> iter 5 value 804.221875
#> iter 6 value 795.035899
#> iter 7 value 793.491370
#> iter 8 value 793.461055
#> iter 9 value 793.460956
#> iter 10 value 793.460699
#> iter 10 value 793.460698
#> iter 10 value 793.460689
#> final value 793.460689
#> converged
#> This is Run number 165
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.05544758 0.90023531 -2.405448 -11.299765 1
#> 2 1 -6.20 -3.90 0.34159978 -0.03579532 -5.858400 -3.935795 2
#> 3 1 -14.20 -5.80 1.78969943 2.84238334 -12.410301 -2.957617 2
#> 4 1 -2.10 -13.20 -0.43402495 1.05847581 -2.534025 -12.141524 1
#> 5 1 -1.70 -4.30 -0.28117573 1.13873339 -1.981176 -3.161267 1
#> 6 1 -6.90 -1.55 0.20266586 2.54737801 -6.697334 0.997378 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4880 -37625 8275
#> initial value 998.131940
#> iter 2 value 832.826218
#> iter 3 value 818.248671
#> iter 4 value 817.378550
#> iter 5 value 778.052578
#> iter 6 value 769.682770
#> iter 7 value 768.514288
#> iter 8 value 768.464975
#> iter 9 value 768.464037
#> iter 10 value 768.463839
#> iter 11 value 768.463596
#> iter 12 value 768.463410
#> iter 12 value 768.463410
#> iter 12 value 768.463410
#> final value 768.463410
#> converged
#> This is Run number 166
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.7776858 0.8099890 -1.5723142 -11.3900110 1
#> 2 1 -6.20 -3.90 0.3999548 -0.9552364 -5.8000452 -4.8552364 2
#> 3 1 -14.20 -5.80 0.7580449 -0.1308905 -13.4419551 -5.9308905 2
#> 4 1 -2.10 -13.20 -0.7311184 -0.3087209 -2.8311184 -13.5087209 1
#> 5 1 -1.70 -4.30 1.4562281 -0.5703175 -0.2437719 -4.8703175 1
#> 6 1 -6.90 -1.55 0.6944846 2.3402125 -6.2055154 0.7902125 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4760 -36650 8925
#> initial value 998.131940
#> iter 2 value 841.568653
#> iter 3 value 825.222170
#> iter 4 value 825.019163
#> iter 5 value 784.996709
#> iter 6 value 777.125917
#> iter 7 value 776.293740
#> iter 8 value 776.266142
#> iter 9 value 776.265725
#> iter 10 value 776.265536
#> iter 11 value 776.265230
#> iter 12 value 776.265061
#> iter 12 value 776.265061
#> iter 12 value 776.265061
#> final value 776.265061
#> converged
#> This is Run number 167
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.939917085 -1.0941903 -0.4100829 -13.294190 1
#> 2 1 -6.20 -3.90 -0.004153738 -0.4760562 -6.2041537 -4.376056 2
#> 3 1 -14.20 -5.80 -0.306372397 -0.4595375 -14.5063724 -6.259537 2
#> 4 1 -2.10 -13.20 0.311642415 0.8998304 -1.7883576 -12.300170 1
#> 5 1 -1.70 -4.30 3.667338481 -0.6083225 1.9673385 -4.908323 1
#> 6 1 -6.90 -1.55 0.399763929 -0.9084288 -6.5002361 -2.458429 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4260 -36050 8400
#> initial value 998.131940
#> iter 2 value 852.511553
#> iter 3 value 837.031597
#> iter 4 value 835.811302
#> iter 5 value 793.109986
#> iter 6 value 785.345863
#> iter 7 value 784.218046
#> iter 8 value 784.178325
#> iter 9 value 784.177660
#> iter 10 value 784.177502
#> iter 11 value 784.177325
#> iter 12 value 784.177203
#> iter 12 value 784.177203
#> iter 12 value 784.177203
#> final value 784.177203
#> converged
#> This is Run number 168
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.13489919 -0.1617607 -3.484899 -12.361761 1
#> 2 1 -6.20 -3.90 -0.05938760 -0.3220271 -6.259388 -4.222027 2
#> 3 1 -14.20 -5.80 -0.25749115 1.6901085 -14.457491 -4.109892 2
#> 4 1 -2.10 -13.20 -0.02934026 -0.8166961 -2.129340 -14.016696 1
#> 5 1 -1.70 -4.30 0.35891212 1.1022053 -1.341088 -3.197795 1
#> 6 1 -6.90 -1.55 -0.10608457 0.4859946 -7.006085 -1.064005 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4660 -37450 8450
#> initial value 998.131940
#> iter 2 value 834.030839
#> iter 3 value 818.601230
#> iter 4 value 817.505831
#> iter 5 value 777.677613
#> iter 6 value 769.436868
#> iter 7 value 768.313057
#> iter 8 value 768.264945
#> iter 9 value 768.264038
#> iter 9 value 768.264029
#> iter 9 value 768.264029
#> final value 768.264029
#> converged
#> This is Run number 169
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.9788143 -0.1222818 -0.37118567 -12.322282 1
#> 2 1 -6.20 -3.90 -0.3023161 0.9877446 -6.50231614 -2.912255 2
#> 3 1 -14.20 -5.80 1.6537913 1.6657509 -12.54620872 -4.134249 2
#> 4 1 -2.10 -13.20 0.2979186 -0.6104767 -1.80208135 -13.810477 1
#> 5 1 -1.70 -4.30 1.6491352 1.6853161 -0.05086477 -2.614684 1
#> 6 1 -6.90 -1.55 -0.3466209 -0.5101114 -7.24662091 -2.060111 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4140 -37975 8475
#> initial value 998.131940
#> iter 2 value 826.209935
#> iter 3 value 822.577559
#> iter 4 value 817.875281
#> iter 5 value 767.155698
#> iter 6 value 757.619861
#> iter 7 value 756.055431
#> iter 8 value 756.032385
#> iter 9 value 756.032317
#> iter 10 value 756.032152
#> iter 10 value 756.032151
#> iter 10 value 756.032143
#> final value 756.032143
#> converged
#> This is Run number 170
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.6861257 -0.84086393 -3.0361257 -13.0408639 1
#> 2 1 -6.20 -3.90 0.4514751 0.89329369 -5.7485249 -3.0067063 2
#> 3 1 -14.20 -5.80 4.8634277 0.83321694 -9.3365723 -4.9667831 2
#> 4 1 -2.10 -13.20 0.7963973 4.99479430 -1.3036027 -8.2052057 1
#> 5 1 -1.70 -4.30 1.2577927 -0.03179632 -0.4422073 -4.3317963 1
#> 6 1 -6.90 -1.55 0.3741752 1.23324209 -6.5258248 -0.3167579 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3720 -36025 9575
#> initial value 998.131940
#> iter 2 value 844.212034
#> iter 3 value 823.946802
#> iter 4 value 822.629849
#> iter 5 value 780.643524
#> iter 6 value 773.392776
#> iter 7 value 772.626774
#> iter 8 value 772.595163
#> iter 9 value 772.594680
#> iter 10 value 772.594564
#> iter 11 value 772.594388
#> iter 12 value 772.594276
#> iter 12 value 772.594276
#> iter 12 value 772.594276
#> final value 772.594276
#> converged
#> This is Run number 171
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.93661084 -0.331523671 -3.286611 -12.531524 1
#> 2 1 -6.20 -3.90 0.70447879 1.155413137 -5.495521 -2.744587 2
#> 3 1 -14.20 -5.80 -0.05061111 1.164067168 -14.250611 -4.635933 2
#> 4 1 -2.10 -13.20 0.60962760 0.005428405 -1.490372 -13.194572 1
#> 5 1 -1.70 -4.30 -0.27278732 -0.788093784 -1.972787 -5.088094 1
#> 6 1 -6.90 -1.55 -1.17828334 -0.218385682 -8.078283 -1.768386 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5280 -37675 8000
#> initial value 998.131940
#> iter 2 value 833.885899
#> iter 3 value 820.761465
#> iter 4 value 820.383048
#> iter 5 value 781.518469
#> iter 6 value 773.011937
#> iter 7 value 771.794277
#> iter 8 value 771.747127
#> iter 9 value 771.746276
#> iter 10 value 771.746042
#> iter 11 value 771.745729
#> iter 12 value 771.745510
#> iter 12 value 771.745510
#> iter 12 value 771.745510
#> final value 771.745510
#> converged
#> This is Run number 172
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.58825862 0.2634678 -1.761741 -11.9365322 1
#> 2 1 -6.20 -3.90 -0.08682885 0.8447727 -6.286829 -3.0552273 2
#> 3 1 -14.20 -5.80 -1.43756368 0.6035796 -15.637564 -5.1964204 2
#> 4 1 -2.10 -13.20 0.47054629 0.9685211 -1.629454 -12.2314789 1
#> 5 1 -1.70 -4.30 0.59220511 0.4745151 -1.107795 -3.8254849 1
#> 6 1 -6.90 -1.55 -1.04093013 2.1323456 -7.940930 0.5823456 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5360 -36950 6875
#> initial value 998.131940
#> iter 2 value 850.090872
#> iter 3 value 840.154317
#> iter 4 value 839.347687
#> iter 5 value 798.006356
#> iter 6 value 789.686224
#> iter 7 value 787.769678
#> iter 8 value 787.699927
#> iter 9 value 787.698872
#> iter 10 value 787.698654
#> iter 11 value 787.698357
#> iter 12 value 787.698175
#> iter 12 value 787.698175
#> iter 12 value 787.698175
#> final value 787.698175
#> converged
#> This is Run number 173
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.9206062 0.5515899 -3.270606 -11.64841009 1
#> 2 1 -6.20 -3.90 1.2348756 0.6052025 -4.965124 -3.29479751 2
#> 3 1 -14.20 -5.80 1.9552070 -0.8856825 -12.244793 -6.68568253 2
#> 4 1 -2.10 -13.20 0.2347557 -0.2385170 -1.865244 -13.43851703 1
#> 5 1 -1.70 -4.30 -1.0558044 -0.3108100 -2.755804 -4.61080998 1
#> 6 1 -6.90 -1.55 -1.0028322 1.5217008 -7.902832 -0.02829924 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5020 -38050 7350
#> initial value 998.131940
#> iter 2 value 832.453767
#> iter 3 value 830.939458
#> iter 4 value 828.322091
#> iter 5 value 779.993576
#> iter 6 value 770.110888
#> iter 7 value 768.623034
#> iter 8 value 768.593458
#> iter 9 value 768.593283
#> iter 10 value 768.592988
#> iter 10 value 768.592987
#> iter 11 value 768.592927
#> iter 12 value 768.592891
#> iter 13 value 768.592879
#> iter 14 value 768.592856
#> iter 14 value 768.592856
#> iter 14 value 768.592856
#> final value 768.592856
#> converged
#> This is Run number 174
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.31580171 -0.72081287 -2.034198 -12.9208129 1
#> 2 1 -6.20 -3.90 -0.58567863 1.52167889 -6.785679 -2.3783211 2
#> 3 1 -14.20 -5.80 0.84321203 0.02168525 -13.356788 -5.7783147 2
#> 4 1 -2.10 -13.20 3.11523382 0.33440204 1.015234 -12.8655980 1
#> 5 1 -1.70 -4.30 0.08362867 3.60342171 -1.616371 -0.6965783 2
#> 6 1 -6.90 -1.55 0.47564486 0.33304922 -6.424355 -1.2169508 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4440 -37575 8725
#> initial value 998.131940
#> iter 2 value 830.380121
#> iter 3 value 829.786317
#> iter 4 value 827.259114
#> iter 5 value 774.194290
#> iter 6 value 764.752744
#> iter 7 value 763.192569
#> iter 8 value 763.170181
#> iter 9 value 763.170080
#> iter 10 value 763.169808
#> iter 10 value 763.169807
#> iter 10 value 763.169807
#> final value 763.169807
#> converged
#> This is Run number 175
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.2057203 -0.37101673 -2.555720 -12.571017 1
#> 2 1 -6.20 -3.90 -0.7037336 2.16597378 -6.903734 -1.734026 2
#> 3 1 -14.20 -5.80 -1.4669198 0.06653863 -15.666920 -5.733461 2
#> 4 1 -2.10 -13.20 -0.3386193 2.53126816 -2.438619 -10.668732 1
#> 5 1 -1.70 -4.30 -0.3077345 1.49366648 -2.007735 -2.806334 1
#> 6 1 -6.90 -1.55 1.1779748 0.49418469 -5.722025 -1.055815 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4420 -38575 9450
#> initial value 998.131940
#> iter 2 value 811.076372
#> iter 3 value 808.619565
#> iter 4 value 805.942068
#> iter 5 value 755.033141
#> iter 6 value 745.609529
#> iter 7 value 744.000142
#> iter 8 value 743.974006
#> iter 9 value 743.973756
#> iter 10 value 743.973692
#> iter 11 value 743.973675
#> iter 12 value 743.973655
#> iter 12 value 743.973655
#> iter 12 value 743.973655
#> final value 743.973655
#> converged
#> This is Run number 176
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.63452224 -0.8517979 -3.9845222 -13.051798 1
#> 2 1 -6.20 -3.90 1.87490392 -0.0494601 -4.3250961 -3.949460 2
#> 3 1 -14.20 -5.80 -1.69163911 0.7474401 -15.8916391 -5.052560 2
#> 4 1 -2.10 -13.20 1.84405192 0.0743271 -0.2559481 -13.125673 1
#> 5 1 -1.70 -4.30 2.51273872 0.9882329 0.8127387 -3.311767 1
#> 6 1 -6.90 -1.55 0.06521507 -0.1720708 -6.8347849 -1.722071 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4720 -37775 8325
#> initial value 998.131940
#> iter 2 value 830.374553
#> iter 3 value 829.746528
#> iter 4 value 827.574347
#> iter 5 value 776.145726
#> iter 6 value 766.536157
#> iter 7 value 765.021150
#> iter 8 value 764.996986
#> iter 9 value 764.996758
#> iter 10 value 764.996696
#> iter 11 value 764.996664
#> iter 12 value 764.996385
#> iter 12 value 764.996385
#> iter 12 value 764.996385
#> final value 764.996385
#> converged
#> This is Run number 177
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.05006067 1.5208829 -3.4000607 -10.6791171 1
#> 2 1 -6.20 -3.90 0.89231913 -0.4880213 -5.3076809 -4.3880213 2
#> 3 1 -14.20 -5.80 -0.42755825 -0.3715286 -14.6275583 -6.1715286 2
#> 4 1 -2.10 -13.20 2.90936966 -0.6090787 0.8093697 -13.8090787 1
#> 5 1 -1.70 -4.30 0.02520851 0.9905541 -1.6747915 -3.3094459 1
#> 6 1 -6.90 -1.55 1.62931341 0.5834068 -5.2706866 -0.9665932 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5360 -37050 6900
#> initial value 998.131940
#> iter 2 value 848.632099
#> iter 3 value 838.602422
#> iter 4 value 837.764325
#> iter 5 value 796.637711
#> iter 6 value 788.278837
#> iter 7 value 786.370338
#> iter 8 value 786.299729
#> iter 9 value 786.298645
#> iter 10 value 786.298428
#> iter 11 value 786.298136
#> iter 12 value 786.297954
#> iter 12 value 786.297954
#> iter 12 value 786.297954
#> final value 786.297954
#> converged
#> This is Run number 178
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.0205178 0.309119889 -2.3294822 -11.890880 1
#> 2 1 -6.20 -3.90 0.7275786 0.247493146 -5.4724214 -3.652507 2
#> 3 1 -14.20 -5.80 2.9028207 -0.372665195 -11.2971793 -6.172665 2
#> 4 1 -2.10 -13.20 0.8439077 0.005098387 -1.2560923 -13.194902 1
#> 5 1 -1.70 -4.30 0.8934374 0.012849077 -0.8065626 -4.287151 1
#> 6 1 -6.90 -1.55 3.5402764 0.277238680 -3.3597236 -1.272761 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4340 -35975 7625
#> initial value 998.131940
#> iter 2 value 858.240605
#> iter 3 value 845.017418
#> iter 4 value 843.251390
#> iter 5 value 799.335006
#> iter 6 value 791.430582
#> iter 7 value 789.909346
#> iter 8 value 789.855397
#> iter 9 value 789.854595
#> iter 10 value 789.854467
#> iter 11 value 789.854333
#> iter 12 value 789.854236
#> iter 12 value 789.854236
#> iter 12 value 789.854236
#> final value 789.854236
#> converged
#> This is Run number 179
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.0108671 1.2059996 -1.339133 -10.994000 1
#> 2 1 -6.20 -3.90 -0.4672756 1.2711213 -6.667276 -2.628879 2
#> 3 1 -14.20 -5.80 1.0861191 2.6018875 -13.113881 -3.198113 2
#> 4 1 -2.10 -13.20 0.7718259 0.6066224 -1.328174 -12.593378 1
#> 5 1 -1.70 -4.30 0.2388730 0.9929998 -1.461127 -3.307000 1
#> 6 1 -6.90 -1.55 0.6694543 -0.7740096 -6.230546 -2.324010 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4520 -36075 7675
#> initial value 998.131940
#> iter 2 value 856.805601
#> iter 3 value 843.785573
#> iter 4 value 842.434793
#> iter 5 value 799.180296
#> iter 6 value 791.250193
#> iter 7 value 789.782356
#> iter 8 value 789.731418
#> iter 9 value 789.730633
#> iter 10 value 789.730472
#> iter 11 value 789.730286
#> iter 12 value 789.730164
#> iter 12 value 789.730164
#> iter 12 value 789.730164
#> final value 789.730164
#> converged
#> This is Run number 180
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.0787446 0.1354055 -3.428745 -12.064595 1
#> 2 1 -6.20 -3.90 4.5782060 -0.4589881 -1.621794 -4.358988 1
#> 3 1 -14.20 -5.80 0.6672760 2.7674734 -13.532724 -3.032527 2
#> 4 1 -2.10 -13.20 -0.7290240 -0.6589795 -2.829024 -13.858979 1
#> 5 1 -1.70 -4.30 0.3648897 2.7558566 -1.335110 -1.544143 1
#> 6 1 -6.90 -1.55 1.0087148 3.3770423 -5.891285 1.827042 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4920 -37700 8075
#> initial value 998.131940
#> iter 2 value 833.055161
#> iter 3 value 832.955650
#> iter 4 value 831.234290
#> iter 5 value 780.096998
#> iter 6 value 770.426743
#> iter 7 value 768.923747
#> iter 8 value 768.897291
#> iter 9 value 768.896848
#> iter 10 value 768.896682
#> iter 10 value 768.896681
#> iter 11 value 768.896608
#> iter 11 value 768.896605
#> iter 12 value 768.896587
#> iter 12 value 768.896578
#> iter 12 value 768.896578
#> final value 768.896578
#> converged
#> This is Run number 181
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 3.14977813 0.7883694 0.7997781 -11.411631 1
#> 2 1 -6.20 -3.90 0.06542119 0.2664515 -6.1345788 -3.633549 2
#> 3 1 -14.20 -5.80 0.09965880 -1.2535819 -14.1003412 -7.053582 2
#> 4 1 -2.10 -13.20 -1.16945727 0.6735650 -3.2694573 -12.526435 1
#> 5 1 -1.70 -4.30 -0.63616565 2.1841320 -2.3361657 -2.115868 2
#> 6 1 -6.90 -1.55 -0.53983719 -0.8806205 -7.4398372 -2.430621 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4600 -37600 8400
#> initial value 998.131940
#> iter 2 value 832.265649
#> iter 3 value 831.718739
#> iter 4 value 829.365882
#> iter 5 value 777.138459
#> iter 6 value 767.606052
#> iter 7 value 766.079205
#> iter 8 value 766.055579
#> iter 9 value 766.055428
#> iter 10 value 766.055240
#> iter 11 value 766.055212
#> iter 12 value 766.055031
#> iter 12 value 766.055031
#> iter 12 value 766.055031
#> final value 766.055031
#> converged
#> This is Run number 182
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.3700766 2.53812693 -3.7200766 -9.6618731 1
#> 2 1 -6.20 -3.90 0.4562224 0.73030959 -5.7437776 -3.1696904 2
#> 3 1 -14.20 -5.80 1.1245371 -0.07030654 -13.0754629 -5.8703065 2
#> 4 1 -2.10 -13.20 -0.3341984 0.32984680 -2.4341984 -12.8701532 1
#> 5 1 -1.70 -4.30 1.0686566 0.67234556 -0.6313434 -3.6276544 1
#> 6 1 -6.90 -1.55 0.4300712 0.67710254 -6.4699288 -0.8728975 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5140 -38250 8150
#> initial value 998.131940
#> iter 2 value 824.872421
#> iter 3 value 824.386198
#> iter 4 value 823.000196
#> iter 5 value 773.686672
#> iter 6 value 763.858075
#> iter 7 value 762.368509
#> iter 8 value 762.342488
#> iter 9 value 762.342091
#> iter 10 value 762.341898
#> iter 11 value 762.341835
#> iter 12 value 762.341730
#> iter 12 value 762.341730
#> iter 12 value 762.341730
#> final value 762.341730
#> converged
#> This is Run number 183
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.17874901 -0.2303294 -2.171251 -12.4303294 1
#> 2 1 -6.20 -3.90 1.20634435 2.3905585 -4.993656 -1.5094415 2
#> 3 1 -14.20 -5.80 1.60252074 1.1396396 -12.597479 -4.6603604 2
#> 4 1 -2.10 -13.20 0.55904292 -0.3027912 -1.540957 -13.5027912 1
#> 5 1 -1.70 -4.30 -0.72897239 0.3491448 -2.428972 -3.9508552 1
#> 6 1 -6.90 -1.55 -0.09538345 0.6791749 -6.995383 -0.8708251 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4320 -36900 7875
#> initial value 998.131940
#> iter 2 value 844.827345
#> iter 3 value 843.832861
#> iter 4 value 840.458372
#> iter 5 value 787.011690
#> iter 6 value 777.644219
#> iter 7 value 776.127714
#> iter 8 value 776.103222
#> iter 9 value 776.102947
#> iter 10 value 776.102882
#> iter 10 value 776.102878
#> iter 11 value 776.102856
#> iter 12 value 776.102798
#> iter 12 value 776.102793
#> iter 12 value 776.102792
#> final value 776.102792
#> converged
#> This is Run number 184
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.5289846 -1.0426591 -1.821015 -13.242659 1
#> 2 1 -6.20 -3.90 -0.4509584 -0.1501863 -6.650958 -4.050186 2
#> 3 1 -14.20 -5.80 -0.4117330 -0.8129843 -14.611733 -6.612984 2
#> 4 1 -2.10 -13.20 -1.0339534 -0.6930176 -3.133953 -13.893018 1
#> 5 1 -1.70 -4.30 0.1079656 2.8601453 -1.592034 -1.439855 2
#> 6 1 -6.90 -1.55 0.5672184 -1.2517605 -6.332782 -2.801760 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5040 -38250 7850
#> initial value 998.131940
#> iter 2 value 826.708157
#> iter 3 value 825.557067
#> iter 4 value 823.484712
#> iter 5 value 774.780532
#> iter 6 value 764.922604
#> iter 7 value 763.448114
#> iter 8 value 763.421019
#> iter 9 value 763.420551
#> iter 10 value 763.420473
#> iter 11 value 763.420456
#> iter 12 value 763.420278
#> iter 12 value 763.420278
#> iter 12 value 763.420278
#> final value 763.420278
#> converged
#> This is Run number 185
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.42437984 -0.04052128 -2.774380 -12.2405213 1
#> 2 1 -6.20 -3.90 0.21339949 0.88075007 -5.986601 -3.0192499 2
#> 3 1 -14.20 -5.80 -1.58495686 0.51083812 -15.784957 -5.2891619 2
#> 4 1 -2.10 -13.20 -0.50534976 0.69451068 -2.605350 -12.5054893 1
#> 5 1 -1.70 -4.30 -0.01138258 0.83367062 -1.711383 -3.4663294 1
#> 6 1 -6.90 -1.55 -0.27305383 0.80578125 -7.173054 -0.7442187 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4540 -36800 7525
#> initial value 998.131940
#> iter 2 value 848.343113
#> iter 3 value 847.851758
#> iter 4 value 844.989339
#> iter 5 value 791.980766
#> iter 6 value 782.586073
#> iter 7 value 781.080610
#> iter 8 value 781.053622
#> iter 9 value 781.053513
#> iter 10 value 781.053235
#> iter 10 value 781.053232
#> iter 11 value 781.053198
#> iter 12 value 781.053128
#> iter 13 value 781.053114
#> iter 14 value 781.053102
#> iter 14 value 781.053102
#> iter 14 value 781.053102
#> final value 781.053102
#> converged
#> This is Run number 186
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.1368768 0.916809636 -2.213123 -11.28319036 1
#> 2 1 -6.20 -3.90 1.3424906 0.493717824 -4.857509 -3.40628218 2
#> 3 1 -14.20 -5.80 1.7151312 2.143341726 -12.484869 -3.65665827 2
#> 4 1 -2.10 -13.20 -0.5272566 0.003026948 -2.627257 -13.19697305 1
#> 5 1 -1.70 -4.30 -0.8982325 -0.054648929 -2.598232 -4.35464893 1
#> 6 1 -6.90 -1.55 -0.4318366 1.505628731 -7.331837 -0.04437127 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4460 -36025 6775
#> initial value 998.131940
#> iter 2 value 862.308773
#> iter 3 value 861.440372
#> iter 4 value 858.325799
#> iter 5 value 804.469066
#> iter 6 value 795.342853
#> iter 7 value 793.792388
#> iter 8 value 793.763715
#> iter 9 value 793.763658
#> iter 10 value 793.763518
#> iter 10 value 793.763518
#> iter 10 value 793.763514
#> final value 793.763514
#> converged
#> This is Run number 187
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.8007374 3.3015374 -1.5492626 -8.898463 1
#> 2 1 -6.20 -3.90 0.5945164 0.2518329 -5.6054836 -3.648167 2
#> 3 1 -14.20 -5.80 0.7789776 0.6085331 -13.4210224 -5.191467 2
#> 4 1 -2.10 -13.20 1.4466652 -0.6312492 -0.6533348 -13.831249 1
#> 5 1 -1.70 -4.30 0.2745075 -0.2548041 -1.4254925 -4.554804 1
#> 6 1 -6.90 -1.55 -0.0149709 2.6396468 -6.9149709 1.089647 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5160 -38675 8050
#> initial value 998.131940
#> iter 2 value 819.348442
#> iter 3 value 817.946348
#> iter 4 value 816.163963
#> iter 5 value 768.566792
#> iter 6 value 758.645091
#> iter 7 value 757.182181
#> iter 8 value 757.156474
#> iter 9 value 757.156090
#> iter 10 value 757.155849
#> iter 11 value 757.155817
#> iter 12 value 757.155700
#> iter 12 value 757.155700
#> iter 12 value 757.155700
#> final value 757.155700
#> converged
#> This is Run number 188
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.4262638 2.43093629 0.07626377 -9.769064 1
#> 2 1 -6.20 -3.90 -1.2857705 0.24089165 -7.48577048 -3.659108 2
#> 3 1 -14.20 -5.80 -1.2989798 1.12096042 -15.49897981 -4.679040 2
#> 4 1 -2.10 -13.20 -1.4849666 -0.42266271 -3.58496656 -13.622663 1
#> 5 1 -1.70 -4.30 -0.5959271 -0.54712499 -2.29592707 -4.847125 1
#> 6 1 -6.90 -1.55 2.1161153 -0.07945213 -4.78388473 -1.629452 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4320 -36475 8225
#> initial value 998.131940
#> iter 2 value 848.243533
#> iter 3 value 833.178463
#> iter 4 value 831.638043
#> iter 5 value 789.310977
#> iter 6 value 781.342166
#> iter 7 value 780.096679
#> iter 8 value 780.049327
#> iter 9 value 780.048520
#> iter 10 value 780.048371
#> iter 11 value 780.048223
#> iter 12 value 780.048107
#> iter 12 value 780.048107
#> iter 12 value 780.048107
#> final value 780.048107
#> converged
#> This is Run number 189
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.1171067 1.2048103 -1.2328933 -10.99518969 1
#> 2 1 -6.20 -3.90 0.5317395 0.9415294 -5.6682605 -2.95847063 2
#> 3 1 -14.20 -5.80 0.4676202 1.1920872 -13.7323798 -4.60791279 2
#> 4 1 -2.10 -13.20 -0.1865045 0.3905657 -2.2865045 -12.80943431 1
#> 5 1 -1.70 -4.30 1.2447684 -0.9535877 -0.4552316 -5.25358769 1
#> 6 1 -6.90 -1.55 0.3935711 1.6374025 -6.5064289 0.08740254 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4760 -35575 7200
#> initial value 998.131940
#> iter 2 value 865.786836
#> iter 3 value 854.596915
#> iter 4 value 853.625857
#> iter 5 value 809.454235
#> iter 6 value 801.694880
#> iter 7 value 800.055277
#> iter 8 value 800.004531
#> iter 9 value 800.003833
#> iter 10 value 800.003654
#> iter 11 value 800.003415
#> iter 12 value 800.003287
#> iter 12 value 800.003287
#> iter 12 value 800.003287
#> final value 800.003287
#> converged
#> This is Run number 190
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.0466317 0.44040720 -3.3966317 -11.759593 1
#> 2 1 -6.20 -3.90 1.2509813 1.91027959 -4.9490187 -1.989720 2
#> 3 1 -14.20 -5.80 1.4758548 1.54105332 -12.7241452 -4.258947 2
#> 4 1 -2.10 -13.20 0.3720488 -0.55387167 -1.7279512 -13.753872 1
#> 5 1 -1.70 -4.30 2.4278099 -0.65524296 0.7278099 -4.955243 1
#> 6 1 -6.90 -1.55 -0.6161156 0.06297309 -7.5161156 -1.487027 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5000 -37200 6925
#> initial value 998.131940
#> iter 2 value 846.481654
#> iter 3 value 845.880628
#> iter 4 value 843.498222
#> iter 5 value 793.165678
#> iter 6 value 783.534825
#> iter 7 value 781.985496
#> iter 8 value 781.952588
#> iter 9 value 781.952465
#> iter 10 value 781.952119
#> iter 10 value 781.952119
#> iter 11 value 781.952104
#> iter 12 value 781.952074
#> iter 12 value 781.952074
#> iter 12 value 781.952073
#> final value 781.952073
#> converged
#> This is Run number 191
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.06857950 -0.1032335 -2.418580 -12.3032335 1
#> 2 1 -6.20 -3.90 -0.03525107 0.5804152 -6.235251 -3.3195848 2
#> 3 1 -14.20 -5.80 1.56786913 0.9600912 -12.632131 -4.8399088 2
#> 4 1 -2.10 -13.20 -1.69355498 0.6158353 -3.793555 -12.5841647 1
#> 5 1 -1.70 -4.30 -1.64365019 0.8818170 -3.343650 -3.4181830 1
#> 6 1 -6.90 -1.55 4.12598863 1.7897396 -2.774011 0.2397396 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4180 -37275 9575
#> initial value 998.131940
#> iter 2 value 828.293826
#> iter 3 value 808.457980
#> iter 4 value 807.488734
#> iter 5 value 767.968655
#> iter 6 value 760.355134
#> iter 7 value 759.577874
#> iter 8 value 759.539618
#> iter 9 value 759.539079
#> iter 10 value 759.538725
#> iter 11 value 759.538460
#> iter 11 value 759.538452
#> iter 11 value 759.538452
#> final value 759.538452
#> converged
#> This is Run number 192
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 3.9862754 1.22277472 1.6362754 -10.977225 1
#> 2 1 -6.20 -3.90 1.3695216 1.58602347 -4.8304784 -2.313977 2
#> 3 1 -14.20 -5.80 0.3995884 -0.31630443 -13.8004116 -6.116304 2
#> 4 1 -2.10 -13.20 -1.1881315 3.11787970 -3.2881315 -10.082120 1
#> 5 1 -1.70 -4.30 0.9551859 -0.08201285 -0.7448141 -4.382013 1
#> 6 1 -6.90 -1.55 -0.7450587 -0.90661582 -7.6450587 -2.456616 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4040 -36525 8425
#> initial value 998.131940
#> iter 2 value 846.089822
#> iter 3 value 846.031026
#> iter 4 value 842.640024
#> iter 5 value 786.523676
#> iter 6 value 777.397058
#> iter 7 value 775.836703
#> iter 8 value 775.814633
#> iter 9 value 775.814507
#> iter 10 value 775.814490
#> iter 11 value 775.814473
#> iter 12 value 775.814286
#> iter 12 value 775.814286
#> iter 12 value 775.814286
#> final value 775.814286
#> converged
#> This is Run number 193
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.6372537 0.72501692 -2.987254 -11.474983 1
#> 2 1 -6.20 -3.90 0.9631344 -1.11052772 -5.236866 -5.010528 2
#> 3 1 -14.20 -5.80 0.4176449 1.65600278 -13.782355 -4.143997 2
#> 4 1 -2.10 -13.20 0.5659806 0.57733000 -1.534019 -12.622670 1
#> 5 1 -1.70 -4.30 0.5559379 0.01894109 -1.144062 -4.281059 1
#> 6 1 -6.90 -1.55 0.1185758 -1.23436664 -6.781424 -2.784367 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5180 -38100 7525
#> initial value 998.131940
#> iter 2 value 830.771777
#> iter 3 value 830.014063
#> iter 4 value 828.146449
#> iter 5 value 779.586435
#> iter 6 value 769.691728
#> iter 7 value 768.208273
#> iter 8 value 768.178058
#> iter 9 value 768.177809
#> iter 10 value 768.177535
#> iter 11 value 768.177507
#> iter 12 value 768.177270
#> iter 12 value 768.177270
#> iter 12 value 768.177270
#> final value 768.177270
#> converged
#> This is Run number 194
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.6587907 1.19807011 -1.6912093 -11.001930 1
#> 2 1 -6.20 -3.90 1.0542933 1.40176571 -5.1457067 -2.498234 2
#> 3 1 -14.20 -5.80 0.5181683 0.32846473 -13.6818317 -5.471535 2
#> 4 1 -2.10 -13.20 2.4193912 -0.93035715 0.3193912 -14.130357 1
#> 5 1 -1.70 -4.30 -0.1020587 -0.55341990 -1.8020587 -4.853420 1
#> 6 1 -6.90 -1.55 -1.3631788 0.03273008 -8.2631788 -1.517270 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3840 -38100 8900
#> initial value 998.131940
#> iter 2 value 821.283767
#> iter 3 value 816.348242
#> iter 4 value 810.556337
#> iter 5 value 759.597504
#> iter 6 value 750.175479
#> iter 7 value 748.531019
#> iter 8 value 748.506041
#> iter 9 value 748.505965
#> iter 10 value 748.505916
#> iter 10 value 748.505916
#> iter 11 value 748.505902
#> iter 11 value 748.505897
#> iter 11 value 748.505897
#> final value 748.505897
#> converged
#> This is Run number 195
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.88961426 1.1818945 -4.2396143 -11.0181055 1
#> 2 1 -6.20 -3.90 0.50438218 0.6048647 -5.6956178 -3.2951353 2
#> 3 1 -14.20 -5.80 -0.34351261 -0.1556335 -14.5435126 -5.9556335 2
#> 4 1 -2.10 -13.20 -0.02031323 0.1906350 -2.1203132 -13.0093650 1
#> 5 1 -1.70 -4.30 1.14364940 0.9910110 -0.5563506 -3.3089890 1
#> 6 1 -6.90 -1.55 -0.00664636 1.3402454 -6.9066464 -0.2097546 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4400 -38275 8200
#> initial value 998.131940
#> iter 2 value 823.910984
#> iter 3 value 820.339981
#> iter 4 value 816.064159
#> iter 5 value 766.976362
#> iter 6 value 757.283750
#> iter 7 value 755.769023
#> iter 8 value 755.745560
#> iter 9 value 755.745487
#> iter 10 value 755.745233
#> iter 10 value 755.745231
#> iter 11 value 755.745211
#> iter 11 value 755.745202
#> iter 11 value 755.745198
#> final value 755.745198
#> converged
#> This is Run number 196
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.1637910 0.6287964 -3.5137910 -11.5712036 1
#> 2 1 -6.20 -3.90 1.7244808 4.8247516 -4.4755192 0.9247516 2
#> 3 1 -14.20 -5.80 -0.4103943 2.6792455 -14.6103943 -3.1207545 2
#> 4 1 -2.10 -13.20 -0.7444798 0.5418108 -2.8444798 -12.6581892 1
#> 5 1 -1.70 -4.30 1.1800858 -0.7111698 -0.5199142 -5.0111698 1
#> 6 1 -6.90 -1.55 -0.1903098 1.3502617 -7.0903098 -0.1997383 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4960 -40250 8600
#> initial value 998.131940
#> iter 2 value 791.692129
#> iter 3 value 786.288856
#> iter 4 value 782.822821
#> iter 5 value 740.187564
#> iter 6 value 730.462037
#> iter 7 value 729.021822
#> iter 8 value 728.996366
#> iter 9 value 728.996068
#> iter 10 value 728.995842
#> iter 11 value 728.995740
#> iter 12 value 728.995699
#> iter 12 value 728.995699
#> iter 12 value 728.995699
#> final value 728.995699
#> converged
#> This is Run number 197
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.5917722 0.2638446 -1.758228 -11.9361554 1
#> 2 1 -6.20 -3.90 -0.1640450 3.2817926 -6.364045 -0.6182074 2
#> 3 1 -14.20 -5.80 0.1877137 -1.2358812 -14.012286 -7.0358812 2
#> 4 1 -2.10 -13.20 -0.1647376 0.5100212 -2.264738 -12.6899788 1
#> 5 1 -1.70 -4.30 -0.2474549 1.3667281 -1.947455 -2.9332719 1
#> 6 1 -6.90 -1.55 -1.0143700 -1.1463998 -7.914370 -2.6963998 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4300 -35350 8575
#> initial value 998.131940
#> iter 2 value 860.028209
#> iter 3 value 844.426985
#> iter 4 value 843.805923
#> iter 5 value 800.754197
#> iter 6 value 793.299138
#> iter 7 value 792.326425
#> iter 8 value 792.298478
#> iter 9 value 792.298061
#> iter 10 value 792.297910
#> iter 11 value 792.297714
#> iter 12 value 792.297603
#> iter 12 value 792.297603
#> iter 12 value 792.297603
#> final value 792.297603
#> converged
#> This is Run number 198
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.73136270 2.8472852 -3.081363 -9.352715 1
#> 2 1 -6.20 -3.90 0.07798976 1.6388682 -6.122010 -2.261132 2
#> 3 1 -14.20 -5.80 -0.58144214 2.9682919 -14.781442 -2.831708 2
#> 4 1 -2.10 -13.20 0.88491770 0.1085445 -1.215082 -13.091455 1
#> 5 1 -1.70 -4.30 -0.54067985 1.9711485 -2.240680 -2.328851 1
#> 6 1 -6.90 -1.55 1.38873960 -0.8016604 -5.511260 -2.351660 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5260 -38100 7050
#> initial value 998.131940
#> iter 2 value 833.414073
#> iter 3 value 832.294536
#> iter 4 value 830.092224
#> iter 5 value 782.530152
#> iter 6 value 772.572888
#> iter 7 value 771.059595
#> iter 8 value 771.026417
#> iter 9 value 771.026286
#> iter 10 value 771.025842
#> iter 10 value 771.025841
#> iter 11 value 771.025809
#> iter 12 value 771.025794
#> iter 12 value 771.025793
#> iter 12 value 771.025789
#> final value 771.025789
#> converged
#> This is Run number 199
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.67975874 0.1176193 -3.0297587 -12.0823807 1
#> 2 1 -6.20 -3.90 -1.52037728 -0.1515259 -7.7203773 -4.0515259 2
#> 3 1 -14.20 -5.80 0.38401302 -0.2785157 -13.8159870 -6.0785157 2
#> 4 1 -2.10 -13.20 0.02622931 1.2998564 -2.0737707 -11.9001436 1
#> 5 1 -1.70 -4.30 2.09693940 1.9349019 0.3969394 -2.3650981 1
#> 6 1 -6.90 -1.55 0.86559452 0.6622561 -6.0344055 -0.8877439 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5240 -38125 7175
#> initial value 998.131940
#> iter 2 value 832.382809
#> iter 3 value 831.321095
#> iter 4 value 829.188711
#> iter 5 value 781.450124
#> iter 6 value 771.499516
#> iter 7 value 769.999410
#> iter 8 value 769.967115
#> iter 9 value 769.966981
#> iter 10 value 769.966498
#> iter 10 value 769.966494
#> iter 11 value 769.966441
#> iter 11 value 769.966435
#> iter 11 value 769.966433
#> final value 769.966433
#> converged
#> This is Run number 200
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.02564954 -0.3828214 -1.3243505 -12.582821 1
#> 2 1 -6.20 -3.90 0.69711801 -0.4021504 -5.5028820 -4.302150 2
#> 3 1 -14.20 -5.80 0.05799658 -0.5287932 -14.1420034 -6.328793 2
#> 4 1 -2.10 -13.20 4.39369893 -0.7035667 2.2936989 -13.903567 1
#> 5 1 -1.70 -4.30 0.87861540 0.3748881 -0.8213846 -3.925112 1
#> 6 1 -6.90 -1.55 0.96225048 -0.8427006 -5.9377495 -2.392701 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4860 -37950 6825
#> initial value 998.131940
#> iter 2 value 836.637014
#> iter 3 value 833.623796
#> iter 4 value 829.799665
#> iter 5 value 782.334893
#> iter 6 value 772.422116
#> iter 7 value 770.868755
#> iter 8 value 770.836952
#> iter 9 value 770.836916
#> iter 10 value 770.836809
#> iter 10 value 770.836808
#> iter 10 value 770.836802
#> final value 770.836802
#> converged
#> This is Run number 201
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.6611689 -0.5192342 -0.6888311 -12.719234 1
#> 2 1 -6.20 -3.90 -0.3953617 -1.5911902 -6.5953617 -5.491190 2
#> 3 1 -14.20 -5.80 3.3363392 2.0013493 -10.8636608 -3.798651 2
#> 4 1 -2.10 -13.20 1.3444213 -1.0772566 -0.7555787 -14.277257 1
#> 5 1 -1.70 -4.30 -0.5800091 1.7551467 -2.2800091 -2.544853 1
#> 6 1 -6.90 -1.55 0.3693793 0.1379461 -6.5306207 -1.412054 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5140 -37950 7700
#> initial value 998.131940
#> iter 2 value 831.866493
#> iter 3 value 831.489997
#> iter 4 value 829.831201
#> iter 5 value 780.383607
#> iter 6 value 770.557277
#> iter 7 value 769.068489
#> iter 8 value 769.039009
#> iter 9 value 769.038666
#> iter 10 value 769.038416
#> iter 11 value 769.038366
#> iter 12 value 769.038200
#> iter 12 value 769.038200
#> iter 12 value 769.038200
#> final value 769.038200
#> converged
#> This is Run number 202
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.2212173 1.07261390 -2.571217 -11.1273861 1
#> 2 1 -6.20 -3.90 -1.4528728 0.23157444 -7.652873 -3.6684256 2
#> 3 1 -14.20 -5.80 0.7043056 -0.30487024 -13.495694 -6.1048702 2
#> 4 1 -2.10 -13.20 0.8734026 2.27787752 -1.226597 -10.9221225 1
#> 5 1 -1.70 -4.30 0.5994021 -0.04387482 -1.100598 -4.3438748 1
#> 6 1 -6.90 -1.55 -0.0730933 0.89834610 -6.973093 -0.6516539 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4740 -38200 7800
#> initial value 998.131940
#> iter 2 value 827.632029
#> iter 3 value 825.272047
#> iter 4 value 822.012029
#> iter 5 value 773.339383
#> iter 6 value 763.529589
#> iter 7 value 762.049835
#> iter 8 value 762.024263
#> iter 9 value 762.023932
#> iter 10 value 762.023869
#> iter 10 value 762.023869
#> iter 11 value 762.023838
#> iter 12 value 762.023751
#> iter 12 value 762.023751
#> iter 12 value 762.023747
#> final value 762.023747
#> converged
#> This is Run number 203
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.4223917 0.54838832 -2.772392 -11.6516117 1
#> 2 1 -6.20 -3.90 -0.1913676 -1.04892467 -6.391368 -4.9489247 2
#> 3 1 -14.20 -5.80 1.6427687 0.04426186 -12.557231 -5.7557381 2
#> 4 1 -2.10 -13.20 0.4886420 2.14948461 -1.611358 -11.0505154 1
#> 5 1 -1.70 -4.30 -1.0308608 1.23312064 -2.730861 -3.0668794 1
#> 6 1 -6.90 -1.55 0.4178737 1.92678055 -6.482126 0.3767805 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4840 -37225 8075
#> initial value 998.131940
#> iter 2 value 839.531371
#> iter 3 value 825.594456
#> iter 4 value 824.667629
#> iter 5 value 784.362840
#> iter 6 value 776.064548
#> iter 7 value 774.800128
#> iter 8 value 774.750323
#> iter 9 value 774.749418
#> iter 10 value 774.749219
#> iter 11 value 774.748986
#> iter 12 value 774.748814
#> iter 12 value 774.748814
#> iter 12 value 774.748814
#> final value 774.748814
#> converged
#> This is Run number 204
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.3272043 0.13172885 -2.6772043 -12.0682711 1
#> 2 1 -6.20 -3.90 4.1554959 -0.42807068 -2.0445041 -4.3280707 1
#> 3 1 -14.20 -5.80 1.6140968 0.10340405 -12.5859032 -5.6965959 2
#> 4 1 -2.10 -13.20 1.4138129 2.68682560 -0.6861871 -10.5131744 1
#> 5 1 -1.70 -4.30 1.1933754 0.03015926 -0.5066246 -4.2698407 1
#> 6 1 -6.90 -1.55 -0.3170472 0.80494024 -7.2170472 -0.7450598 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4920 -37725 8000
#> initial value 998.131940
#> iter 2 value 833.171157
#> iter 3 value 832.916900
#> iter 4 value 831.087327
#> iter 5 value 780.198995
#> iter 6 value 770.512187
#> iter 7 value 769.013462
#> iter 8 value 768.986663
#> iter 9 value 768.986216
#> iter 10 value 768.986105
#> iter 11 value 768.986070
#> iter 12 value 768.985940
#> iter 12 value 768.985940
#> iter 12 value 768.985940
#> final value 768.985940
#> converged
#> This is Run number 205
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.53660929 0.009501503 -1.81339071 -12.190498 1
#> 2 1 -6.20 -3.90 3.41665951 0.516960836 -2.78334049 -3.383039 1
#> 3 1 -14.20 -5.80 -0.87680918 -0.053463640 -15.07680918 -5.853464 2
#> 4 1 -2.10 -13.20 0.05147548 1.120640636 -2.04852452 -12.079359 1
#> 5 1 -1.70 -4.30 1.68717513 0.269970203 -0.01282487 -4.030030 1
#> 6 1 -6.90 -1.55 0.76125277 3.411392328 -6.13874723 1.861392 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4540 -37975 7975
#> initial value 998.131940
#> iter 2 value 829.665778
#> iter 3 value 827.200445
#> iter 4 value 823.608741
#> iter 5 value 773.796901
#> iter 6 value 764.101593
#> iter 7 value 762.601784
#> iter 8 value 762.577343
#> iter 9 value 762.577102
#> iter 10 value 762.576942
#> iter 10 value 762.576942
#> iter 11 value 762.576929
#> iter 12 value 762.576892
#> iter 12 value 762.576892
#> iter 12 value 762.576890
#> final value 762.576890
#> converged
#> This is Run number 206
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.33147691 0.99003239 -2.018523 -11.209968 1
#> 2 1 -6.20 -3.90 -1.52250633 0.98664660 -7.722506 -2.913353 2
#> 3 1 -14.20 -5.80 -0.23216934 1.91391446 -14.432169 -3.886086 2
#> 4 1 -2.10 -13.20 -0.06535737 1.52462297 -2.165357 -11.675377 1
#> 5 1 -1.70 -4.30 0.10177041 -0.80387259 -1.598230 -5.103873 1
#> 6 1 -6.90 -1.55 0.42164366 0.09852411 -6.478356 -1.451476 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4220 -38325 8600
#> initial value 998.131940
#> iter 2 value 820.471299
#> iter 3 value 816.497086
#> iter 4 value 811.900589
#> iter 5 value 762.209930
#> iter 6 value 752.634874
#> iter 7 value 751.075121
#> iter 8 value 751.051807
#> iter 9 value 751.051717
#> iter 10 value 751.051564
#> iter 10 value 751.051561
#> iter 10 value 751.051556
#> final value 751.051556
#> converged
#> This is Run number 207
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.8819750 -1.2915663 -0.468025 -13.491566 1
#> 2 1 -6.20 -3.90 1.1323766 0.6188376 -5.067623 -3.281162 2
#> 3 1 -14.20 -5.80 0.6224675 1.2390871 -13.577533 -4.560913 2
#> 4 1 -2.10 -13.20 0.2718437 -0.6112038 -1.828156 -13.811204 1
#> 5 1 -1.70 -4.30 -0.8276116 2.4274721 -2.527612 -1.872528 2
#> 6 1 -6.90 -1.55 1.1114923 3.7289883 -5.788508 2.178988 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4340 -38225 8850
#> initial value 998.131940
#> iter 2 value 820.328416
#> iter 3 value 817.694536
#> iter 4 value 814.199310
#> iter 5 value 763.393848
#> iter 6 value 753.879835
#> iter 7 value 752.309889
#> iter 8 value 752.286877
#> iter 9 value 752.286758
#> iter 10 value 752.286583
#> iter 10 value 752.286582
#> iter 11 value 752.286556
#> iter 11 value 752.286548
#> iter 11 value 752.286548
#> final value 752.286548
#> converged
#> This is Run number 208
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.2645935 3.7486865 -2.085406 -8.451314 1
#> 2 1 -6.20 -3.90 0.1348066 1.3281247 -6.065193 -2.571875 2
#> 3 1 -14.20 -5.80 0.7251795 2.3766584 -13.474821 -3.423342 2
#> 4 1 -2.10 -13.20 1.0677728 0.6002044 -1.032227 -12.599796 1
#> 5 1 -1.70 -4.30 -0.2882502 0.7660063 -1.988250 -3.533994 1
#> 6 1 -6.90 -1.55 0.9701812 0.2959677 -5.929819 -1.254032 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4440 -38025 7875
#> initial value 998.131940
#> iter 2 value 829.498088
#> iter 3 value 826.197684
#> iter 4 value 821.948733
#> iter 5 value 772.625836
#> iter 6 value 762.905278
#> iter 7 value 761.399717
#> iter 8 value 761.375311
#> iter 9 value 761.375158
#> iter 10 value 761.375036
#> iter 10 value 761.375035
#> iter 11 value 761.375002
#> iter 12 value 761.374978
#> iter 12 value 761.374978
#> iter 12 value 761.374971
#> final value 761.374971
#> converged
#> This is Run number 209
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.5274654 -0.03312567 -1.8225346 -12.233126 1
#> 2 1 -6.20 -3.90 1.6312161 -1.26986942 -4.5687839 -5.169869 1
#> 3 1 -14.20 -5.80 0.2480153 1.62287504 -13.9519847 -4.177125 2
#> 4 1 -2.10 -13.20 1.2027451 0.43044158 -0.8972549 -12.769558 1
#> 5 1 -1.70 -4.30 4.5306161 2.94256439 2.8306161 -1.357436 1
#> 6 1 -6.90 -1.55 1.5341076 -0.08601901 -5.3658924 -1.636019 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5200 -38700 7300
#> initial value 998.131940
#> iter 2 value 823.397883
#> iter 3 value 821.216503
#> iter 4 value 818.528295
#> iter 5 value 772.592925
#> iter 6 value 762.517834
#> iter 7 value 761.059714
#> iter 8 value 761.030326
#> iter 9 value 761.030030
#> iter 10 value 761.029823
#> iter 10 value 761.029823
#> iter 11 value 761.029792
#> iter 12 value 761.029748
#> iter 12 value 761.029748
#> iter 12 value 761.029743
#> final value 761.029743
#> converged
#> This is Run number 210
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.1768665 -0.7960847 -2.1731335 -12.996085 1
#> 2 1 -6.20 -3.90 0.7901106 1.3908150 -5.4098894 -2.509185 2
#> 3 1 -14.20 -5.80 -0.5724390 -0.9475604 -14.7724390 -6.747560 2
#> 4 1 -2.10 -13.20 0.3822200 1.1498824 -1.7177800 -12.050118 1
#> 5 1 -1.70 -4.30 2.4046482 -0.9636387 0.7046482 -5.263639 1
#> 6 1 -6.90 -1.55 0.2213680 0.1867141 -6.6786320 -1.363286 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4600 -38375 8425
#> initial value 998.131940
#> iter 2 value 821.165205
#> iter 3 value 818.692703
#> iter 4 value 815.553862
#> iter 5 value 766.183941
#> iter 6 value 756.501016
#> iter 7 value 754.990281
#> iter 8 value 754.967107
#> iter 9 value 754.967001
#> iter 10 value 754.966656
#> iter 10 value 754.966656
#> iter 11 value 754.966635
#> iter 12 value 754.966614
#> iter 12 value 754.966614
#> iter 12 value 754.966609
#> final value 754.966609
#> converged
#> This is Run number 211
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.96082601 0.89956020 -0.389174 -11.300440 1
#> 2 1 -6.20 -3.90 -0.09946271 1.00658810 -6.299463 -2.893412 2
#> 3 1 -14.20 -5.80 -0.20824904 2.39293508 -14.408249 -3.407065 2
#> 4 1 -2.10 -13.20 -0.88722908 1.33952258 -2.987229 -11.860477 1
#> 5 1 -1.70 -4.30 -0.97506850 -0.02062372 -2.675069 -4.320624 1
#> 6 1 -6.90 -1.55 0.32015415 3.28518430 -6.579846 1.735184 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4260 -35950 7550
#> initial value 998.131940
#> iter 2 value 858.925078
#> iter 3 value 845.722675
#> iter 4 value 843.700840
#> iter 5 value 799.392752
#> iter 6 value 791.475751
#> iter 7 value 789.899219
#> iter 8 value 789.842737
#> iter 9 value 789.841929
#> iter 10 value 789.841822
#> iter 11 value 789.841720
#> iter 12 value 789.841639
#> iter 12 value 789.841639
#> iter 12 value 789.841639
#> final value 789.841639
#> converged
#> This is Run number 212
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.2947065 0.6409884 -2.6447065 -11.559012 1
#> 2 1 -6.20 -3.90 -0.3603534 1.3152634 -6.5603534 -2.584737 2
#> 3 1 -14.20 -5.80 1.1207609 4.1729656 -13.0792391 -1.627034 2
#> 4 1 -2.10 -13.20 1.5686805 2.9921795 -0.5313195 -10.207821 1
#> 5 1 -1.70 -4.30 1.4065242 1.9161339 -0.2934758 -2.383866 1
#> 6 1 -6.90 -1.55 3.0936157 -0.3648565 -3.8063843 -1.914856 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3800 -36850 8175
#> initial value 998.131940
#> iter 2 value 843.143895
#> iter 3 value 840.175148
#> iter 4 value 835.036905
#> iter 5 value 780.879108
#> iter 6 value 771.599884
#> iter 7 value 770.012818
#> iter 8 value 769.990330
#> iter 8 value 769.990328
#> final value 769.990328
#> converged
#> This is Run number 213
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.5252644 -0.6165983 0.1752644 -12.816598 1
#> 2 1 -6.20 -3.90 -0.1078932 -1.0227831 -6.3078932 -4.922783 2
#> 3 1 -14.20 -5.80 -0.9044652 0.5887002 -15.1044652 -5.211300 2
#> 4 1 -2.10 -13.20 -0.2690952 -0.1724116 -2.3690952 -13.372412 1
#> 5 1 -1.70 -4.30 -0.3998890 1.0748204 -2.0998890 -3.225180 1
#> 6 1 -6.90 -1.55 0.5526397 -1.3208595 -6.3473603 -2.870860 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4800 -37150 8300
#> initial value 998.131940
#> iter 2 value 839.114363
#> iter 3 value 824.510748
#> iter 4 value 823.750861
#> iter 5 value 783.556588
#> iter 6 value 775.338357
#> iter 7 value 774.193530
#> iter 8 value 774.149097
#> iter 9 value 774.148286
#> iter 10 value 774.148084
#> iter 11 value 774.147833
#> iter 12 value 774.147655
#> iter 12 value 774.147655
#> iter 12 value 774.147655
#> final value 774.147655
#> converged
#> This is Run number 214
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.13989282 0.31788820 -2.489893 -11.8821118 1
#> 2 1 -6.20 -3.90 2.44017767 2.67297784 -3.759822 -1.2270222 2
#> 3 1 -14.20 -5.80 0.08114534 0.76591541 -14.118855 -5.0340846 2
#> 4 1 -2.10 -13.20 0.62950384 -0.99450266 -1.470496 -14.1945027 1
#> 5 1 -1.70 -4.30 0.28862814 -0.04864252 -1.411372 -4.3486425 1
#> 6 1 -6.90 -1.55 0.80438102 1.09363756 -6.095619 -0.4563624 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4700 -38775 8075
#> initial value 998.131940
#> iter 2 value 817.598850
#> iter 3 value 814.067338
#> iter 4 value 810.350101
#> iter 5 value 763.269256
#> iter 6 value 753.422729
#> iter 7 value 751.952003
#> iter 8 value 751.928085
#> iter 9 value 751.927990
#> iter 10 value 751.927649
#> iter 10 value 751.927645
#> iter 11 value 751.927606
#> iter 11 value 751.927599
#> iter 11 value 751.927596
#> final value 751.927596
#> converged
#> This is Run number 215
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.7818964 -0.36930080 -1.5681036 -12.5693008 1
#> 2 1 -6.20 -3.90 0.2217283 2.82988152 -5.9782717 -1.0701185 2
#> 3 1 -14.20 -5.80 -0.8209807 -0.04621425 -15.0209807 -5.8462143 2
#> 4 1 -2.10 -13.20 3.0456854 -0.37238226 0.9456854 -13.5723823 1
#> 5 1 -1.70 -4.30 1.0786661 4.51897137 -0.6213339 0.2189714 2
#> 6 1 -6.90 -1.55 -1.4165239 -0.26052548 -8.3165239 -1.8105255 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4360 -36600 8400
#> initial value 998.131940
#> iter 2 value 845.536623
#> iter 3 value 830.012685
#> iter 4 value 828.677130
#> iter 5 value 786.893422
#> iter 6 value 778.926744
#> iter 7 value 777.769857
#> iter 8 value 777.725289
#> iter 9 value 777.724504
#> iter 10 value 777.724344
#> iter 11 value 777.724173
#> iter 12 value 777.724044
#> iter 12 value 777.724044
#> iter 12 value 777.724044
#> final value 777.724044
#> converged
#> This is Run number 216
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.8572214 -0.046325959 -3.207221 -12.246326 1
#> 2 1 -6.20 -3.90 -0.6141226 1.361625768 -6.814123 -2.538374 2
#> 3 1 -14.20 -5.80 1.1848798 0.214174812 -13.015120 -5.585825 2
#> 4 1 -2.10 -13.20 -0.5069679 -0.003723596 -2.606968 -13.203724 1
#> 5 1 -1.70 -4.30 -0.1515510 0.122873746 -1.851551 -4.177126 1
#> 6 1 -6.90 -1.55 -0.6558761 0.343744846 -7.555876 -1.206255 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4460 -37450 8400
#> initial value 998.131940
#> iter 2 value 834.249097
#> iter 3 value 833.514098
#> iter 4 value 830.774512
#> iter 5 value 778.021919
#> iter 6 value 768.552743
#> iter 7 value 767.018294
#> iter 8 value 766.994992
#> iter 9 value 766.994858
#> iter 10 value 766.994669
#> iter 11 value 766.994650
#> iter 12 value 766.994500
#> iter 12 value 766.994500
#> iter 12 value 766.994500
#> final value 766.994500
#> converged
#> This is Run number 217
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.9060572 0.9835320 -1.44394276 -11.2164680 1
#> 2 1 -6.20 -3.90 1.0482856 0.7338503 -5.15171436 -3.1661497 2
#> 3 1 -14.20 -5.80 0.9730635 1.1934169 -13.22693647 -4.6065831 2
#> 4 1 -2.10 -13.20 -0.2847167 -0.4568749 -2.38471669 -13.6568749 1
#> 5 1 -1.70 -4.30 1.6222771 1.3209311 -0.07772293 -2.9790689 1
#> 6 1 -6.90 -1.55 0.1058330 2.5148493 -6.79416704 0.9648493 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5300 -38200 7150
#> initial value 998.131940
#> iter 2 value 831.451972
#> iter 3 value 830.433227
#> iter 4 value 828.404009
#> iter 5 value 780.970543
#> iter 6 value 770.988737
#> iter 7 value 769.488339
#> iter 8 value 769.455520
#> iter 9 value 769.455379
#> iter 10 value 769.454883
#> iter 10 value 769.454878
#> iter 11 value 769.454828
#> iter 11 value 769.454819
#> iter 11 value 769.454817
#> final value 769.454817
#> converged
#> This is Run number 218
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.1574379 -0.7112123 -2.19256214 -12.911212 1
#> 2 1 -6.20 -3.90 -1.0373591 0.1572026 -7.23735912 -3.742797 2
#> 3 1 -14.20 -5.80 -0.2482313 1.0187661 -14.44823131 -4.781234 2
#> 4 1 -2.10 -13.20 0.1080556 1.7519414 -1.99194443 -11.448059 1
#> 5 1 -1.70 -4.30 1.6982922 0.1584201 -0.00170778 -4.141580 1
#> 6 1 -6.90 -1.55 0.6121255 -1.1919284 -6.28787453 -2.741928 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5040 -37525 8100
#> initial value 998.131940
#> iter 2 value 835.332731
#> iter 3 value 821.576755
#> iter 4 value 820.927865
#> iter 5 value 781.520256
#> iter 6 value 773.111806
#> iter 7 value 771.894903
#> iter 8 value 771.846412
#> iter 9 value 771.845514
#> iter 10 value 771.845297
#> iter 11 value 771.845024
#> iter 12 value 771.844825
#> iter 12 value 771.844825
#> iter 12 value 771.844825
#> final value 771.844825
#> converged
#> This is Run number 219
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.2451418 0.2229629 -2.595142 -11.9770371 1
#> 2 1 -6.20 -3.90 4.2556032 -0.3249627 -1.944397 -4.2249627 1
#> 3 1 -14.20 -5.80 -0.5330461 0.5285331 -14.733046 -5.2714669 2
#> 4 1 -2.10 -13.20 -0.3067118 1.1227871 -2.406712 -12.0772129 1
#> 5 1 -1.70 -4.30 0.1042856 -0.3718101 -1.595714 -4.6718101 1
#> 6 1 -6.90 -1.55 -0.2574763 1.7295182 -7.157476 0.1795182 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4940 -38975 9050
#> initial value 998.131940
#> iter 2 value 808.271769
#> iter 3 value 806.279874
#> iter 4 value 804.705132
#> iter 5 value 756.169423
#> iter 6 value 746.511555
#> iter 7 value 744.980557
#> iter 8 value 744.957975
#> iter 9 value 744.957716
#> iter 10 value 744.957511
#> iter 10 value 744.957504
#> iter 11 value 744.957463
#> iter 12 value 744.957434
#> iter 12 value 744.957431
#> iter 12 value 744.957423
#> final value 744.957423
#> converged
#> This is Run number 220
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.6830793 -0.89195528 -3.0330793 -13.091955 1
#> 2 1 -6.20 -3.90 1.7715770 2.71132969 -4.4284230 -1.188670 2
#> 3 1 -14.20 -5.80 -0.1466834 0.68075818 -14.3466834 -5.119242 2
#> 4 1 -2.10 -13.20 -0.1869603 1.57027988 -2.2869603 -11.629720 1
#> 5 1 -1.70 -4.30 0.9843228 -0.45901535 -0.7156772 -4.759015 1
#> 6 1 -6.90 -1.55 3.0694237 0.09228439 -3.8305763 -1.457716 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4600 -37850 9400
#> initial value 998.131940
#> iter 2 value 821.911909
#> iter 3 value 803.274657
#> iter 4 value 802.729930
#> iter 5 value 764.671946
#> iter 6 value 756.795479
#> iter 7 value 756.012670
#> iter 8 value 755.973726
#> iter 9 value 755.973189
#> iter 10 value 755.972636
#> iter 11 value 755.972338
#> iter 12 value 755.972305
#> iter 12 value 755.972305
#> iter 12 value 755.972305
#> final value 755.972305
#> converged
#> This is Run number 221
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.46204251 2.0258411 -1.887957 -10.174159 1
#> 2 1 -6.20 -3.90 -0.73703195 2.7396051 -6.937032 -1.160395 2
#> 3 1 -14.20 -5.80 4.62026472 -1.1042179 -9.579735 -6.904218 2
#> 4 1 -2.10 -13.20 -0.78874110 -0.6175690 -2.888741 -13.817569 1
#> 5 1 -1.70 -4.30 -0.09436361 1.1072941 -1.794364 -3.192706 1
#> 6 1 -6.90 -1.55 -0.17157498 -0.9294871 -7.071575 -2.479487 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5100 -37275 7475
#> initial value 998.131940
#> iter 2 value 842.473425
#> iter 3 value 830.551070
#> iter 4 value 829.579977
#> iter 5 value 789.091698
#> iter 6 value 780.668399
#> iter 7 value 779.089779
#> iter 8 value 779.028540
#> iter 9 value 779.027502
#> iter 10 value 779.027297
#> iter 11 value 779.027052
#> iter 12 value 779.026877
#> iter 12 value 779.026877
#> iter 12 value 779.026877
#> final value 779.026877
#> converged
#> This is Run number 222
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.8331926 0.3044384 -3.183193 -11.895562 1
#> 2 1 -6.20 -3.90 -0.8347592 0.8766310 -7.034759 -3.023369 2
#> 3 1 -14.20 -5.80 1.9946349 0.1053642 -12.205365 -5.694636 2
#> 4 1 -2.10 -13.20 -0.6342008 1.2022323 -2.734201 -11.997768 1
#> 5 1 -1.70 -4.30 4.3684669 1.6272935 2.668467 -2.672707 1
#> 6 1 -6.90 -1.55 5.8201447 -0.7644829 -1.079855 -2.314483 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4560 -38400 8650
#> initial value 998.131940
#> iter 2 value 819.303495
#> iter 3 value 816.906029
#> iter 4 value 813.895717
#> iter 5 value 764.121457
#> iter 6 value 754.495744
#> iter 7 value 752.964872
#> iter 8 value 752.942043
#> iter 9 value 752.941920
#> iter 10 value 752.941645
#> iter 10 value 752.941645
#> iter 11 value 752.941631
#> iter 12 value 752.941581
#> iter 12 value 752.941581
#> iter 12 value 752.941577
#> final value 752.941577
#> converged
#> This is Run number 223
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.5462463 -0.5084753 -0.8037537 -12.7084753 1
#> 2 1 -6.20 -3.90 -0.7297658 2.7955792 -6.9297658 -1.1044208 2
#> 3 1 -14.20 -5.80 2.7662387 -1.0960633 -11.4337613 -6.8960633 2
#> 4 1 -2.10 -13.20 1.0825753 0.2544271 -1.0174247 -12.9455729 1
#> 5 1 -1.70 -4.30 0.2226683 1.1584525 -1.4773317 -3.1415475 1
#> 6 1 -6.90 -1.55 1.7433892 0.6413078 -5.1566108 -0.9086922 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4220 -36100 7950
#> initial value 998.131940
#> iter 2 value 854.655717
#> iter 3 value 840.286851
#> iter 4 value 838.464413
#> iter 5 value 794.937719
#> iter 6 value 787.043538
#> iter 7 value 785.666582
#> iter 8 value 785.616369
#> iter 9 value 785.615586
#> iter 10 value 785.615459
#> iter 11 value 785.615338
#> iter 12 value 785.615244
#> iter 12 value 785.615244
#> iter 12 value 785.615244
#> final value 785.615244
#> converged
#> This is Run number 224
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 3.1527113 2.0518032 0.8027113 -10.148197 1
#> 2 1 -6.20 -3.90 0.8899827 -1.0239389 -5.3100173 -4.923939 2
#> 3 1 -14.20 -5.80 -0.8217042 -1.0562186 -15.0217042 -6.856219 2
#> 4 1 -2.10 -13.20 1.0924533 -1.4447415 -1.0075467 -14.644742 1
#> 5 1 -1.70 -4.30 1.5310610 -0.3864360 -0.1689390 -4.686436 1
#> 6 1 -6.90 -1.55 2.6157620 -0.1411399 -4.2842380 -1.691140 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4880 -38475 8025
#> initial value 998.131940
#> iter 2 value 822.365538
#> iter 3 value 820.314271
#> iter 4 value 817.651485
#> iter 5 value 769.432425
#> iter 6 value 759.592431
#> iter 7 value 758.120696
#> iter 8 value 758.095726
#> iter 9 value 758.095415
#> iter 10 value 758.095192
#> iter 10 value 758.095187
#> iter 11 value 758.095149
#> iter 12 value 758.095103
#> iter 12 value 758.095103
#> iter 12 value 758.095095
#> final value 758.095095
#> converged
#> This is Run number 225
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.6489142 -0.98052015 -1.701086 -13.1805201 1
#> 2 1 -6.20 -3.90 0.6566954 1.94836813 -5.543305 -1.9516319 2
#> 3 1 -14.20 -5.80 0.2926962 -0.03185116 -13.907304 -5.8318512 2
#> 4 1 -2.10 -13.20 0.8665063 -0.79771814 -1.233494 -13.9977181 1
#> 5 1 -1.70 -4.30 -0.7990171 3.10619374 -2.499017 -1.1938063 2
#> 6 1 -6.90 -1.55 0.3351253 0.55250965 -6.564875 -0.9974904 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3720 -35775 8600
#> initial value 998.131940
#> iter 2 value 854.130016
#> iter 3 value 836.997157
#> iter 4 value 834.807542
#> iter 5 value 790.634845
#> iter 6 value 783.053786
#> iter 7 value 781.931676
#> iter 8 value 781.889693
#> iter 9 value 781.889041
#> iter 10 value 781.888943
#> iter 11 value 781.888872
#> iter 12 value 781.888805
#> iter 12 value 781.888805
#> iter 12 value 781.888805
#> final value 781.888805
#> converged
#> This is Run number 226
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.63429934 3.258987 0.2842993 -8.9410130 1
#> 2 1 -6.20 -3.90 -0.08634780 -1.211447 -6.2863478 -5.1114473 2
#> 3 1 -14.20 -5.80 -0.05242249 1.559033 -14.2524225 -4.2409672 2
#> 4 1 -2.10 -13.20 -1.07424200 2.101584 -3.1742420 -11.0984162 1
#> 5 1 -1.70 -4.30 0.87497769 1.659815 -0.8250223 -2.6401852 1
#> 6 1 -6.90 -1.55 -1.10712039 1.016576 -8.0071204 -0.5334245 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5200 -38225 7300
#> initial value 998.131940
#> iter 2 value 830.268985
#> iter 3 value 829.038991
#> iter 4 value 826.835613
#> iter 5 value 779.189578
#> iter 6 value 769.230033
#> iter 7 value 767.744815
#> iter 8 value 767.713835
#> iter 9 value 767.713723
#> iter 10 value 767.713288
#> iter 10 value 767.713283
#> iter 11 value 767.713209
#> iter 12 value 767.713165
#> iter 12 value 767.713154
#> iter 12 value 767.713154
#> final value 767.713154
#> converged
#> This is Run number 227
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.5387713 0.5110238 -0.8112287 -11.688976 1
#> 2 1 -6.20 -3.90 -0.6929681 -0.5261176 -6.8929681 -4.426118 2
#> 3 1 -14.20 -5.80 -0.1610842 1.2185085 -14.3610842 -4.581491 2
#> 4 1 -2.10 -13.20 -0.3075401 1.2440309 -2.4075401 -11.955969 1
#> 5 1 -1.70 -4.30 -0.5152276 0.6473089 -2.2152276 -3.652691 1
#> 6 1 -6.90 -1.55 0.6693692 0.4242264 -6.2306308 -1.125774 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4800 -37250 7025
#> initial value 998.131940
#> iter 2 value 845.220847
#> iter 3 value 843.856517
#> iter 4 value 840.851468
#> iter 5 value 790.498915
#> iter 6 value 780.863900
#> iter 7 value 779.327932
#> iter 8 value 779.297416
#> iter 9 value 779.297334
#> iter 10 value 779.297059
#> iter 10 value 779.297059
#> iter 11 value 779.297043
#> iter 11 value 779.297032
#> iter 11 value 779.297030
#> final value 779.297030
#> converged
#> This is Run number 228
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.00913671 0.3640908 -3.359137 -11.835909 1
#> 2 1 -6.20 -3.90 1.86487839 1.0866935 -4.335122 -2.813306 2
#> 3 1 -14.20 -5.80 -0.70743127 -0.8649129 -14.907431 -6.664913 2
#> 4 1 -2.10 -13.20 0.52873096 0.5563107 -1.571269 -12.643689 1
#> 5 1 -1.70 -4.30 -0.51320387 -1.4462085 -2.213204 -5.746209 1
#> 6 1 -6.90 -1.55 -0.06736038 1.3044030 -6.967360 -0.245597 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4760 -37475 7350
#> initial value 998.131940
#> iter 2 value 840.375129
#> iter 3 value 838.978332
#> iter 4 value 835.992906
#> iter 5 value 785.700100
#> iter 6 value 776.022173
#> iter 7 value 774.516113
#> iter 8 value 774.487554
#> iter 9 value 774.487458
#> iter 10 value 774.487164
#> iter 10 value 774.487164
#> iter 11 value 774.487130
#> iter 12 value 774.487077
#> iter 12 value 774.487077
#> iter 12 value 774.487069
#> final value 774.487069
#> converged
#> This is Run number 229
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.3476047 0.06034758 -1.002395 -12.139652 1
#> 2 1 -6.20 -3.90 5.0253341 -0.97462922 -1.174666 -4.874629 1
#> 3 1 -14.20 -5.80 1.9787679 1.85553392 -12.221232 -3.944466 2
#> 4 1 -2.10 -13.20 0.7544058 5.70771000 -1.345594 -7.492290 1
#> 5 1 -1.70 -4.30 -0.1644608 1.80539359 -1.864461 -2.494606 1
#> 6 1 -6.90 -1.55 -0.2085016 0.88587599 -7.108502 -0.664124 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3980 -35300 8425
#> initial value 998.131940
#> iter 2 value 861.351832
#> iter 3 value 845.557691
#> iter 4 value 844.190153
#> iter 5 value 800.030576
#> iter 6 value 792.581504
#> iter 7 value 791.488121
#> iter 8 value 791.452715
#> iter 9 value 791.452167
#> iter 10 value 791.452031
#> iter 11 value 791.451883
#> iter 12 value 791.451786
#> iter 12 value 791.451786
#> iter 12 value 791.451786
#> final value 791.451786
#> converged
#> This is Run number 230
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.61012389 2.1967122 -1.7398761 -10.003288 1
#> 2 1 -6.20 -3.90 1.43976316 0.4304440 -4.7602368 -3.469556 2
#> 3 1 -14.20 -5.80 -0.71785614 2.0145349 -14.9178561 -3.785465 2
#> 4 1 -2.10 -13.20 0.04187654 -0.8844330 -2.0581235 -14.084433 1
#> 5 1 -1.70 -4.30 0.75768673 -0.8960483 -0.9423133 -5.196048 1
#> 6 1 -6.90 -1.55 -1.30695771 -0.1131472 -8.2069577 -1.663147 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4420 -37150 9025
#> initial value 998.131940
#> iter 2 value 834.105507
#> iter 3 value 816.605813
#> iter 4 value 815.713186
#> iter 5 value 775.763984
#> iter 6 value 767.854580
#> iter 7 value 766.952069
#> iter 8 value 766.913096
#> iter 9 value 766.912416
#> iter 10 value 766.912264
#> iter 11 value 766.912008
#> iter 12 value 766.911823
#> iter 12 value 766.911823
#> iter 12 value 766.911823
#> final value 766.911823
#> converged
#> This is Run number 231
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.16827061 0.4721674 -2.181729 -11.727833 1
#> 2 1 -6.20 -3.90 -0.44011012 2.7785072 -6.640110 -1.121493 2
#> 3 1 -14.20 -5.80 -0.06088043 1.2742445 -14.260880 -4.525755 2
#> 4 1 -2.10 -13.20 -0.41934075 0.6170567 -2.519341 -12.582943 1
#> 5 1 -1.70 -4.30 -0.64130981 0.5044677 -2.341310 -3.795532 1
#> 6 1 -6.90 -1.55 -0.88892186 0.3666270 -7.788922 -1.183373 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4520 -38550 9250
#> initial value 998.131940
#> iter 2 value 812.952560
#> iter 3 value 810.740577
#> iter 4 value 808.238683
#> iter 5 value 757.667863
#> iter 6 value 748.176439
#> iter 7 value 746.592313
#> iter 8 value 746.568208
#> iter 9 value 746.567989
#> iter 10 value 746.567875
#> iter 10 value 746.567873
#> iter 10 value 746.567872
#> final value 746.567872
#> converged
#> This is Run number 232
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.6562666 0.7279654 -1.6937334 -11.4720346 1
#> 2 1 -6.20 -3.90 -0.3315619 1.1393507 -6.5315619 -2.7606493 2
#> 3 1 -14.20 -5.80 3.0002982 1.5335912 -11.1997018 -4.2664088 2
#> 4 1 -2.10 -13.20 1.9653324 2.5459133 -0.1346676 -10.6540867 1
#> 5 1 -1.70 -4.30 -0.9620042 2.0163120 -2.6620042 -2.2836880 2
#> 6 1 -6.90 -1.55 1.9552861 0.6347921 -4.9447139 -0.9152079 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4440 -37075 7600
#> initial value 998.131940
#> iter 2 value 844.198408
#> iter 3 value 842.744285
#> iter 4 value 839.295916
#> iter 5 value 787.098577
#> iter 6 value 777.617475
#> iter 7 value 776.106609
#> iter 8 value 776.080737
#> iter 9 value 776.080530
#> iter 10 value 776.080376
#> iter 10 value 776.080376
#> iter 11 value 776.080357
#> iter 12 value 776.080331
#> iter 12 value 776.080331
#> iter 12 value 776.080325
#> final value 776.080325
#> converged
#> This is Run number 233
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.77672651 0.07332117 -1.573273 -12.126679 1
#> 2 1 -6.20 -3.90 0.78101133 2.91430997 -5.418989 -0.985690 2
#> 3 1 -14.20 -5.80 -0.02314009 0.18009432 -14.223140 -5.619906 2
#> 4 1 -2.10 -13.20 0.86328819 -0.44309015 -1.236712 -13.643090 1
#> 5 1 -1.70 -4.30 -1.00193681 0.91426214 -2.701937 -3.385738 1
#> 6 1 -6.90 -1.55 0.32296627 -0.96275018 -6.577034 -2.512750 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4560 -37900 8625
#> initial value 998.131940
#> iter 2 value 826.594068
#> iter 3 value 825.472269
#> iter 4 value 822.959707
#> iter 5 value 771.329928
#> iter 6 value 761.780075
#> iter 7 value 760.239878
#> iter 8 value 760.217148
#> iter 9 value 760.217040
#> iter 10 value 760.216722
#> iter 11 value 760.216708
#> iter 12 value 760.216661
#> iter 12 value 760.216661
#> iter 12 value 760.216661
#> final value 760.216661
#> converged
#> This is Run number 234
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.57613146 0.1066032 -2.926131 -12.0933968 1
#> 2 1 -6.20 -3.90 -0.07533067 0.8923694 -6.275331 -3.0076306 2
#> 3 1 -14.20 -5.80 -0.21428682 2.8658044 -14.414287 -2.9341956 2
#> 4 1 -2.10 -13.20 -0.07444164 2.7899533 -2.174442 -10.4100467 1
#> 5 1 -1.70 -4.30 0.56680012 1.1422351 -1.133200 -3.1577649 1
#> 6 1 -6.90 -1.55 0.82872452 0.9845114 -6.071275 -0.5654886 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4540 -38000 7725
#> initial value 998.131940
#> iter 2 value 830.809529
#> iter 3 value 827.814378
#> iter 4 value 823.825890
#> iter 5 value 774.691562
#> iter 6 value 764.936060
#> iter 7 value 763.438897
#> iter 8 value 763.413680
#> iter 9 value 763.413451
#> iter 10 value 763.413380
#> iter 10 value 763.413379
#> iter 11 value 763.413363
#> iter 12 value 763.413316
#> iter 12 value 763.413314
#> iter 12 value 763.413312
#> final value 763.413312
#> converged
#> This is Run number 235
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.8609022 -0.3543153 -1.4890978 -12.554315 1
#> 2 1 -6.20 -3.90 1.5331985 0.9031450 -4.6668015 -2.996855 2
#> 3 1 -14.20 -5.80 3.0657897 1.2485331 -11.1342103 -4.551467 2
#> 4 1 -2.10 -13.20 2.9493356 0.2997115 0.8493356 -12.900289 1
#> 5 1 -1.70 -4.30 0.8355937 0.6438314 -0.8644063 -3.656169 1
#> 6 1 -6.90 -1.55 -0.7399820 -0.3127829 -7.6399820 -1.862783 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4320 -37275 6750
#> initial value 998.131940
#> iter 2 value 846.006023
#> iter 3 value 841.262583
#> iter 4 value 836.317886
#> iter 5 value 786.577587
#> iter 6 value 776.851900
#> iter 7 value 775.236546
#> iter 8 value 775.205536
#> iter 9 value 775.205513
#> iter 9 value 775.205509
#> iter 9 value 775.205507
#> final value 775.205507
#> converged
#> This is Run number 236
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 3.06900657 0.2463602 0.7190066 -11.953640 1
#> 2 1 -6.20 -3.90 -0.36377570 -0.7264029 -6.5637757 -4.626403 2
#> 3 1 -14.20 -5.80 -0.08543647 0.7455482 -14.2854365 -5.054452 2
#> 4 1 -2.10 -13.20 0.14689917 -0.9700900 -1.9531008 -14.170090 1
#> 5 1 -1.70 -4.30 -0.06712430 0.8552935 -1.7671243 -3.444707 1
#> 6 1 -6.90 -1.55 -0.37561250 -0.8692690 -7.2756125 -2.419269 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5280 -39325 8075
#> initial value 998.131940
#> iter 2 value 809.507159
#> iter 3 value 807.183957
#> iter 4 value 805.272537
#> iter 5 value 759.988338
#> iter 6 value 749.980981
#> iter 7 value 748.552081
#> iter 8 value 748.527495
#> iter 9 value 748.527405
#> iter 10 value 748.526859
#> iter 10 value 748.526852
#> iter 11 value 748.526720
#> iter 12 value 748.526698
#> iter 13 value 748.526686
#> iter 13 value 748.526682
#> iter 13 value 748.526682
#> final value 748.526682
#> converged
#> This is Run number 237
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.35073754 -1.1729103 -0.9992625 -13.3729103 1
#> 2 1 -6.20 -3.90 1.78474880 1.9182288 -4.4152512 -1.9817712 2
#> 3 1 -14.20 -5.80 -0.47908179 -0.4313195 -14.6790818 -6.2313195 2
#> 4 1 -2.10 -13.20 0.48351782 0.4159895 -1.6164822 -12.7840105 1
#> 5 1 -1.70 -4.30 0.01199428 -0.6818011 -1.6880057 -4.9818011 1
#> 6 1 -6.90 -1.55 0.52393012 0.9461725 -6.3760699 -0.6038275 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5060 -36350 7325
#> initial value 998.131940
#> iter 2 value 855.477702
#> iter 3 value 844.211536
#> iter 4 value 843.519965
#> iter 5 value 801.212878
#> iter 6 value 793.128543
#> iter 7 value 791.527456
#> iter 8 value 791.474664
#> iter 9 value 791.473891
#> iter 10 value 791.473685
#> iter 11 value 791.473411
#> iter 12 value 791.473252
#> iter 12 value 791.473252
#> iter 12 value 791.473252
#> final value 791.473252
#> converged
#> This is Run number 238
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.2945176 1.2785394 -1.0554824 -10.921461 1
#> 2 1 -6.20 -3.90 1.9221402 -0.3283209 -4.2778598 -4.228321 2
#> 3 1 -14.20 -5.80 -1.0257321 2.2361994 -15.2257321 -3.563801 2
#> 4 1 -2.10 -13.20 1.2583617 0.3497378 -0.8416383 -12.850262 1
#> 5 1 -1.70 -4.30 0.8480809 0.3766968 -0.8519191 -3.923303 1
#> 6 1 -6.90 -1.55 -0.3289784 0.4087266 -7.2289784 -1.141273 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4460 -37075 8000
#> initial value 998.131940
#> iter 2 value 841.836768
#> iter 3 value 841.304673
#> iter 4 value 838.443149
#> iter 5 value 785.284953
#> iter 6 value 775.863089
#> iter 7 value 774.349403
#> iter 8 value 774.324587
#> iter 9 value 774.324248
#> iter 10 value 774.324196
#> iter 11 value 774.324183
#> iter 12 value 774.324058
#> iter 12 value 774.324058
#> iter 12 value 774.324058
#> final value 774.324058
#> converged
#> This is Run number 239
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.1783481 0.28678833 -2.1716519 -11.913212 1
#> 2 1 -6.20 -3.90 -0.7703255 -0.28859054 -6.9703255 -4.188591 2
#> 3 1 -14.20 -5.80 0.3893850 1.71547328 -13.8106150 -4.084527 2
#> 4 1 -2.10 -13.20 1.4587360 0.06386876 -0.6412640 -13.136131 1
#> 5 1 -1.70 -4.30 1.9703241 3.17371512 0.2703241 -1.126285 1
#> 6 1 -6.90 -1.55 1.8232117 3.46785428 -5.0767883 1.917854 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5000 -37925 7650
#> initial value 998.131940
#> iter 2 value 832.493908
#> iter 3 value 831.612845
#> iter 4 value 829.445344
#> iter 5 value 780.017732
#> iter 6 value 770.214725
#> iter 7 value 768.729649
#> iter 8 value 768.701117
#> iter 9 value 768.700775
#> iter 10 value 768.700531
#> iter 11 value 768.700510
#> iter 12 value 768.700394
#> iter 12 value 768.700394
#> iter 12 value 768.700394
#> final value 768.700394
#> converged
#> This is Run number 240
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.2070988 0.06965739 -0.1429012 -12.1303426 1
#> 2 1 -6.20 -3.90 -1.0670426 -1.03099058 -7.2670426 -4.9309906 2
#> 3 1 -14.20 -5.80 0.2969437 -0.51771517 -13.9030563 -6.3177152 2
#> 4 1 -2.10 -13.20 0.6265145 -0.72090700 -1.4734855 -13.9209070 1
#> 5 1 -1.70 -4.30 -0.4225846 1.30227959 -2.1225846 -2.9977204 1
#> 6 1 -6.90 -1.55 0.4264199 1.67028352 -6.4735801 0.1202835 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5320 -39650 7650
#> initial value 998.131940
#> iter 2 value 807.105776
#> iter 3 value 803.882030
#> iter 4 value 801.168408
#> iter 5 value 757.958370
#> iter 6 value 747.813651
#> iter 7 value 746.423783
#> iter 8 value 746.398119
#> iter 9 value 746.397852
#> iter 10 value 746.397539
#> iter 10 value 746.397536
#> iter 11 value 746.397505
#> iter 12 value 746.397421
#> iter 13 value 746.397409
#> iter 14 value 746.397394
#> iter 14 value 746.397393
#> iter 14 value 746.397393
#> final value 746.397393
#> converged
#> This is Run number 241
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 3.2343132 2.7430822 0.8843132 -9.4569178 1
#> 2 1 -6.20 -3.90 1.7514500 0.2686245 -4.4485500 -3.6313755 2
#> 3 1 -14.20 -5.80 1.7276140 1.6995864 -12.4723860 -4.1004136 2
#> 4 1 -2.10 -13.20 1.6426924 0.1917824 -0.4573076 -13.0082176 1
#> 5 1 -1.70 -4.30 2.6579869 0.3651781 0.9579869 -3.9348219 1
#> 6 1 -6.90 -1.55 0.9294552 1.1395428 -5.9705448 -0.4104572 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4220 -37125 7300
#> initial value 998.131940
#> iter 2 value 845.043203
#> iter 3 value 841.542907
#> iter 4 value 836.828556
#> iter 5 value 785.539046
#> iter 6 value 775.982584
#> iter 7 value 774.431668
#> iter 8 value 774.405440
#> iter 9 value 774.405375
#> iter 10 value 774.405333
#> iter 10 value 774.405331
#> iter 10 value 774.405327
#> final value 774.405327
#> converged
#> This is Run number 242
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.89544520 1.1578822 -1.4545548 -11.042118 1
#> 2 1 -6.20 -3.90 1.11566543 -1.0685621 -5.0843346 -4.968562 2
#> 3 1 -14.20 -5.80 -0.08291291 1.5410772 -14.2829129 -4.258923 2
#> 4 1 -2.10 -13.20 2.84154000 0.3777172 0.7415400 -12.822283 1
#> 5 1 -1.70 -4.30 0.76117726 1.0133436 -0.9388227 -3.286656 1
#> 6 1 -6.90 -1.55 -0.30470940 0.4522350 -7.2047094 -1.097765 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4860 -38200 8100
#> initial value 998.131940
#> iter 2 value 825.850112
#> iter 3 value 824.451531
#> iter 4 value 822.097550
#> iter 5 value 772.701606
#> iter 6 value 762.932969
#> iter 7 value 761.446672
#> iter 8 value 761.421595
#> iter 9 value 761.421247
#> iter 10 value 761.421037
#> iter 11 value 761.421019
#> iter 12 value 761.420937
#> iter 12 value 761.420937
#> iter 12 value 761.420937
#> final value 761.420937
#> converged
#> This is Run number 243
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.80289733 2.3190678725 -1.547103 -9.880932 1
#> 2 1 -6.20 -3.90 -0.06479988 0.5804386897 -6.264800 -3.319561 2
#> 3 1 -14.20 -5.80 0.15568816 0.5206998146 -14.044312 -5.279300 2
#> 4 1 -2.10 -13.20 4.79622144 0.5605024008 2.696221 -12.639498 1
#> 5 1 -1.70 -4.30 0.37084398 0.3659471744 -1.329156 -3.934053 1
#> 6 1 -6.90 -1.55 -0.65688212 0.0005944527 -7.556882 -1.549406 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5000 -38275 7175
#> initial value 998.131940
#> iter 2 value 830.213683
#> iter 3 value 827.847365
#> iter 4 value 824.660784
#> iter 5 value 777.543238
#> iter 6 value 767.574103
#> iter 7 value 766.082779
#> iter 8 value 766.053095
#> iter 9 value 766.052959
#> iter 10 value 766.052768
#> iter 10 value 766.052767
#> iter 11 value 766.052718
#> iter 12 value 766.052693
#> iter 12 value 766.052684
#> iter 12 value 766.052678
#> final value 766.052678
#> converged
#> This is Run number 244
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.7374863 -1.7841795 -0.6125137 -13.9841795 1
#> 2 1 -6.20 -3.90 1.2681919 4.4311791 -4.9318081 0.5311791 2
#> 3 1 -14.20 -5.80 -0.9198659 -1.3338836 -15.1198659 -7.1338836 2
#> 4 1 -2.10 -13.20 3.0491093 -0.2883479 0.9491093 -13.4883479 1
#> 5 1 -1.70 -4.30 1.2145476 1.0413194 -0.4854524 -3.2586806 1
#> 6 1 -6.90 -1.55 0.7897933 2.0323293 -6.1102067 0.4823293 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4380 -35400 7900
#> initial value 998.131940
#> iter 2 value 863.721718
#> iter 3 value 850.141443
#> iter 4 value 849.104956
#> iter 5 value 805.064294
#> iter 6 value 797.452035
#> iter 7 value 796.163852
#> iter 8 value 796.124375
#> iter 9 value 796.123798
#> iter 10 value 796.123637
#> iter 11 value 796.123440
#> iter 12 value 796.123327
#> iter 12 value 796.123327
#> iter 12 value 796.123327
#> final value 796.123327
#> converged
#> This is Run number 245
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 3.19440633 -0.41301540 0.8444063 -12.613015 1
#> 2 1 -6.20 -3.90 0.94827336 1.38310947 -5.2517266 -2.516891 2
#> 3 1 -14.20 -5.80 -1.15488533 1.85201664 -15.3548853 -3.947983 2
#> 4 1 -2.10 -13.20 -0.71407583 1.47823072 -2.8140758 -11.721769 1
#> 5 1 -1.70 -4.30 1.89396201 1.66492594 0.1939620 -2.635074 1
#> 6 1 -6.90 -1.55 -0.06012311 -0.09178225 -6.9601231 -1.641782 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4880 -35700 7775
#> initial value 998.131940
#> iter 2 value 861.009295
#> iter 3 value 848.537322
#> iter 4 value 848.144897
#> iter 5 value 805.226327
#> iter 6 value 797.441832
#> iter 7 value 796.147782
#> iter 8 value 796.111376
#> iter 9 value 796.110894
#> iter 10 value 796.110724
#> iter 11 value 796.110491
#> iter 12 value 796.110364
#> iter 12 value 796.110364
#> iter 12 value 796.110364
#> final value 796.110364
#> converged
#> This is Run number 246
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.4211629 -0.4670171 -0.9288371 -12.667017 1
#> 2 1 -6.20 -3.90 1.3642335 1.0634425 -4.8357665 -2.836557 2
#> 3 1 -14.20 -5.80 -0.1407627 -0.6584476 -14.3407627 -6.458448 2
#> 4 1 -2.10 -13.20 5.0803110 -0.1165087 2.9803110 -13.316509 1
#> 5 1 -1.70 -4.30 -0.3237473 -0.2534970 -2.0237473 -4.553497 1
#> 6 1 -6.90 -1.55 -0.3267394 -1.5831361 -7.2267394 -3.133136 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4640 -37325 8075
#> initial value 998.131940
#> iter 2 value 838.103580
#> iter 3 value 837.846563
#> iter 4 value 835.499652
#> iter 5 value 783.028829
#> iter 6 value 773.513889
#> iter 7 value 772.003318
#> iter 8 value 771.977959
#> iter 9 value 771.977570
#> iter 10 value 771.977517
#> iter 10 value 771.977516
#> iter 11 value 771.977406
#> iter 12 value 771.977381
#> iter 12 value 771.977375
#> iter 13 value 771.977354
#> iter 13 value 771.977350
#> iter 13 value 771.977349
#> final value 771.977349
#> converged
#> This is Run number 247
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.3959167 2.2706722 -2.7459167 -9.929328 1
#> 2 1 -6.20 -3.90 -1.3521366 0.9617223 -7.5521366 -2.938278 2
#> 3 1 -14.20 -5.80 0.2731979 0.5496064 -13.9268021 -5.250394 2
#> 4 1 -2.10 -13.20 0.4483795 0.2512043 -1.6516205 -12.948796 1
#> 5 1 -1.70 -4.30 1.2282968 1.7412562 -0.4717032 -2.558744 1
#> 6 1 -6.90 -1.55 1.4250086 -0.7443913 -5.4749914 -2.294391 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4100 -37750 8175
#> initial value 998.131940
#> iter 2 value 831.237477
#> iter 3 value 827.393848
#> iter 4 value 822.370617
#> iter 5 value 771.518197
#> iter 6 value 761.960920
#> iter 7 value 760.406305
#> iter 8 value 760.383028
#> iter 9 value 760.382981
#> iter 10 value 760.382818
#> iter 10 value 760.382818
#> iter 10 value 760.382807
#> final value 760.382807
#> converged
#> This is Run number 248
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.01346409 0.6818874 -1.336536 -11.5181126 1
#> 2 1 -6.20 -3.90 -0.57800453 -0.2467242 -6.778005 -4.1467242 2
#> 3 1 -14.20 -5.80 0.41616299 -0.3872476 -13.783837 -6.1872476 2
#> 4 1 -2.10 -13.20 -0.03474797 -0.9544492 -2.134748 -14.1544492 1
#> 5 1 -1.70 -4.30 -0.84659199 0.8223439 -2.546592 -3.4776561 1
#> 6 1 -6.90 -1.55 -1.03292094 1.4418269 -7.932921 -0.1081731 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4940 -38525 8050
#> initial value 998.131940
#> iter 2 value 821.502531
#> iter 3 value 819.614231
#> iter 4 value 817.171445
#> iter 5 value 769.061986
#> iter 6 value 759.207915
#> iter 7 value 757.738131
#> iter 8 value 757.713088
#> iter 9 value 757.712770
#> iter 10 value 757.712539
#> iter 10 value 757.712529
#> iter 11 value 757.712481
#> iter 12 value 757.712434
#> iter 12 value 757.712433
#> iter 12 value 757.712424
#> final value 757.712424
#> converged
#> This is Run number 249
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.675063313 -0.354143238 -1.674937 -12.5541432 1
#> 2 1 -6.20 -3.90 0.016680353 -0.181195330 -6.183320 -4.0811953 2
#> 3 1 -14.20 -5.80 1.119773706 -0.007716459 -13.080226 -5.8077165 2
#> 4 1 -2.10 -13.20 -1.019716587 0.813660684 -3.119717 -12.3863393 1
#> 5 1 -1.70 -4.30 -0.009039244 -0.046969906 -1.709039 -4.3469699 1
#> 6 1 -6.90 -1.55 -0.598067427 1.224129456 -7.498067 -0.3258705 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4460 -34550 8075
#> initial value 998.131940
#> iter 2 value 872.690871
#> iter 3 value 859.124817
#> iter 4 value 858.728678
#> iter 5 value 814.269957
#> iter 6 value 807.053891
#> iter 7 value 805.962897
#> iter 8 value 805.937509
#> iter 9 value 805.937216
#> iter 10 value 805.937102
#> iter 11 value 805.936938
#> iter 12 value 805.936854
#> iter 12 value 805.936854
#> iter 12 value 805.936854
#> final value 805.936854
#> converged
#> This is Run number 250
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.6737905 0.5366978 -3.023790 -11.6633022 1
#> 2 1 -6.20 -3.90 -1.0552016 1.4407607 -7.255202 -2.4592393 2
#> 3 1 -14.20 -5.80 0.6952433 1.9591203 -13.504757 -3.8408797 2
#> 4 1 -2.10 -13.20 0.9222169 0.9959376 -1.177783 -12.2040624 1
#> 5 1 -1.70 -4.30 -0.2940708 -1.1843768 -1.994071 -5.4843768 1
#> 6 1 -6.90 -1.55 0.7387849 1.2373763 -6.161215 -0.3126237 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4840 -36550 6675
#> initial value 998.131940
#> iter 2 value 856.304166
#> iter 3 value 855.826251
#> iter 4 value 853.267279
#> iter 5 value 801.359351
#> iter 6 value 791.997910
#> iter 7 value 790.416992
#> iter 8 value 790.384328
#> iter 9 value 790.384231
#> iter 10 value 790.384021
#> iter 10 value 790.384020
#> iter 10 value 790.384015
#> final value 790.384015
#> converged
#> This is Run number 251
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.35574548 -0.426004759 -3.705745 -12.626005 1
#> 2 1 -6.20 -3.90 -0.06524111 -0.096986246 -6.265241 -3.996986 2
#> 3 1 -14.20 -5.80 -0.10959214 1.202041309 -14.309592 -4.597959 2
#> 4 1 -2.10 -13.20 -0.47824362 2.074851064 -2.578244 -11.125149 1
#> 5 1 -1.70 -4.30 -0.44198468 0.004047382 -2.141985 -4.295953 1
#> 6 1 -6.90 -1.55 2.10722232 -0.689602931 -4.792778 -2.239603 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4740 -38550 7200
#> initial value 998.131940
#> iter 2 value 826.008514
#> iter 3 value 821.717030
#> iter 4 value 817.124282
#> iter 5 value 771.120170
#> iter 6 value 761.100213
#> iter 7 value 759.605856
#> iter 8 value 759.577883
#> iter 9 value 759.577777
#> iter 9 value 759.577766
#> iter 9 value 759.577763
#> final value 759.577763
#> converged
#> This is Run number 252
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.7543915 -0.3203302 -0.5956085 -12.5203302 1
#> 2 1 -6.20 -3.90 -0.2707458 0.7089252 -6.4707458 -3.1910748 2
#> 3 1 -14.20 -5.80 -0.5215159 -0.3763422 -14.7215159 -6.1763422 2
#> 4 1 -2.10 -13.20 1.1762452 2.2905682 -0.9237548 -10.9094318 1
#> 5 1 -1.70 -4.30 0.8568102 0.2498012 -0.8431898 -4.0501988 1
#> 6 1 -6.90 -1.55 0.1403917 1.4049789 -6.7596083 -0.1450211 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5380 -39450 8050
#> initial value 998.131940
#> iter 2 value 807.753579
#> iter 3 value 805.501039
#> iter 4 value 803.795725
#> iter 5 value 759.008537
#> iter 6 value 748.966950
#> iter 7 value 747.546132
#> iter 8 value 747.521413
#> iter 9 value 747.521312
#> iter 10 value 747.520745
#> iter 10 value 747.520734
#> iter 11 value 747.520599
#> iter 12 value 747.520576
#> iter 13 value 747.520560
#> iter 13 value 747.520558
#> iter 13 value 747.520558
#> final value 747.520558
#> converged
#> This is Run number 253
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.5651526 2.2172693 -2.9151526 -9.982731 1
#> 2 1 -6.20 -3.90 -0.7417840 -0.1839346 -6.9417840 -4.083935 2
#> 3 1 -14.20 -5.80 1.4079297 1.4395377 -12.7920703 -4.360462 2
#> 4 1 -2.10 -13.20 1.9313503 -0.1102003 -0.1686497 -13.310200 1
#> 5 1 -1.70 -4.30 -0.1645268 0.2509864 -1.8645268 -4.049014 1
#> 6 1 -6.90 -1.55 1.4543051 0.4214847 -5.4456949 -1.128515 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5620 -37875 6300
#> initial value 998.131940
#> iter 2 value 840.318574
#> iter 3 value 839.756244
#> iter 4 value 837.988288
#> iter 5 value 791.189724
#> iter 6 value 781.276146
#> iter 7 value 779.590586
#> iter 8 value 779.547364
#> iter 9 value 779.547197
#> iter 10 value 779.546984
#> iter 10 value 779.546984
#> iter 11 value 779.546945
#> iter 12 value 779.546920
#> iter 12 value 779.546920
#> iter 12 value 779.546919
#> final value 779.546919
#> converged
#> This is Run number 254
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.7303440 1.91143748 -3.080344 -10.2885625 1
#> 2 1 -6.20 -3.90 0.8262939 3.08966653 -5.373706 -0.8103335 2
#> 3 1 -14.20 -5.80 1.3964165 0.32091622 -12.803583 -5.4790838 2
#> 4 1 -2.10 -13.20 -0.4686648 -0.86700709 -2.568665 -14.0670071 1
#> 5 1 -1.70 -4.30 -0.5282651 -0.23292143 -2.228265 -4.5329214 1
#> 6 1 -6.90 -1.55 3.0534335 -0.06342435 -3.846567 -1.6134244 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5580 -38175 6850
#> initial value 998.131940
#> iter 2 value 833.361684
#> iter 3 value 832.933578
#> iter 4 value 831.446188
#> iter 5 value 784.528875
#> iter 6 value 774.504223
#> iter 7 value 772.950464
#> iter 8 value 772.912456
#> iter 9 value 772.912262
#> iter 10 value 772.911788
#> iter 10 value 772.911777
#> iter 11 value 772.911754
#> iter 12 value 772.911700
#> iter 12 value 772.911698
#> iter 12 value 772.911696
#> final value 772.911696
#> converged
#> This is Run number 255
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.66801453 -1.07769098 -0.6819855 -13.277691 1
#> 2 1 -6.20 -3.90 -0.80293569 -0.84698522 -7.0029357 -4.746985 2
#> 3 1 -14.20 -5.80 0.03256312 0.19592351 -14.1674369 -5.604076 2
#> 4 1 -2.10 -13.20 -0.50600387 -1.00538403 -2.6060039 -14.205384 1
#> 5 1 -1.70 -4.30 0.25586647 -0.33696877 -1.4441335 -4.636969 1
#> 6 1 -6.90 -1.55 -0.10996734 0.05244321 -7.0099673 -1.497557 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5160 -37475 7625
#> initial value 998.131940
#> iter 2 value 838.891743
#> iter 3 value 826.623182
#> iter 4 value 825.813382
#> iter 5 value 785.958153
#> iter 6 value 777.475745
#> iter 7 value 775.999707
#> iter 8 value 775.941633
#> iter 9 value 775.940613
#> iter 10 value 775.940396
#> iter 11 value 775.940136
#> iter 12 value 775.939946
#> iter 12 value 775.939946
#> iter 12 value 775.939946
#> final value 775.939946
#> converged
#> This is Run number 256
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.67534494 -1.0501892 -3.0253449 -13.250189 1
#> 2 1 -6.20 -3.90 1.60735572 0.2543263 -4.5926443 -3.645674 2
#> 3 1 -14.20 -5.80 1.71064006 0.4454262 -12.4893599 -5.354574 2
#> 4 1 -2.10 -13.20 -0.81746349 -0.5347361 -2.9174635 -13.734736 1
#> 5 1 -1.70 -4.30 0.73245545 -0.4573337 -0.9675446 -4.757334 1
#> 6 1 -6.90 -1.55 0.05082333 -0.6406013 -6.8491767 -2.190601 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4540 -36125 7675
#> initial value 998.131940
#> iter 2 value 856.185337
#> iter 3 value 843.183098
#> iter 4 value 841.846232
#> iter 5 value 798.705347
#> iter 6 value 790.755002
#> iter 7 value 789.285494
#> iter 8 value 789.234249
#> iter 9 value 789.233455
#> iter 10 value 789.233293
#> iter 11 value 789.233105
#> iter 12 value 789.232981
#> iter 12 value 789.232981
#> iter 12 value 789.232981
#> final value 789.232981
#> converged
#> This is Run number 257
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.3828843 -1.28299968 -1.967116 -13.483000 1
#> 2 1 -6.20 -3.90 1.4373883 1.56690704 -4.762612 -2.333093 2
#> 3 1 -14.20 -5.80 0.4611053 0.19804591 -13.738895 -5.601954 2
#> 4 1 -2.10 -13.20 0.2877794 -1.24220136 -1.812221 -14.442201 1
#> 5 1 -1.70 -4.30 -0.9626279 0.06948724 -2.662628 -4.230513 1
#> 6 1 -6.90 -1.55 -0.8353488 0.29029210 -7.735349 -1.259708 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4500 -36775 8175
#> initial value 998.131940
#> iter 2 value 844.760231
#> iter 3 value 830.071996
#> iter 4 value 828.726098
#> iter 5 value 787.161650
#> iter 6 value 779.064801
#> iter 7 value 777.807394
#> iter 8 value 777.758604
#> iter 9 value 777.757748
#> iter 10 value 777.757582
#> iter 11 value 777.757408
#> iter 12 value 777.757274
#> iter 12 value 777.757274
#> iter 12 value 777.757274
#> final value 777.757274
#> converged
#> This is Run number 258
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.63059651 -0.1028855 -2.980597 -12.3028855 1
#> 2 1 -6.20 -3.90 -0.03358859 3.4414384 -6.233589 -0.4585616 2
#> 3 1 -14.20 -5.80 1.75005727 -0.9720768 -12.449943 -6.7720768 2
#> 4 1 -2.10 -13.20 0.58754051 -0.7065826 -1.512459 -13.9065826 1
#> 5 1 -1.70 -4.30 0.02168703 1.9600223 -1.678313 -2.3399777 1
#> 6 1 -6.90 -1.55 2.38244858 -0.2154154 -4.517551 -1.7654154 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4120 -36500 9400
#> initial value 998.131940
#> iter 2 value 839.811453
#> iter 3 value 820.781442
#> iter 4 value 819.937936
#> iter 5 value 779.144524
#> iter 6 value 771.618301
#> iter 7 value 770.836833
#> iter 8 value 770.805061
#> iter 9 value 770.804563
#> iter 10 value 770.804379
#> iter 11 value 770.804124
#> iter 12 value 770.803998
#> iter 12 value 770.803998
#> iter 12 value 770.803998
#> final value 770.803998
#> converged
#> This is Run number 259
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.9529708 -0.5702410 -1.397029 -12.770241 1
#> 2 1 -6.20 -3.90 1.3823365 1.8521584 -4.817664 -2.047842 2
#> 3 1 -14.20 -5.80 -0.6998242 0.9640390 -14.899824 -4.835961 2
#> 4 1 -2.10 -13.20 -0.2242287 0.9418883 -2.324229 -12.258112 1
#> 5 1 -1.70 -4.30 -0.9306554 0.8394361 -2.630655 -3.460564 1
#> 6 1 -6.90 -1.55 0.4112747 -0.2651830 -6.488725 -1.815183 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4860 -38175 7575
#> initial value 998.131940
#> iter 2 value 829.356045
#> iter 3 value 827.237087
#> iter 4 value 824.174926
#> iter 5 value 775.860460
#> iter 6 value 765.998534
#> iter 7 value 764.521306
#> iter 8 value 764.494171
#> iter 9 value 764.493838
#> iter 10 value 764.493724
#> iter 10 value 764.493724
#> iter 11 value 764.493702
#> iter 12 value 764.493636
#> iter 12 value 764.493636
#> iter 12 value 764.493633
#> final value 764.493633
#> converged
#> This is Run number 260
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.3154995 -0.9482555 -2.665500 -13.148256 1
#> 2 1 -6.20 -3.90 -0.5864451 2.5955753 -6.786445 -1.304425 2
#> 3 1 -14.20 -5.80 0.5288345 1.7725477 -13.671165 -4.027452 2
#> 4 1 -2.10 -13.20 1.5139850 0.6695697 -0.586015 -12.530430 1
#> 5 1 -1.70 -4.30 -0.4281403 0.1615318 -2.128140 -4.138468 1
#> 6 1 -6.90 -1.55 -0.2336292 -1.2261673 -7.133629 -2.776167 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4800 -38125 9050
#> initial value 998.131940
#> iter 2 value 820.610838
#> iter 3 value 820.281970
#> iter 4 value 818.908529
#> iter 5 value 767.173012
#> iter 6 value 757.601195
#> iter 7 value 756.042654
#> iter 8 value 756.021016
#> iter 9 value 756.020830
#> iter 10 value 756.020627
#> iter 10 value 756.020617
#> iter 11 value 756.020584
#> iter 12 value 756.020562
#> iter 12 value 756.020556
#> iter 12 value 756.020550
#> final value 756.020550
#> converged
#> This is Run number 261
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.95104985 -0.4310288 -1.398950 -12.6310288 1
#> 2 1 -6.20 -3.90 0.17441897 -0.5800786 -6.025581 -4.4800786 2
#> 3 1 -14.20 -5.80 2.08681824 -1.3266877 -12.113182 -7.1266877 2
#> 4 1 -2.10 -13.20 -0.12456566 0.7619312 -2.224566 -12.4380688 1
#> 5 1 -1.70 -4.30 -0.17299350 0.3018050 -1.872993 -3.9981950 1
#> 6 1 -6.90 -1.55 -0.03823451 1.2993148 -6.938235 -0.2506852 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5160 -38475 8100
#> initial value 998.131940
#> iter 2 value 821.949253
#> iter 3 value 821.011750
#> iter 4 value 819.456812
#> iter 5 value 771.042176
#> iter 6 value 761.161193
#> iter 7 value 759.685103
#> iter 8 value 759.659196
#> iter 9 value 759.658799
#> iter 10 value 759.658581
#> iter 11 value 759.658532
#> iter 12 value 759.658424
#> iter 12 value 759.658424
#> iter 12 value 759.658424
#> final value 759.658424
#> converged
#> This is Run number 262
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.7064619 2.0096444 -1.643538 -10.190356 1
#> 2 1 -6.20 -3.90 1.3205672 0.1436868 -4.879433 -3.756313 2
#> 3 1 -14.20 -5.80 1.2144921 0.5944948 -12.985508 -5.205505 2
#> 4 1 -2.10 -13.20 -0.5755310 0.8272430 -2.675531 -12.372757 1
#> 5 1 -1.70 -4.30 -0.2975813 -1.2849693 -1.997581 -5.584969 1
#> 6 1 -6.90 -1.55 -0.9083996 1.3951720 -7.808400 -0.154828 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4960 -37725 8425
#> initial value 998.131940
#> iter 2 value 830.492831
#> iter 3 value 815.599456
#> iter 4 value 814.979245
#> iter 5 value 776.162255
#> iter 6 value 767.800039
#> iter 7 value 766.725441
#> iter 8 value 766.680067
#> iter 9 value 766.679210
#> iter 10 value 766.679164
#> iter 11 value 766.678874
#> iter 12 value 766.678505
#> iter 12 value 766.678505
#> iter 12 value 766.678505
#> final value 766.678505
#> converged
#> This is Run number 263
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.1122481 -0.08075542 -2.462248 -12.2807554 1
#> 2 1 -6.20 -3.90 -1.2107533 0.17632669 -7.410753 -3.7236733 2
#> 3 1 -14.20 -5.80 2.1538025 -0.10911869 -12.046197 -5.9091187 2
#> 4 1 -2.10 -13.20 -0.9958497 -1.08144334 -3.095850 -14.2814433 1
#> 5 1 -1.70 -4.30 -0.6229861 1.79538750 -2.322986 -2.5046125 1
#> 6 1 -6.90 -1.55 2.1347198 1.04684593 -4.765280 -0.5031541 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4560 -36375 7925
#> initial value 998.131940
#> iter 2 value 851.526507
#> iter 3 value 837.809206
#> iter 4 value 836.608832
#> iter 5 value 794.243787
#> iter 6 value 786.234732
#> iter 7 value 784.888406
#> iter 8 value 784.840226
#> iter 9 value 784.839434
#> iter 10 value 784.839261
#> iter 11 value 784.839064
#> iter 12 value 784.838929
#> iter 12 value 784.838929
#> iter 12 value 784.838929
#> final value 784.838929
#> converged
#> This is Run number 264
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.8148613 -1.4854678 -3.1648613 -13.685468 1
#> 2 1 -6.20 -3.90 1.7163049 -1.2015542 -4.4836951 -5.101554 1
#> 3 1 -14.20 -5.80 1.5685297 1.0586762 -12.6314703 -4.741324 2
#> 4 1 -2.10 -13.20 0.5167421 0.4533081 -1.5832579 -12.746692 1
#> 5 1 -1.70 -4.30 1.7469247 -0.3183840 0.0469247 -4.618384 1
#> 6 1 -6.90 -1.55 0.2983296 -0.2016370 -6.6016704 -1.751637 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4920 -39150 7725
#> initial value 998.131940
#> iter 2 value 814.220916
#> iter 3 value 810.360705
#> iter 4 value 806.607949
#> iter 5 value 761.602464
#> iter 6 value 751.584065
#> iter 7 value 750.151405
#> iter 8 value 750.126374
#> iter 9 value 750.126266
#> iter 10 value 750.125978
#> iter 10 value 750.125967
#> iter 11 value 750.125926
#> iter 12 value 750.125905
#> iter 13 value 750.125890
#> iter 13 value 750.125885
#> iter 13 value 750.125884
#> final value 750.125884
#> converged
#> This is Run number 265
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.2283242 0.6513222 -2.1216758 -11.5486778 1
#> 2 1 -6.20 -3.90 -0.7800968 0.8473252 -6.9800968 -3.0526748 2
#> 3 1 -14.20 -5.80 0.2469707 0.1323707 -13.9530293 -5.6676293 2
#> 4 1 -2.10 -13.20 -0.2966443 -1.0750012 -2.3966443 -14.2750012 1
#> 5 1 -1.70 -4.30 0.9565836 0.1384165 -0.7434164 -4.1615835 1
#> 6 1 -6.90 -1.55 0.7973541 2.5471965 -6.1026459 0.9971965 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4200 -37700 8925
#> initial value 998.131940
#> iter 2 value 827.113561
#> iter 3 value 825.467210
#> iter 4 value 822.067160
#> iter 5 value 769.081762
#> iter 6 value 759.696170
#> iter 7 value 758.099541
#> iter 8 value 758.076916
#> iter 9 value 758.076818
#> iter 10 value 758.076660
#> iter 10 value 758.076658
#> iter 11 value 758.076640
#> iter 11 value 758.076630
#> iter 11 value 758.076630
#> final value 758.076630
#> converged
#> This is Run number 266
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.04988001 0.9639194 -2.300120 -11.2360806 1
#> 2 1 -6.20 -3.90 -1.17592102 -0.2901711 -7.375921 -4.1901711 2
#> 3 1 -14.20 -5.80 1.55538326 1.4798673 -12.644617 -4.3201327 2
#> 4 1 -2.10 -13.20 0.23459976 1.0964539 -1.865400 -12.1035461 1
#> 5 1 -1.70 -4.30 -0.39103993 3.8455579 -2.091040 -0.4544421 2
#> 6 1 -6.90 -1.55 0.05794937 1.9561793 -6.842051 0.4061793 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4700 -38375 8000
#> initial value 998.131940
#> iter 2 value 823.894177
#> iter 3 value 821.243907
#> iter 4 value 817.903597
#> iter 5 value 769.455472
#> iter 6 value 759.657090
#> iter 7 value 758.176145
#> iter 8 value 758.151645
#> iter 9 value 758.151426
#> iter 10 value 758.151344
#> iter 10 value 758.151344
#> iter 11 value 758.151267
#> iter 12 value 758.151160
#> iter 12 value 758.151160
#> iter 13 value 758.151144
#> iter 13 value 758.151135
#> iter 13 value 758.151135
#> final value 758.151135
#> converged
#> This is Run number 267
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.828903057 -0.1824931 -0.5210969 -12.3824931 1
#> 2 1 -6.20 -3.90 0.441459107 4.6791642 -5.7585409 0.7791642 2
#> 3 1 -14.20 -5.80 0.095236506 3.4767301 -14.1047635 -2.3232699 2
#> 4 1 -2.10 -13.20 0.020543487 -0.6294502 -2.0794565 -13.8294502 1
#> 5 1 -1.70 -4.30 -0.008758834 0.2029718 -1.7087588 -4.0970282 1
#> 6 1 -6.90 -1.55 -1.692136742 -0.3424918 -8.5921367 -1.8924918 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5020 -36675 7850
#> initial value 998.131940
#> iter 2 value 848.233821
#> iter 3 value 835.441413
#> iter 4 value 834.940109
#> iter 5 value 793.791188
#> iter 6 value 785.620153
#> iter 7 value 784.309815
#> iter 8 value 784.265680
#> iter 9 value 784.264976
#> iter 10 value 784.264767
#> iter 11 value 784.264495
#> iter 12 value 784.264325
#> iter 12 value 784.264325
#> iter 12 value 784.264325
#> final value 784.264325
#> converged
#> This is Run number 268
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.2309816 0.6199279 -3.58098162 -11.5800721 1
#> 2 1 -6.20 -3.90 -0.2565846 1.0923968 -6.45658461 -2.8076032 2
#> 3 1 -14.20 -5.80 -0.1506538 0.4196866 -14.35065376 -5.3803134 2
#> 4 1 -2.10 -13.20 -0.1869117 -1.0559504 -2.28691167 -14.2559504 1
#> 5 1 -1.70 -4.30 1.6637279 -0.2638964 -0.03627212 -4.5638964 1
#> 6 1 -6.90 -1.55 1.4635455 0.9208483 -5.43645455 -0.6291517 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4020 -35875 7950
#> initial value 998.131940
#> iter 2 value 857.302590
#> iter 3 value 842.593746
#> iter 4 value 840.429176
#> iter 5 value 796.041655
#> iter 6 value 788.226637
#> iter 7 value 786.835305
#> iter 8 value 786.784962
#> iter 9 value 786.784224
#> iter 10 value 786.784124
#> iter 11 value 786.784043
#> iter 12 value 786.783972
#> iter 12 value 786.783972
#> iter 12 value 786.783972
#> final value 786.783972
#> converged
#> This is Run number 269
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.4071624 4.7951792 -2.7571624 -7.404821 1
#> 2 1 -6.20 -3.90 -0.2358374 0.2047911 -6.4358374 -3.695209 2
#> 3 1 -14.20 -5.80 2.3787943 -0.6797464 -11.8212057 -6.479746 2
#> 4 1 -2.10 -13.20 1.1462626 0.8334918 -0.9537374 -12.366508 1
#> 5 1 -1.70 -4.30 0.4521959 -0.4411602 -1.2478041 -4.741160 1
#> 6 1 -6.90 -1.55 0.5487390 0.5310566 -6.3512610 -1.018943 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4520 -36200 8725
#> initial value 998.131940
#> iter 2 value 848.634824
#> iter 3 value 832.650705
#> iter 4 value 832.150745
#> iter 5 value 790.763260
#> iter 6 value 783.004880
#> iter 7 value 782.070269
#> iter 8 value 782.039690
#> iter 9 value 782.039192
#> iter 10 value 782.039015
#> iter 11 value 782.038771
#> iter 12 value 782.038626
#> iter 12 value 782.038626
#> iter 12 value 782.038626
#> final value 782.038626
#> converged
#> This is Run number 270
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.233550199 0.1655327 -2.583550 -12.0344673 1
#> 2 1 -6.20 -3.90 -0.263935875 3.3334062 -6.463936 -0.5665938 2
#> 3 1 -14.20 -5.80 0.001955034 1.0132645 -14.198045 -4.7867355 2
#> 4 1 -2.10 -13.20 -0.034781464 -0.7535538 -2.134781 -13.9535538 1
#> 5 1 -1.70 -4.30 -0.747101450 0.3706924 -2.447101 -3.9293076 1
#> 6 1 -6.90 -1.55 -0.230059827 0.6358891 -7.130060 -0.9141109 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5200 -38200 8075
#> initial value 998.131940
#> iter 2 value 826.056095
#> iter 3 value 825.772761
#> iter 4 value 824.518376
#> iter 5 value 775.198907
#> iter 6 value 765.354159
#> iter 7 value 763.863902
#> iter 8 value 763.836969
#> iter 9 value 763.836508
#> iter 10 value 763.836366
#> iter 11 value 763.836300
#> iter 12 value 763.836184
#> iter 12 value 763.836184
#> iter 12 value 763.836184
#> final value 763.836184
#> converged
#> This is Run number 271
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.58054380 -1.1285687 -1.769456 -13.328569 1
#> 2 1 -6.20 -3.90 0.02388196 -0.1766518 -6.176118 -4.076652 2
#> 3 1 -14.20 -5.80 2.00012293 4.3443098 -12.199877 -1.455690 2
#> 4 1 -2.10 -13.20 -0.08388964 -0.2594556 -2.183890 -13.459456 1
#> 5 1 -1.70 -4.30 0.25895436 2.8456051 -1.441046 -1.454395 1
#> 6 1 -6.90 -1.55 0.80672041 0.4484857 -6.093280 -1.101514 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5120 -38175 7350
#> initial value 998.131940
#> iter 2 value 830.696016
#> iter 3 value 829.328458
#> iter 4 value 826.953553
#> iter 5 value 779.041523
#> iter 6 value 769.112183
#> iter 7 value 767.628852
#> iter 8 value 767.598714
#> iter 9 value 767.598537
#> iter 10 value 767.598190
#> iter 10 value 767.598186
#> iter 11 value 767.598156
#> iter 12 value 767.598080
#> iter 13 value 767.598064
#> iter 14 value 767.598051
#> iter 14 value 767.598051
#> iter 14 value 767.598051
#> final value 767.598051
#> converged
#> This is Run number 272
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.6604348 0.5794324 -3.010435 -11.620568 1
#> 2 1 -6.20 -3.90 -0.1993343 0.4997224 -6.399334 -3.400278 2
#> 3 1 -14.20 -5.80 3.3199862 -0.7270863 -10.880014 -6.527086 2
#> 4 1 -2.10 -13.20 -0.1088352 -1.4307371 -2.208835 -14.630737 1
#> 5 1 -1.70 -4.30 -0.9789592 -0.6404310 -2.678959 -4.940431 1
#> 6 1 -6.90 -1.55 0.6489310 -0.6369424 -6.251069 -2.186942 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4340 -37400 7700
#> initial value 998.131940
#> iter 2 value 839.149646
#> iter 3 value 836.576789
#> iter 4 value 832.456752
#> iter 5 value 781.245043
#> iter 6 value 771.673605
#> iter 7 value 770.154351
#> iter 8 value 770.129430
#> iter 9 value 770.129226
#> iter 9 value 770.129225
#> iter 10 value 770.129156
#> iter 10 value 770.129145
#> iter 10 value 770.129145
#> final value 770.129145
#> converged
#> This is Run number 273
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.5223860 1.8968617 -1.827614 -10.303138 1
#> 2 1 -6.20 -3.90 4.4259297 -0.6392413 -1.774070 -4.539241 1
#> 3 1 -14.20 -5.80 3.4536777 1.4396279 -10.746322 -4.360372 2
#> 4 1 -2.10 -13.20 0.8614061 0.3016300 -1.238594 -12.898370 1
#> 5 1 -1.70 -4.30 0.2241985 -0.8381999 -1.475801 -5.138200 1
#> 6 1 -6.90 -1.55 -0.3639845 0.5463087 -7.263984 -1.003691 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4820 -37125 7025
#> initial value 998.131940
#> iter 2 value 846.910817
#> iter 3 value 845.902215
#> iter 4 value 843.099146
#> iter 5 value 792.314042
#> iter 6 value 782.727075
#> iter 7 value 781.191067
#> iter 8 value 781.160280
#> iter 9 value 781.160186
#> iter 10 value 781.159880
#> iter 10 value 781.159879
#> iter 11 value 781.159864
#> iter 12 value 781.159849
#> iter 12 value 781.159849
#> iter 12 value 781.159846
#> final value 781.159846
#> converged
#> This is Run number 274
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.43089161 -0.21297977 -2.780892 -12.412980 1
#> 2 1 -6.20 -3.90 1.77042234 -1.08554967 -4.429578 -4.985550 1
#> 3 1 -14.20 -5.80 -0.44869055 -0.44084402 -14.648691 -6.240844 2
#> 4 1 -2.10 -13.20 -0.01103609 0.03377588 -2.111036 -13.166224 1
#> 5 1 -1.70 -4.30 -0.03025948 1.21590417 -1.730259 -3.084096 1
#> 6 1 -6.90 -1.55 2.52717446 0.23636150 -4.372826 -1.313638 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4400 -37500 9175
#> initial value 998.131940
#> iter 2 value 828.279739
#> iter 3 value 810.111225
#> iter 4 value 809.121716
#> iter 5 value 769.800309
#> iter 6 value 761.889672
#> iter 7 value 761.012448
#> iter 8 value 760.970723
#> iter 9 value 760.970031
#> iter 10 value 760.969787
#> iter 11 value 760.969524
#> iter 12 value 760.969438
#> iter 12 value 760.969438
#> iter 12 value 760.969438
#> final value 760.969438
#> converged
#> This is Run number 275
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.7796459 -1.11096906 -3.129646 -13.310969 1
#> 2 1 -6.20 -3.90 -0.6753307 0.22681138 -6.875331 -3.673189 2
#> 3 1 -14.20 -5.80 0.3441147 0.45486160 -13.855885 -5.345138 2
#> 4 1 -2.10 -13.20 0.3724539 -0.06941275 -1.727546 -13.269413 1
#> 5 1 -1.70 -4.30 -1.9011615 0.30025218 -3.601161 -3.999748 1
#> 6 1 -6.90 -1.55 -0.7291533 0.44228200 -7.629153 -1.107718 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5000 -35950 7475
#> initial value 998.131940
#> iter 2 value 859.677299
#> iter 3 value 848.087117
#> iter 4 value 847.583299
#> iter 5 value 804.765037
#> iter 6 value 796.849677
#> iter 7 value 795.377255
#> iter 8 value 795.333027
#> iter 9 value 795.332423
#> iter 10 value 795.332232
#> iter 11 value 795.331972
#> iter 12 value 795.331830
#> iter 12 value 795.331830
#> iter 12 value 795.331830
#> final value 795.331830
#> converged
#> This is Run number 276
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.15805801 -0.082975704 -3.5080580 -12.282976 1
#> 2 1 -6.20 -3.90 -0.06634443 1.716855023 -6.2663444 -2.183145 2
#> 3 1 -14.20 -5.80 1.41271586 -0.790117681 -12.7872841 -6.590118 2
#> 4 1 -2.10 -13.20 2.73969920 0.188038987 0.6396992 -13.011961 1
#> 5 1 -1.70 -4.30 -0.26873676 0.116775524 -1.9687368 -4.183224 1
#> 6 1 -6.90 -1.55 2.25664326 -0.005117227 -4.6433567 -1.555117 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4260 -36400 7450
#> initial value 998.131940
#> iter 2 value 853.780686
#> iter 3 value 852.752212
#> iter 4 value 849.219169
#> iter 5 value 795.046322
#> iter 6 value 785.813806
#> iter 7 value 784.300052
#> iter 8 value 784.274729
#> iter 9 value 784.274645
#> iter 10 value 784.274487
#> iter 10 value 784.274487
#> iter 11 value 784.274460
#> iter 12 value 784.274426
#> iter 12 value 784.274425
#> iter 12 value 784.274419
#> final value 784.274419
#> converged
#> This is Run number 277
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.09351409 1.3824487 -2.256486 -10.817551 1
#> 2 1 -6.20 -3.90 1.29003815 2.1371470 -4.909962 -1.762853 2
#> 3 1 -14.20 -5.80 0.94326935 -0.6044273 -13.256731 -6.404427 2
#> 4 1 -2.10 -13.20 0.06607300 1.4055173 -2.033927 -11.794483 1
#> 5 1 -1.70 -4.30 -0.40273973 2.9278946 -2.102740 -1.372105 2
#> 6 1 -6.90 -1.55 -1.00269218 -0.3565022 -7.902692 -1.906502 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4820 -37200 7725
#> initial value 998.131940
#> iter 2 value 841.979281
#> iter 3 value 828.932466
#> iter 4 value 827.607645
#> iter 5 value 786.763844
#> iter 6 value 778.411699
#> iter 7 value 776.932874
#> iter 8 value 776.873858
#> iter 9 value 776.872833
#> iter 10 value 776.872657
#> iter 11 value 776.872470
#> iter 12 value 776.872323
#> iter 12 value 776.872323
#> iter 12 value 776.872323
#> final value 776.872323
#> converged
#> This is Run number 278
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.4343840 -0.1611722 -3.784384 -12.361172 1
#> 2 1 -6.20 -3.90 1.2707179 0.8410213 -4.929282 -3.058979 2
#> 3 1 -14.20 -5.80 0.2484319 2.3094229 -13.951568 -3.490577 2
#> 4 1 -2.10 -13.20 0.6737509 1.7204311 -1.426249 -11.479569 1
#> 5 1 -1.70 -4.30 -0.6848286 0.5589237 -2.384829 -3.741076 1
#> 6 1 -6.90 -1.55 -0.6632426 4.1271730 -7.563243 2.577173 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4520 -37475 7000
#> initial value 998.131940
#> iter 2 value 842.143624
#> iter 3 value 838.769020
#> iter 4 value 834.439246
#> iter 5 value 784.989187
#> iter 6 value 775.261652
#> iter 7 value 773.705186
#> iter 8 value 773.676039
#> iter 9 value 773.676015
#> iter 10 value 773.675935
#> iter 10 value 773.675932
#> iter 10 value 773.675922
#> final value 773.675922
#> converged
#> This is Run number 279
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.004247866 1.6216892 -2.354248 -10.578311 1
#> 2 1 -6.20 -3.90 0.227818769 0.8483744 -5.972181 -3.051626 2
#> 3 1 -14.20 -5.80 -0.658148406 2.1087128 -14.858148 -3.691287 2
#> 4 1 -2.10 -13.20 -0.152420716 0.5171178 -2.252421 -12.682882 1
#> 5 1 -1.70 -4.30 -0.229338995 -0.2029905 -1.929339 -4.502990 1
#> 6 1 -6.90 -1.55 -1.360208186 -0.4626162 -8.260208 -2.012616 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4980 -37325 8400
#> initial value 998.131940
#> iter 2 value 836.146862
#> iter 3 value 821.516055
#> iter 4 value 821.083678
#> iter 5 value 781.637353
#> iter 6 value 773.368187
#> iter 7 value 772.309884
#> iter 8 value 772.269542
#> iter 9 value 772.268818
#> iter 10 value 772.268602
#> iter 11 value 772.268300
#> iter 12 value 772.268100
#> iter 12 value 772.268100
#> iter 12 value 772.268100
#> final value 772.268100
#> converged
#> This is Run number 280
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.9480277 2.2455868 -1.4019723 -9.954413 1
#> 2 1 -6.20 -3.90 2.8372982 -0.1716139 -3.3627018 -4.071614 1
#> 3 1 -14.20 -5.80 1.5363792 0.1603869 -12.6636208 -5.639613 2
#> 4 1 -2.10 -13.20 -0.4821113 1.4373065 -2.5821113 -11.762693 1
#> 5 1 -1.70 -4.30 0.7980978 1.4797368 -0.9019022 -2.820263 1
#> 6 1 -6.90 -1.55 1.3486664 0.3904670 -5.5513336 -1.159533 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4280 -38325 8225
#> initial value 998.131940
#> iter 2 value 822.939399
#> iter 3 value 818.602670
#> iter 4 value 813.710071
#> iter 5 value 764.864926
#> iter 6 value 755.180950
#> iter 7 value 753.652262
#> iter 8 value 753.628788
#> iter 9 value 753.628721
#> iter 10 value 753.628543
#> iter 10 value 753.628539
#> iter 10 value 753.628529
#> final value 753.628529
#> converged
#> This is Run number 281
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.76026700 -1.5073630 -4.110267 -13.707363 1
#> 2 1 -6.20 -3.90 0.97932205 1.5549443 -5.220678 -2.345056 2
#> 3 1 -14.20 -5.80 1.18773048 0.9124961 -13.012270 -4.887504 2
#> 4 1 -2.10 -13.20 -1.08670805 1.7214012 -3.186708 -11.478599 1
#> 5 1 -1.70 -4.30 0.02013901 1.5039662 -1.679861 -2.796034 1
#> 6 1 -6.90 -1.55 0.26323521 2.5766065 -6.636765 1.026606 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4580 -36850 7625
#> initial value 998.131940
#> iter 2 value 847.130382
#> iter 3 value 846.902338
#> iter 4 value 844.253362
#> iter 5 value 791.176170
#> iter 6 value 781.770767
#> iter 7 value 780.267276
#> iter 8 value 780.240278
#> iter 9 value 780.240114
#> iter 10 value 780.239893
#> iter 10 value 780.239884
#> iter 11 value 780.239859
#> iter 12 value 780.239784
#> iter 13 value 780.239759
#> iter 14 value 780.239702
#> iter 14 value 780.239702
#> iter 14 value 780.239702
#> final value 780.239702
#> converged
#> This is Run number 282
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.8551593 1.3771275 -1.4948407 -10.822873 1
#> 2 1 -6.20 -3.90 -0.2767462 0.9965802 -6.4767462 -2.903420 2
#> 3 1 -14.20 -5.80 -0.0177853 -0.1113018 -14.2177853 -5.911302 2
#> 4 1 -2.10 -13.20 1.0238907 0.5095162 -1.0761093 -12.690484 1
#> 5 1 -1.70 -4.30 1.5266674 0.1667696 -0.1733326 -4.133230 1
#> 6 1 -6.90 -1.55 0.8932593 -0.3741849 -6.0067407 -1.924185 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5260 -38675 6950
#> initial value 998.131940
#> iter 2 value 825.664993
#> iter 3 value 823.277693
#> iter 4 value 820.340607
#> iter 5 value 775.050938
#> iter 6 value 764.923114
#> iter 7 value 763.432323
#> iter 8 value 763.400380
#> iter 9 value 763.400349
#> iter 10 value 763.400069
#> iter 10 value 763.400068
#> iter 11 value 763.399991
#> iter 12 value 763.399977
#> iter 12 value 763.399975
#> iter 12 value 763.399975
#> final value 763.399975
#> converged
#> This is Run number 283
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.5975855 2.9895837 -1.7524145 -9.210416 1
#> 2 1 -6.20 -3.90 1.2699305 -0.2841597 -4.9300695 -4.184160 2
#> 3 1 -14.20 -5.80 -0.7085589 -0.8670847 -14.9085589 -6.667085 2
#> 4 1 -2.10 -13.20 1.8357813 -0.7801554 -0.2642187 -13.980155 1
#> 5 1 -1.70 -4.30 2.5345521 1.0795835 0.8345521 -3.220416 1
#> 6 1 -6.90 -1.55 -0.7463267 -0.3227869 -7.6463267 -1.872787 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3800 -37600 10325
#> initial value 998.131940
#> iter 2 value 817.682918
#> iter 3 value 817.228366
#> iter 4 value 813.955883
#> iter 5 value 756.886581
#> iter 6 value 747.786568
#> iter 7 value 746.046857
#> iter 8 value 746.007141
#> iter 9 value 746.006940
#> iter 9 value 746.006930
#> iter 9 value 746.006928
#> final value 746.006928
#> converged
#> This is Run number 284
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.30704363 1.81076610 -2.6570436 -10.389234 1
#> 2 1 -6.20 -3.90 1.58028159 -0.05677147 -4.6197184 -3.956771 2
#> 3 1 -14.20 -5.80 0.50657932 1.99604598 -13.6934207 -3.803954 2
#> 4 1 -2.10 -13.20 0.44981920 0.12034947 -1.6501808 -13.079651 1
#> 5 1 -1.70 -4.30 0.90013906 0.88369319 -0.7998609 -3.416307 1
#> 6 1 -6.90 -1.55 -0.02221114 -0.88228731 -6.9222111 -2.432287 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4560 -39150 7950
#> initial value 998.131940
#> iter 2 value 812.696466
#> iter 3 value 807.219831
#> iter 4 value 802.079849
#> iter 5 value 756.900392
#> iter 6 value 746.992633
#> iter 7 value 745.525640
#> iter 8 value 745.501380
#> iter 9 value 745.501296
#> iter 10 value 745.501140
#> iter 10 value 745.501132
#> iter 10 value 745.501132
#> final value 745.501132
#> converged
#> This is Run number 285
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.4514838362 1.1894183 0.1014838 -11.010582 1
#> 2 1 -6.20 -3.90 2.1294118579 -0.9889652 -4.0705881 -4.888965 1
#> 3 1 -14.20 -5.80 -0.3639604052 1.2684194 -14.5639604 -4.531581 2
#> 4 1 -2.10 -13.20 -0.0006974039 -0.4515859 -2.1006974 -13.651586 1
#> 5 1 -1.70 -4.30 -0.3924597619 0.5402908 -2.0924598 -3.759709 1
#> 6 1 -6.90 -1.55 -0.7881755944 0.5247585 -7.6881756 -1.025242 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4120 -35500 8875
#> initial value 998.131940
#> iter 2 value 856.074791
#> iter 3 value 839.155430
#> iter 4 value 838.369855
#> iter 5 value 795.624971
#> iter 6 value 788.214396
#> iter 7 value 787.321331
#> iter 8 value 787.293362
#> iter 9 value 787.292919
#> iter 10 value 787.292769
#> iter 11 value 787.292576
#> iter 12 value 787.292462
#> iter 12 value 787.292462
#> iter 12 value 787.292462
#> final value 787.292462
#> converged
#> This is Run number 286
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 3.0581532 0.5032065 0.7081532 -11.696794 1
#> 2 1 -6.20 -3.90 1.4657886 -0.4525641 -4.7342114 -4.352564 2
#> 3 1 -14.20 -5.80 0.3057803 2.0826512 -13.8942197 -3.717349 2
#> 4 1 -2.10 -13.20 0.9985572 -1.3596535 -1.1014428 -14.559653 1
#> 5 1 -1.70 -4.30 -0.1057624 -0.8171847 -1.8057624 -5.117185 1
#> 6 1 -6.90 -1.55 1.3905252 0.1128239 -5.5094748 -1.437176 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4680 -37725 8025
#> initial value 998.131940
#> iter 2 value 832.934852
#> iter 3 value 831.807357
#> iter 4 value 829.145967
#> iter 5 value 778.226169
#> iter 6 value 768.585401
#> iter 7 value 767.085238
#> iter 8 value 767.060011
#> iter 9 value 767.059635
#> iter 10 value 767.059563
#> iter 11 value 767.059549
#> iter 12 value 767.059415
#> iter 12 value 767.059415
#> iter 12 value 767.059415
#> final value 767.059415
#> converged
#> This is Run number 287
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.3746014 0.676434466 -1.975399 -11.52356553 1
#> 2 1 -6.20 -3.90 -0.1081228 -0.398982501 -6.308123 -4.29898250 2
#> 3 1 -14.20 -5.80 3.8639008 -0.015114326 -10.336099 -5.81511433 2
#> 4 1 -2.10 -13.20 3.3042832 -0.627803743 1.204283 -13.82780374 1
#> 5 1 -1.70 -4.30 0.2238921 0.004673063 -1.476108 -4.29532694 1
#> 6 1 -6.90 -1.55 1.0094519 1.560112448 -5.890548 0.01011245 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4680 -37725 8150
#> initial value 998.131940
#> iter 2 value 832.160267
#> iter 3 value 831.232957
#> iter 4 value 828.736999
#> iter 5 value 777.530045
#> iter 6 value 767.910681
#> iter 7 value 766.404506
#> iter 8 value 766.379742
#> iter 9 value 766.379398
#> iter 10 value 766.379236
#> iter 11 value 766.379215
#> iter 12 value 766.379143
#> iter 12 value 766.379143
#> iter 12 value 766.379143
#> final value 766.379143
#> converged
#> This is Run number 288
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.4477791 -0.02290675 -3.797779 -12.222907 1
#> 2 1 -6.20 -3.90 0.1492592 2.26465771 -6.050741 -1.635342 2
#> 3 1 -14.20 -5.80 1.6131790 -1.25167863 -12.586821 -7.051679 2
#> 4 1 -2.10 -13.20 0.8608860 1.85819946 -1.239114 -11.341801 1
#> 5 1 -1.70 -4.30 -0.4602671 -0.35374786 -2.160267 -4.653748 1
#> 6 1 -6.90 -1.55 2.5246221 -0.56342768 -4.375378 -2.113428 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5180 -39225 7825
#> initial value 998.131940
#> iter 2 value 812.547827
#> iter 3 value 809.825646
#> iter 4 value 807.274064
#> iter 5 value 762.164553
#> iter 6 value 752.120804
#> iter 7 value 750.698504
#> iter 8 value 750.673055
#> iter 9 value 750.672742
#> iter 10 value 750.672605
#> iter 10 value 750.672605
#> iter 11 value 750.672503
#> iter 12 value 750.672378
#> iter 12 value 750.672377
#> iter 13 value 750.672363
#> iter 14 value 750.672335
#> iter 14 value 750.672335
#> iter 14 value 750.672334
#> final value 750.672334
#> converged
#> This is Run number 289
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.0156155 0.8217866 -1.334384 -11.378213 1
#> 2 1 -6.20 -3.90 0.9281853 -0.7850243 -5.271815 -4.685024 2
#> 3 1 -14.20 -5.80 -0.7863569 1.4266482 -14.986357 -4.373352 2
#> 4 1 -2.10 -13.20 0.3990939 0.1474919 -1.700906 -13.052508 1
#> 5 1 -1.70 -4.30 -1.0462950 1.5595730 -2.746295 -2.740427 2
#> 6 1 -6.90 -1.55 2.0404020 -0.2830759 -4.859598 -1.833076 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5260 -37750 8000
#> initial value 998.131940
#> iter 2 value 832.848741
#> iter 3 value 819.663993
#> iter 4 value 819.225382
#> iter 5 value 780.460935
#> iter 6 value 771.936724
#> iter 7 value 770.709565
#> iter 8 value 770.660929
#> iter 9 value 770.660036
#> iter 10 value 770.659803
#> iter 11 value 770.659496
#> iter 12 value 770.659276
#> iter 12 value 770.659276
#> iter 12 value 770.659276
#> final value 770.659276
#> converged
#> This is Run number 290
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.4073788 3.8165215 -3.75737879 -8.383479 1
#> 2 1 -6.20 -3.90 0.8872467 -0.8139064 -5.31275326 -4.713906 2
#> 3 1 -14.20 -5.80 0.2457654 3.8831192 -13.95423462 -1.916881 2
#> 4 1 -2.10 -13.20 0.5387143 -0.6082700 -1.56128573 -13.808270 1
#> 5 1 -1.70 -4.30 1.7145458 0.1519977 0.01454577 -4.148002 1
#> 6 1 -6.90 -1.55 1.4108770 2.1594590 -5.48912299 0.609459 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4640 -37650 8350
#> initial value 998.131940
#> iter 2 value 831.915655
#> iter 3 value 831.322872
#> iter 4 value 829.007503
#> iter 5 value 777.073827
#> iter 6 value 767.513507
#> iter 7 value 765.992270
#> iter 8 value 765.968363
#> iter 9 value 765.968157
#> iter 10 value 765.968071
#> iter 11 value 765.968041
#> iter 12 value 765.967793
#> iter 12 value 765.967793
#> iter 12 value 765.967793
#> final value 765.967793
#> converged
#> This is Run number 291
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.5183990 3.3941148 -0.8316010 -8.805885 1
#> 2 1 -6.20 -3.90 1.7693622 -0.2634645 -4.4306378 -4.163464 2
#> 3 1 -14.20 -5.80 0.9919890 1.4104441 -13.2080110 -4.389556 2
#> 4 1 -2.10 -13.20 0.9583359 -0.1757396 -1.1416641 -13.375740 1
#> 5 1 -1.70 -4.30 0.8438243 0.4805695 -0.8561757 -3.819431 1
#> 6 1 -6.90 -1.55 -0.7981524 -0.1423040 -7.6981524 -1.692304 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4300 -36425 7675
#> initial value 998.131940
#> iter 2 value 852.202529
#> iter 3 value 851.856167
#> iter 4 value 848.691770
#> iter 5 value 794.060865
#> iter 6 value 784.847043
#> iter 7 value 783.340460
#> iter 8 value 783.315455
#> iter 9 value 783.315274
#> iter 10 value 783.315110
#> iter 10 value 783.315106
#> iter 11 value 783.315049
#> iter 12 value 783.315023
#> iter 12 value 783.315023
#> iter 12 value 783.315020
#> final value 783.315020
#> converged
#> This is Run number 292
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.9108058 -0.8361003 -1.439194 -13.0361003 1
#> 2 1 -6.20 -3.90 0.5334250 3.1293773 -5.666575 -0.7706227 2
#> 3 1 -14.20 -5.80 0.3946201 0.3952252 -13.805380 -5.4047748 2
#> 4 1 -2.10 -13.20 1.0094266 0.9599540 -1.090573 -12.2400460 1
#> 5 1 -1.70 -4.30 -1.4228504 -0.6907350 -3.122850 -4.9907350 1
#> 6 1 -6.90 -1.55 1.6018892 0.1336855 -5.298111 -1.4163145 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4680 -37875 8100
#> initial value 998.131940
#> iter 2 value 830.377965
#> iter 3 value 829.011676
#> iter 4 value 826.294391
#> iter 5 value 775.752592
#> iter 6 value 766.087429
#> iter 7 value 764.587422
#> iter 8 value 764.562674
#> iter 9 value 764.562343
#> iter 10 value 764.562171
#> iter 11 value 764.562158
#> iter 12 value 764.562089
#> iter 12 value 764.562089
#> iter 12 value 764.562089
#> final value 764.562089
#> converged
#> This is Run number 293
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.7639582 -0.1482784 -0.58604182 -12.348278 1
#> 2 1 -6.20 -3.90 0.4799515 -0.2919752 -5.72004848 -4.191975 2
#> 3 1 -14.20 -5.80 0.2914612 0.1977963 -13.90853876 -5.602204 2
#> 4 1 -2.10 -13.20 -1.0652048 -1.0547899 -3.16520485 -14.254790 1
#> 5 1 -1.70 -4.30 1.7495964 0.2627416 0.04959638 -4.037258 1
#> 6 1 -6.90 -1.55 -0.6477456 -0.4431251 -7.54774561 -1.993125 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4560 -37250 8275
#> initial value 998.131940
#> iter 2 value 837.827435
#> iter 3 value 837.782543
#> iter 4 value 835.462991
#> iter 5 value 782.262045
#> iter 6 value 772.810511
#> iter 7 value 771.286098
#> iter 8 value 771.261869
#> iter 9 value 771.261554
#> iter 10 value 771.261405
#> iter 11 value 771.261369
#> iter 12 value 771.261304
#> iter 12 value 771.261304
#> iter 12 value 771.261304
#> final value 771.261304
#> converged
#> This is Run number 294
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.9051838 1.1136679 -1.44481619 -11.086332 1
#> 2 1 -6.20 -3.90 1.4965862 1.1429707 -4.70341381 -2.757029 2
#> 3 1 -14.20 -5.80 0.4268191 1.2854921 -13.77318088 -4.514508 2
#> 4 1 -2.10 -13.20 2.1503160 2.1706564 0.05031595 -11.029344 1
#> 5 1 -1.70 -4.30 -0.4598082 -0.3673346 -2.15980816 -4.667335 1
#> 6 1 -6.90 -1.55 -0.5028535 -0.9075608 -7.40285353 -2.457561 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3520 -36700 7925
#> initial value 998.131940
#> iter 2 value 846.264840
#> iter 3 value 841.158836
#> iter 4 value 834.835188
#> iter 5 value 780.699748
#> iter 6 value 771.377294
#> iter 7 value 769.746027
#> iter 8 value 769.722802
#> iter 9 value 769.722788
#> iter 10 value 769.722773
#> iter 11 value 769.722760
#> iter 11 value 769.722756
#> iter 11 value 769.722756
#> final value 769.722756
#> converged
#> This is Run number 295
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.4295164 -1.2492667 -1.9204836 -13.4492667 1
#> 2 1 -6.20 -3.90 -0.2737735 0.4702446 -6.4737735 -3.4297554 2
#> 3 1 -14.20 -5.80 0.2326485 1.2376123 -13.9673515 -4.5623877 2
#> 4 1 -2.10 -13.20 -0.3914729 -0.3132818 -2.4914729 -13.5132818 1
#> 5 1 -1.70 -4.30 1.1065599 1.7746163 -0.5934401 -2.5253837 1
#> 6 1 -6.90 -1.55 1.8180783 0.6678185 -5.0819217 -0.8821815 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4220 -36175 7850
#> initial value 998.131940
#> iter 2 value 854.306060
#> iter 3 value 840.157063
#> iter 4 value 838.168920
#> iter 5 value 794.557103
#> iter 6 value 786.608679
#> iter 7 value 785.167725
#> iter 8 value 785.114475
#> iter 9 value 785.113662
#> iter 10 value 785.113546
#> iter 11 value 785.113442
#> iter 12 value 785.113357
#> iter 12 value 785.113357
#> iter 12 value 785.113357
#> final value 785.113357
#> converged
#> This is Run number 296
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.59273926 1.1984392 -2.942739 -11.001561 1
#> 2 1 -6.20 -3.90 -1.10252295 -0.5383388 -7.302523 -4.438339 2
#> 3 1 -14.20 -5.80 1.37803237 -0.5917703 -12.821968 -6.391770 2
#> 4 1 -2.10 -13.20 1.02950651 2.0432735 -1.070493 -11.156727 1
#> 5 1 -1.70 -4.30 -0.04726241 -0.7571170 -1.747262 -5.057117 1
#> 6 1 -6.90 -1.55 -0.17304557 0.1609160 -7.073046 -1.389084 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4820 -38425 8675
#> initial value 998.131940
#> iter 2 value 818.889485
#> iter 3 value 817.502255
#> iter 4 value 815.532071
#> iter 5 value 765.720161
#> iter 6 value 756.040332
#> iter 7 value 754.520029
#> iter 8 value 754.497405
#> iter 9 value 754.497259
#> iter 10 value 754.496923
#> iter 10 value 754.496912
#> iter 11 value 754.496895
#> iter 12 value 754.496848
#> iter 12 value 754.496847
#> iter 12 value 754.496844
#> final value 754.496844
#> converged
#> This is Run number 297
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.68471348 2.4819638 -0.6652865 -9.718036 1
#> 2 1 -6.20 -3.90 2.90998068 0.7208266 -3.2900193 -3.179173 2
#> 3 1 -14.20 -5.80 -0.16923202 1.0174274 -14.3692320 -4.782573 2
#> 4 1 -2.10 -13.20 1.78052097 1.7064601 -0.3194790 -11.493540 1
#> 5 1 -1.70 -4.30 0.07083213 0.7869255 -1.6291679 -3.513075 1
#> 6 1 -6.90 -1.55 -0.84297679 -0.2954682 -7.7429768 -1.845468 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5000 -37625 6775
#> initial value 998.131940
#> iter 2 value 841.465561
#> iter 3 value 839.728272
#> iter 4 value 836.731161
#> iter 5 value 788.184670
#> iter 6 value 778.381874
#> iter 7 value 776.817147
#> iter 8 value 776.783873
#> iter 9 value 776.783797
#> iter 10 value 776.783602
#> iter 10 value 776.783602
#> iter 10 value 776.783593
#> final value 776.783593
#> converged
#> This is Run number 298
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 4.0013924 0.4182143 1.6513924 -11.781786 1
#> 2 1 -6.20 -3.90 0.2034261 0.1976834 -5.9965739 -3.702317 2
#> 3 1 -14.20 -5.80 1.3062459 1.8377576 -12.8937541 -3.962242 2
#> 4 1 -2.10 -13.20 1.4159723 -0.8537479 -0.6840277 -14.053748 1
#> 5 1 -1.70 -4.30 1.5674866 2.6702262 -0.1325134 -1.629774 1
#> 6 1 -6.90 -1.55 -1.1257103 0.1157941 -8.0257103 -1.434206 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5520 -37600 7350
#> initial value 998.131940
#> iter 2 value 838.705906
#> iter 3 value 827.680388
#> iter 4 value 827.246468
#> iter 5 value 787.869321
#> iter 6 value 779.290000
#> iter 7 value 777.714975
#> iter 8 value 777.655481
#> iter 9 value 777.654502
#> iter 10 value 777.654260
#> iter 11 value 777.653941
#> iter 12 value 777.653725
#> iter 12 value 777.653725
#> iter 12 value 777.653725
#> final value 777.653725
#> converged
#> This is Run number 299
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 3.17607263 0.5145536 0.8260726 -11.685446 1
#> 2 1 -6.20 -3.90 -0.46413623 -0.2448955 -6.6641362 -4.144895 2
#> 3 1 -14.20 -5.80 -0.08613995 -0.4313768 -14.2861399 -6.231377 2
#> 4 1 -2.10 -13.20 -1.43751753 0.5158982 -3.5375175 -12.684102 1
#> 5 1 -1.70 -4.30 0.71991091 -0.6474197 -0.9800891 -4.947420 1
#> 6 1 -6.90 -1.55 0.46826533 -0.7188650 -6.4317347 -2.268865 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4640 -36975 7425
#> initial value 998.131940
#> iter 2 value 846.647876
#> iter 3 value 845.987610
#> iter 4 value 843.184032
#> iter 5 value 790.998254
#> iter 6 value 781.518267
#> iter 7 value 780.010759
#> iter 8 value 779.982815
#> iter 9 value 779.982767
#> iter 10 value 779.982423
#> iter 10 value 779.982421
#> iter 11 value 779.982346
#> iter 12 value 779.982305
#> iter 12 value 779.982305
#> iter 12 value 779.982305
#> final value 779.982305
#> converged
#> This is Run number 300
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 3.2041872 4.37694707 0.85418722 -7.8230529 1
#> 2 1 -6.20 -3.90 -0.9989656 0.52276188 -7.19896563 -3.3772381 2
#> 3 1 -14.20 -5.80 -0.6259492 2.79923813 -14.82594916 -3.0007619 2
#> 4 1 -2.10 -13.20 2.1317373 1.53935905 0.03173725 -11.6606410 1
#> 5 1 -1.70 -4.30 0.5154185 -0.06102731 -1.18458149 -4.3610273 1
#> 6 1 -6.90 -1.55 -0.2699454 1.08084548 -7.16994545 -0.4691545 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3640 -35000 8450
#> initial value 998.131940
#> iter 2 value 864.397662
#> iter 3 value 847.910885
#> iter 4 value 845.971355
#> iter 5 value 800.578023
#> iter 6 value 793.258759
#> iter 7 value 792.147823
#> iter 8 value 792.110889
#> iter 9 value 792.110352
#> iter 10 value 792.110253
#> iter 11 value 792.110165
#> iter 12 value 792.110097
#> iter 12 value 792.110097
#> iter 12 value 792.110097
#> final value 792.110097
#> converged
#> This is Run number 301
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.6548712 1.24264138 -3.0048712 -10.9573586 1
#> 2 1 -6.20 -3.90 -1.0764745 -1.32470416 -7.2764745 -5.2247042 2
#> 3 1 -14.20 -5.80 -0.6306849 3.17406028 -14.8306849 -2.6259397 2
#> 4 1 -2.10 -13.20 2.4676385 0.09798356 0.3676385 -13.1020164 1
#> 5 1 -1.70 -4.30 -0.1496658 -0.38435055 -1.8496658 -4.6843505 1
#> 6 1 -6.90 -1.55 -0.7057597 0.69490975 -7.6057597 -0.8550903 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4960 -36650 7850
#> initial value 998.131940
#> iter 2 value 848.552623
#> iter 3 value 835.666641
#> iter 4 value 835.074017
#> iter 5 value 793.784410
#> iter 6 value 785.629458
#> iter 7 value 784.306694
#> iter 8 value 784.261544
#> iter 9 value 784.260816
#> iter 10 value 784.260609
#> iter 11 value 784.260344
#> iter 12 value 784.260176
#> iter 12 value 784.260176
#> iter 12 value 784.260176
#> final value 784.260176
#> converged
#> This is Run number 302
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.9264650 3.1837717 -3.2764650 -9.0162283 1
#> 2 1 -6.20 -3.90 -0.4092675 5.3824587 -6.6092675 1.4824587 2
#> 3 1 -14.20 -5.80 -0.5772868 0.3220420 -14.7772868 -5.4779580 2
#> 4 1 -2.10 -13.20 1.1960403 2.6356212 -0.9039597 -10.5643788 1
#> 5 1 -1.70 -4.30 -0.4248092 -0.8906867 -2.1248092 -5.1906867 1
#> 6 1 -6.90 -1.55 -0.6573954 0.6557251 -7.5573954 -0.8942749 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5120 -36075 7550
#> initial value 998.131940
#> iter 2 value 857.686827
#> iter 3 value 846.053732
#> iter 4 value 845.725383
#> iter 5 value 803.382790
#> iter 6 value 795.408410
#> iter 7 value 793.994501
#> iter 8 value 793.952942
#> iter 9 value 793.952391
#> iter 10 value 793.952205
#> iter 11 value 793.951947
#> iter 12 value 793.951803
#> iter 12 value 793.951803
#> iter 12 value 793.951803
#> final value 793.951803
#> converged
#> This is Run number 303
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.1667076 0.1674771 -2.5167076 -12.032523 1
#> 2 1 -6.20 -3.90 5.2374982 -0.4239506 -0.9625018 -4.323951 1
#> 3 1 -14.20 -5.80 1.9609503 0.7052026 -12.2390497 -5.094797 2
#> 4 1 -2.10 -13.20 0.3902715 -0.4051488 -1.7097285 -13.605149 1
#> 5 1 -1.70 -4.30 -0.8128941 -0.8302226 -2.5128941 -5.130223 1
#> 6 1 -6.90 -1.55 -1.2850345 -0.4009554 -8.1850345 -1.950955 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4380 -37375 8625
#> initial value 998.131940
#> iter 2 value 833.751169
#> iter 3 value 833.276616
#> iter 4 value 830.589115
#> iter 5 value 777.030374
#> iter 6 value 767.631014
#> iter 7 value 766.073880
#> iter 8 value 766.051354
#> iter 9 value 766.051265
#> iter 10 value 766.050983
#> iter 10 value 766.050983
#> iter 10 value 766.050978
#> final value 766.050978
#> converged
#> This is Run number 304
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.0042049 2.3747960810 -1.3457951 -9.825204 1
#> 2 1 -6.20 -3.90 -0.5220648 0.0003921122 -6.7220648 -3.899608 2
#> 3 1 -14.20 -5.80 1.2936594 0.4218276709 -12.9063406 -5.378172 2
#> 4 1 -2.10 -13.20 1.3552346 -0.6179463404 -0.7447654 -13.817946 1
#> 5 1 -1.70 -4.30 0.2924639 1.1868164207 -1.4075361 -3.113184 1
#> 6 1 -6.90 -1.55 0.7778591 2.4600049840 -6.1221409 0.910005 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4300 -36675 7050
#> initial value 998.131940
#> iter 2 value 852.430042
#> iter 3 value 849.899982
#> iter 4 value 845.801168
#> iter 5 value 793.461167
#> iter 6 value 784.051740
#> iter 7 value 782.496838
#> iter 8 value 782.469440
#> iter 9 value 782.469411
#> iter 10 value 782.469314
#> iter 10 value 782.469312
#> iter 10 value 782.469304
#> final value 782.469304
#> converged
#> This is Run number 305
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.653725098 2.3702289 -1.6962749 -9.8297711 1
#> 2 1 -6.20 -3.90 0.008802253 -0.4399920 -6.1911977 -4.3399920 2
#> 3 1 -14.20 -5.80 -0.459302853 0.3373149 -14.6593029 -5.4626851 2
#> 4 1 -2.10 -13.20 2.752489946 0.9533446 0.6524899 -12.2466554 1
#> 5 1 -1.70 -4.30 0.122392938 -0.1975007 -1.5776071 -4.4975007 1
#> 6 1 -6.90 -1.55 -0.907752474 0.8612266 -7.8077525 -0.6887734 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4860 -37375 7575
#> initial value 998.131940
#> iter 2 value 840.498227
#> iter 3 value 840.136265
#> iter 4 value 837.902869
#> iter 5 value 786.728914
#> iter 6 value 777.101847
#> iter 7 value 775.601976
#> iter 8 value 775.573123
#> iter 9 value 775.572962
#> iter 10 value 775.572637
#> iter 11 value 775.572619
#> iter 12 value 775.572434
#> iter 12 value 775.572434
#> iter 12 value 775.572434
#> final value 775.572434
#> converged
#> This is Run number 306
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.7089390 -0.4804931 -1.641061 -12.680493 1
#> 2 1 -6.20 -3.90 0.2047491 -0.5115602 -5.995251 -4.411560 2
#> 3 1 -14.20 -5.80 -0.7900830 1.4032401 -14.990083 -4.396760 2
#> 4 1 -2.10 -13.20 -1.1234467 -0.7413298 -3.223447 -13.941330 1
#> 5 1 -1.70 -4.30 -1.3522570 -0.1221246 -3.052257 -4.422125 1
#> 6 1 -6.90 -1.55 -0.7059682 0.3211663 -7.605968 -1.228834 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4700 -38050 8375
#> initial value 998.131940
#> iter 2 value 826.182074
#> iter 3 value 824.883430
#> iter 4 value 822.435006
#> iter 5 value 771.908162
#> iter 6 value 762.253385
#> iter 7 value 760.741787
#> iter 8 value 760.718140
#> iter 9 value 760.718081
#> iter 10 value 760.717729
#> iter 11 value 760.717712
#> iter 12 value 760.717566
#> iter 12 value 760.717566
#> iter 12 value 760.717566
#> final value 760.717566
#> converged
#> This is Run number 307
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.901778407 0.09895562 -0.4482216 -12.1010444 1
#> 2 1 -6.20 -3.90 -0.001077749 -0.40236546 -6.2010777 -4.3023655 2
#> 3 1 -14.20 -5.80 0.505634123 2.56736028 -13.6943659 -3.2326397 2
#> 4 1 -2.10 -13.20 0.689974753 -0.71577106 -1.4100252 -13.9157711 1
#> 5 1 -1.70 -4.30 0.543589091 1.31136939 -1.1564109 -2.9886306 1
#> 6 1 -6.90 -1.55 0.713582030 1.30770050 -6.1864180 -0.2422995 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4260 -35875 7525
#> initial value 998.131940
#> iter 2 value 860.004124
#> iter 3 value 846.899509
#> iter 4 value 844.910897
#> iter 5 value 800.465998
#> iter 6 value 792.576621
#> iter 7 value 790.995451
#> iter 8 value 790.939357
#> iter 9 value 790.938560
#> iter 10 value 790.938452
#> iter 11 value 790.938346
#> iter 12 value 790.938264
#> iter 12 value 790.938264
#> iter 12 value 790.938264
#> final value 790.938264
#> converged
#> This is Run number 308
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.9344972 -1.1192275 0.5844972 -13.3192275 1
#> 2 1 -6.20 -3.90 2.9104090 -0.6989136 -3.2895910 -4.5989136 1
#> 3 1 -14.20 -5.80 1.4654858 -0.6720275 -12.7345142 -6.4720275 2
#> 4 1 -2.10 -13.20 -0.2923446 2.3453517 -2.3923446 -10.8546483 1
#> 5 1 -1.70 -4.30 1.5823179 0.6622847 -0.1176821 -3.6377153 1
#> 6 1 -6.90 -1.55 -0.2996365 2.2739896 -7.1996365 0.7239896 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3640 -36300 8700
#> initial value 998.131940
#> iter 2 value 846.742812
#> iter 3 value 846.019410
#> iter 4 value 841.522937
#> iter 5 value 783.974326
#> iter 6 value 774.996179
#> iter 7 value 773.366339
#> iter 8 value 773.344973
#> iter 9 value 773.344933
#> iter 10 value 773.344828
#> iter 10 value 773.344824
#> iter 10 value 773.344824
#> final value 773.344824
#> converged
#> This is Run number 309
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.3247173 -0.16808165 -2.674717 -12.3680816 1
#> 2 1 -6.20 -3.90 2.1906308 2.30084426 -4.009369 -1.5991557 2
#> 3 1 -14.20 -5.80 0.4152565 1.09940367 -13.784743 -4.7005963 2
#> 4 1 -2.10 -13.20 0.1461934 -0.26554970 -1.953807 -13.4655497 1
#> 5 1 -1.70 -4.30 3.3215904 0.06642265 1.621590 -4.2335774 1
#> 6 1 -6.90 -1.55 -0.7346083 2.35992606 -7.634608 0.8099261 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4320 -36975 8000
#> initial value 998.131940
#> iter 2 value 843.075245
#> iter 3 value 842.160022
#> iter 4 value 838.858853
#> iter 5 value 785.378283
#> iter 6 value 776.004697
#> iter 7 value 774.484027
#> iter 8 value 774.459899
#> iter 9 value 774.459608
#> iter 10 value 774.459589
#> iter 10 value 774.459589
#> iter 11 value 774.459499
#> iter 11 value 774.459494
#> iter 12 value 774.459472
#> iter 13 value 774.459458
#> iter 13 value 774.459454
#> iter 13 value 774.459453
#> final value 774.459453
#> converged
#> This is Run number 310
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.88175246 0.9683461 -1.468248 -11.231654 1
#> 2 1 -6.20 -3.90 -0.27392876 -0.2618681 -6.473929 -4.161868 2
#> 3 1 -14.20 -5.80 2.26619443 2.0357307 -11.933806 -3.764269 2
#> 4 1 -2.10 -13.20 0.06266407 0.2961921 -2.037336 -12.903808 1
#> 5 1 -1.70 -4.30 -1.22152226 -1.3867326 -2.921522 -5.686733 1
#> 6 1 -6.90 -1.55 0.33576562 -0.4395642 -6.564234 -1.989564 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4220 -36500 7675
#> initial value 998.131940
#> iter 2 value 851.169244
#> iter 3 value 850.243708
#> iter 4 value 846.697682
#> iter 5 value 792.339300
#> iter 6 value 783.098005
#> iter 7 value 781.583572
#> iter 8 value 781.559051
#> iter 9 value 781.558864
#> iter 10 value 781.558726
#> iter 10 value 781.558725
#> iter 11 value 781.558709
#> iter 12 value 781.558687
#> iter 12 value 781.558687
#> iter 12 value 781.558683
#> final value 781.558683
#> converged
#> This is Run number 311
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.5115168 1.01466716 -2.8615168 -11.185333 1
#> 2 1 -6.20 -3.90 1.4032247 -0.02184841 -4.7967753 -3.921848 2
#> 3 1 -14.20 -5.80 1.4153494 0.70786851 -12.7846506 -5.092131 2
#> 4 1 -2.10 -13.20 1.2694801 -0.23517476 -0.8305199 -13.435175 1
#> 5 1 -1.70 -4.30 0.1734830 -0.80645870 -1.5265170 -5.106459 1
#> 6 1 -6.90 -1.55 1.3592699 -0.33755845 -5.5407301 -1.887558 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4100 -37575 9200
#> initial value 998.131940
#> iter 2 value 826.838089
#> iter 3 value 825.612424
#> iter 4 value 822.287150
#> iter 5 value 768.149284
#> iter 6 value 758.854834
#> iter 7 value 757.221658
#> iter 8 value 757.198380
#> iter 9 value 757.198271
#> iter 10 value 757.198177
#> iter 10 value 757.198174
#> iter 11 value 757.198151
#> iter 11 value 757.198148
#> iter 11 value 757.198148
#> final value 757.198148
#> converged
#> This is Run number 312
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.86240171 -1.05561952 -1.487598 -13.255620 1
#> 2 1 -6.20 -3.90 -0.02422799 -2.02723568 -6.224228 -5.927236 2
#> 3 1 -14.20 -5.80 -0.82718011 0.03059423 -15.027180 -5.769406 2
#> 4 1 -2.10 -13.20 -0.90873204 1.76298622 -3.008732 -11.437014 1
#> 5 1 -1.70 -4.30 0.29620949 -1.07418756 -1.403791 -5.374188 1
#> 6 1 -6.90 -1.55 -0.59807415 0.08578685 -7.498074 -1.464213 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4760 -36500 7475
#> initial value 998.131940
#> iter 2 value 852.642265
#> iter 3 value 840.405177
#> iter 4 value 839.136562
#> iter 5 value 796.720395
#> iter 6 value 788.595890
#> iter 7 value 787.008343
#> iter 8 value 786.950927
#> iter 9 value 786.950025
#> iter 10 value 786.949851
#> iter 11 value 786.949644
#> iter 12 value 786.949506
#> iter 12 value 786.949506
#> iter 12 value 786.949506
#> final value 786.949506
#> converged
#> This is Run number 313
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.7592132 0.2398957 -0.5907868 -11.9601043 1
#> 2 1 -6.20 -3.90 -0.1566979 2.8151215 -6.3566979 -1.0848785 2
#> 3 1 -14.20 -5.80 -1.2836421 2.3738340 -15.4836421 -3.4261660 2
#> 4 1 -2.10 -13.20 1.8257272 0.6838008 -0.2742728 -12.5161992 1
#> 5 1 -1.70 -4.30 1.0214538 0.9536818 -0.6785462 -3.3463182 1
#> 6 1 -6.90 -1.55 1.5216595 0.8943069 -5.3783405 -0.6556931 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4600 -36800 8375
#> initial value 998.131940
#> iter 2 value 843.213546
#> iter 3 value 828.160033
#> iter 4 value 827.237153
#> iter 5 value 786.231194
#> iter 6 value 778.166996
#> iter 7 value 777.037946
#> iter 8 value 776.995233
#> iter 9 value 776.994470
#> iter 10 value 776.994283
#> iter 11 value 776.994059
#> iter 12 value 776.993902
#> iter 12 value 776.993902
#> iter 12 value 776.993902
#> final value 776.993902
#> converged
#> This is Run number 314
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.1172372 1.0969271 -0.2327628 -11.103073 1
#> 2 1 -6.20 -3.90 1.3721152 -0.3896656 -4.8278848 -4.289666 2
#> 3 1 -14.20 -5.80 -0.4654766 1.4130257 -14.6654766 -4.386974 2
#> 4 1 -2.10 -13.20 0.5688162 3.1277928 -1.5311838 -10.072207 1
#> 5 1 -1.70 -4.30 0.8178297 0.9096365 -0.8821703 -3.390364 1
#> 6 1 -6.90 -1.55 -0.5245573 0.1184695 -7.4245573 -1.431530 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5660 -40050 8175
#> initial value 998.131940
#> iter 2 value 797.598416
#> iter 3 value 795.099750
#> iter 4 value 793.956358
#> iter 5 value 751.141798
#> iter 6 value 741.084295
#> iter 7 value 739.685807
#> iter 8 value 739.662264
#> iter 9 value 739.662045
#> iter 10 value 739.661431
#> iter 10 value 739.661428
#> iter 11 value 739.661387
#> iter 12 value 739.661322
#> iter 12 value 739.661320
#> iter 12 value 739.661315
#> final value 739.661315
#> converged
#> This is Run number 315
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.55331554 1.12979439 -1.796684 -11.070206 1
#> 2 1 -6.20 -3.90 0.03046934 -0.37953366 -6.169531 -4.279534 2
#> 3 1 -14.20 -5.80 -0.51309325 -0.21348054 -14.713093 -6.013481 2
#> 4 1 -2.10 -13.20 0.04538563 2.04640570 -2.054614 -11.153594 1
#> 5 1 -1.70 -4.30 1.43831604 -0.08514234 -0.261684 -4.385142 1
#> 6 1 -6.90 -1.55 0.34680765 4.30073224 -6.553192 2.750732 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4760 -37750 7300
#> initial value 998.131940
#> iter 2 value 836.857418
#> iter 3 value 834.746274
#> iter 4 value 831.385825
#> iter 5 value 782.189866
#> iter 6 value 772.413625
#> iter 7 value 770.908600
#> iter 8 value 770.880233
#> iter 9 value 770.880098
#> iter 10 value 770.879941
#> iter 10 value 770.879940
#> iter 11 value 770.879905
#> iter 12 value 770.879876
#> iter 12 value 770.879869
#> iter 13 value 770.879850
#> iter 13 value 770.879845
#> iter 13 value 770.879842
#> final value 770.879842
#> converged
#> This is Run number 316
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.5721992 0.3732792 -1.7778008 -11.82672077 1
#> 2 1 -6.20 -3.90 -0.1047494 1.7517530 -6.3047494 -2.14824697 2
#> 3 1 -14.20 -5.80 -1.0866493 0.2175876 -15.2866493 -5.58241240 2
#> 4 1 -2.10 -13.20 1.2614286 0.4812106 -0.8385714 -12.71878941 1
#> 5 1 -1.70 -4.30 1.0044305 -0.2453219 -0.6955695 -4.54532190 1
#> 6 1 -6.90 -1.55 0.7260323 1.5246171 -6.1739677 -0.02538287 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4240 -37300 8125
#> initial value 998.131940
#> iter 2 value 837.871547
#> iter 3 value 835.966190
#> iter 4 value 832.112192
#> iter 5 value 779.560196
#> iter 6 value 770.110951
#> iter 7 value 768.576761
#> iter 8 value 768.553348
#> iter 9 value 768.553164
#> iter 10 value 768.553030
#> iter 10 value 768.553028
#> iter 11 value 768.553011
#> iter 12 value 768.552986
#> iter 12 value 768.552986
#> iter 12 value 768.552982
#> final value 768.552982
#> converged
#> This is Run number 317
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.4478006 3.1808658 -2.79780058 -9.0191342 1
#> 2 1 -6.20 -3.90 2.2949664 0.4951635 -3.90503358 -3.4048365 2
#> 3 1 -14.20 -5.80 0.2486314 0.7670397 -13.95136864 -5.0329603 2
#> 4 1 -2.10 -13.20 -0.6153921 0.7114197 -2.71539210 -12.4885803 1
#> 5 1 -1.70 -4.30 1.7314400 0.9209594 0.03143998 -3.3790406 1
#> 6 1 -6.90 -1.55 -0.3130512 2.3024198 -7.21305115 0.7524198 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3880 -36300 8975
#> initial value 998.131940
#> iter 2 value 845.168703
#> iter 3 value 827.040174
#> iter 4 value 825.298189
#> iter 5 value 782.867729
#> iter 6 value 775.243068
#> iter 7 value 774.265868
#> iter 8 value 774.226072
#> iter 9 value 774.225398
#> iter 10 value 774.225281
#> iter 11 value 774.225163
#> iter 12 value 774.225065
#> iter 12 value 774.225065
#> iter 12 value 774.225065
#> final value 774.225065
#> converged
#> This is Run number 318
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.9323958 2.51118641 -1.4176042 -9.688814 1
#> 2 1 -6.20 -3.90 -1.2005330 -0.61890519 -7.4005330 -4.518905 2
#> 3 1 -14.20 -5.80 0.5319558 1.31141382 -13.6680442 -4.488586 2
#> 4 1 -2.10 -13.20 1.6089105 0.32633153 -0.4910895 -12.873668 1
#> 5 1 -1.70 -4.30 7.7895046 0.01939296 6.0895046 -4.280607 1
#> 6 1 -6.90 -1.55 0.3955878 -0.12401757 -6.5044122 -1.674018 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4700 -39275 8800
#> initial value 998.131940
#> iter 2 value 805.412265
#> iter 3 value 801.500621
#> iter 4 value 798.333878
#> iter 5 value 751.574293
#> iter 6 value 741.902113
#> iter 7 value 740.392357
#> iter 8 value 740.368512
#> iter 9 value 740.368303
#> iter 10 value 740.368096
#> iter 11 value 740.368084
#> iter 12 value 740.367998
#> iter 12 value 740.367998
#> iter 12 value 740.367998
#> final value 740.367998
#> converged
#> This is Run number 319
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.1483996 2.7242116 -2.2016004 -9.475788 1
#> 2 1 -6.20 -3.90 0.6161207 -0.6295322 -5.5838793 -4.529532 2
#> 3 1 -14.20 -5.80 1.1854530 0.1924272 -13.0145470 -5.607573 2
#> 4 1 -2.10 -13.20 1.5377837 -1.0678251 -0.5622163 -14.267825 1
#> 5 1 -1.70 -4.30 2.1805874 -0.6046297 0.4805874 -4.904630 1
#> 6 1 -6.90 -1.55 5.4894229 -0.5782948 -1.4105771 -2.128295 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4460 -38000 7900
#> initial value 998.131940
#> iter 2 value 829.715322
#> iter 3 value 826.636405
#> iter 4 value 822.547752
#> iter 5 value 773.057331
#> iter 6 value 763.347167
#> iter 7 value 761.842900
#> iter 8 value 761.818507
#> iter 9 value 761.818331
#> iter 10 value 761.818198
#> iter 10 value 761.818197
#> iter 11 value 761.818172
#> iter 12 value 761.818146
#> iter 12 value 761.818146
#> iter 12 value 761.818140
#> final value 761.818140
#> converged
#> This is Run number 320
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.3753233 0.5570453 -3.725323 -11.642955 1
#> 2 1 -6.20 -3.90 -0.2309047 -0.3836692 -6.430905 -4.283669 2
#> 3 1 -14.20 -5.80 -1.4438177 2.6131486 -15.643818 -3.186851 2
#> 4 1 -2.10 -13.20 -1.2698387 0.5359663 -3.369839 -12.664034 1
#> 5 1 -1.70 -4.30 -1.0831741 1.9307131 -2.783174 -2.369287 2
#> 6 1 -6.90 -1.55 -0.5103080 0.3051091 -7.410308 -1.244891 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3940 -36850 8925
#> initial value 998.131940
#> iter 2 value 838.407718
#> iter 3 value 838.085741
#> iter 4 value 834.525346
#> iter 5 value 778.342303
#> iter 6 value 769.199156
#> iter 7 value 767.577129
#> iter 8 value 767.555248
#> iter 9 value 767.555182
#> iter 10 value 767.555047
#> iter 10 value 767.555044
#> iter 10 value 767.555044
#> final value 767.555044
#> converged
#> This is Run number 321
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.11453203 0.96558626 -2.464532 -11.2344137 1
#> 2 1 -6.20 -3.90 0.82490040 0.15541478 -5.375100 -3.7445852 2
#> 3 1 -14.20 -5.80 0.88302611 -0.74534385 -13.316974 -6.5453438 2
#> 4 1 -2.10 -13.20 0.02788239 0.08834827 -2.072118 -13.1116517 1
#> 5 1 -1.70 -4.30 -0.84519287 1.30536320 -2.545193 -2.9946368 1
#> 6 1 -6.90 -1.55 0.99627741 1.10580163 -5.903723 -0.4441984 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4360 -36850 8950
#> initial value 998.131940
#> iter 2 value 838.589855
#> iter 3 value 821.331773
#> iter 4 value 820.401747
#> iter 5 value 779.817517
#> iter 6 value 771.962535
#> iter 7 value 771.038786
#> iter 8 value 771.001125
#> iter 9 value 771.000462
#> iter 10 value 771.000386
#> iter 11 value 771.000152
#> iter 12 value 770.999904
#> iter 12 value 770.999904
#> iter 12 value 770.999904
#> final value 770.999904
#> converged
#> This is Run number 322
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.18015067 2.0662150 -0.1698493 -10.1337850 1
#> 2 1 -6.20 -3.90 -0.39262975 2.2688184 -6.5926297 -1.6311816 2
#> 3 1 -14.20 -5.80 -0.04268038 0.7477699 -14.2426804 -5.0522301 2
#> 4 1 -2.10 -13.20 0.53469112 -0.5808446 -1.5653089 -13.7808446 1
#> 5 1 -1.70 -4.30 0.05862777 -0.1481890 -1.6413722 -4.4481890 1
#> 6 1 -6.90 -1.55 1.28109123 1.9930085 -5.6189088 0.4430085 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4820 -37325 7625
#> initial value 998.131940
#> iter 2 value 840.875189
#> iter 3 value 840.551730
#> iter 4 value 838.288155
#> iter 5 value 786.831462
#> iter 6 value 777.231786
#> iter 7 value 775.731902
#> iter 8 value 775.703496
#> iter 9 value 775.703295
#> iter 10 value 775.703052
#> iter 11 value 775.703033
#> iter 12 value 775.702816
#> iter 12 value 775.702816
#> iter 12 value 775.702816
#> final value 775.702816
#> converged
#> This is Run number 323
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.3665956 0.2825180 -0.9834044 -11.917482 1
#> 2 1 -6.20 -3.90 0.6127612 1.7341686 -5.5872388 -2.165831 2
#> 3 1 -14.20 -5.80 -0.1519671 -1.0007078 -14.3519671 -6.800708 2
#> 4 1 -2.10 -13.20 1.6936856 -0.7148602 -0.4063144 -13.914860 1
#> 5 1 -1.70 -4.30 1.0584579 0.6408457 -0.6415421 -3.659154 1
#> 6 1 -6.90 -1.55 0.1770637 -0.2576885 -6.7229363 -1.807689 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4640 -37700 7575
#> initial value 998.131940
#> iter 2 value 835.941052
#> iter 3 value 833.896210
#> iter 4 value 830.487093
#> iter 5 value 780.531764
#> iter 6 value 770.824538
#> iter 7 value 769.326654
#> iter 8 value 769.300087
#> iter 9 value 769.299826
#> iter 10 value 769.299692
#> iter 10 value 769.299692
#> iter 11 value 769.299665
#> iter 12 value 769.299645
#> iter 12 value 769.299645
#> iter 12 value 769.299642
#> final value 769.299642
#> converged
#> This is Run number 324
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.6095498 0.1545595 -3.9595498 -12.0454405 1
#> 2 1 -6.20 -3.90 -0.7948233 1.1377169 -6.9948233 -2.7622831 2
#> 3 1 -14.20 -5.80 0.9254243 0.7005910 -13.2745757 -5.0994090 2
#> 4 1 -2.10 -13.20 1.0183122 0.4738937 -1.0816878 -12.7261063 1
#> 5 1 -1.70 -4.30 1.0551136 -0.7145184 -0.6448864 -5.0145184 1
#> 6 1 -6.90 -1.55 2.3550811 1.0743612 -4.5449189 -0.4756388 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5200 -38400 7625
#> initial value 998.131940
#> iter 2 value 825.904493
#> iter 3 value 824.745706
#> iter 4 value 822.804180
#> iter 5 value 775.092225
#> iter 6 value 765.135946
#> iter 7 value 763.668773
#> iter 8 value 763.639846
#> iter 9 value 763.639425
#> iter 10 value 763.639184
#> iter 11 value 763.639159
#> iter 12 value 763.639061
#> iter 12 value 763.639061
#> iter 12 value 763.639061
#> final value 763.639061
#> converged
#> This is Run number 325
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.08004823 1.646815 -2.430048 -10.553185 1
#> 2 1 -6.20 -3.90 -1.26647767 2.060776 -7.466478 -1.839224 2
#> 3 1 -14.20 -5.80 0.94376410 3.445090 -13.256236 -2.354910 2
#> 4 1 -2.10 -13.20 1.27575503 -0.747848 -0.824245 -13.947848 1
#> 5 1 -1.70 -4.30 -0.08238398 1.210774 -1.782384 -3.089226 1
#> 6 1 -6.90 -1.55 0.09634849 3.771762 -6.803652 2.221762 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4080 -37350 8600
#> initial value 998.131940
#> iter 2 value 834.011222
#> iter 3 value 832.157674
#> iter 4 value 828.183437
#> iter 5 value 774.727268
#> iter 6 value 765.374464
#> iter 7 value 763.792828
#> iter 8 value 763.770421
#> iter 9 value 763.770356
#> iter 10 value 763.770156
#> iter 10 value 763.770152
#> iter 10 value 763.770142
#> final value 763.770142
#> converged
#> This is Run number 326
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.1262641 1.1000863 -2.223736 -11.0999137 1
#> 2 1 -6.20 -3.90 2.8121822 -0.5656718 -3.387818 -4.4656718 1
#> 3 1 -14.20 -5.80 -0.7251008 -0.4584886 -14.925101 -6.2584886 2
#> 4 1 -2.10 -13.20 0.1328302 -0.9053522 -1.967170 -14.1053522 1
#> 5 1 -1.70 -4.30 0.4912990 1.1292724 -1.208701 -3.1707276 1
#> 6 1 -6.90 -1.55 1.1434885 1.8004913 -5.756512 0.2504913 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4280 -37275 8200
#> initial value 998.131940
#> iter 2 value 837.776414
#> iter 3 value 836.298390
#> iter 4 value 832.747698
#> iter 5 value 779.898242
#> iter 6 value 770.467350
#> iter 7 value 768.933266
#> iter 8 value 768.909911
#> iter 9 value 768.909715
#> iter 10 value 768.909568
#> iter 10 value 768.909563
#> iter 11 value 768.909540
#> iter 12 value 768.909514
#> iter 12 value 768.909514
#> iter 12 value 768.909508
#> final value 768.909508
#> converged
#> This is Run number 327
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.6824863 0.14567317 -1.667514 -12.0543268 1
#> 2 1 -6.20 -3.90 0.7475945 0.24836985 -5.452405 -3.6516302 2
#> 3 1 -14.20 -5.80 -0.6996589 1.06049502 -14.899659 -4.7395050 2
#> 4 1 -2.10 -13.20 -1.0510349 -0.03160367 -3.151035 -13.2316037 1
#> 5 1 -1.70 -4.30 4.3074774 -0.53683986 2.607477 -4.8368399 1
#> 6 1 -6.90 -1.55 -0.5976344 0.98816940 -7.497634 -0.5618306 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5100 -40050 9000
#> initial value 998.131940
#> iter 2 value 792.160040
#> iter 3 value 788.073753
#> iter 4 value 786.076290
#> iter 5 value 741.732576
#> iter 6 value 732.098497
#> iter 7 value 730.611237
#> iter 8 value 730.585748
#> iter 9 value 730.585382
#> iter 10 value 730.585185
#> iter 11 value 730.585090
#> iter 12 value 730.585057
#> iter 12 value 730.585057
#> iter 12 value 730.585057
#> final value 730.585057
#> converged
#> This is Run number 328
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.32937511 0.003805928 -2.020625 -12.1961941 1
#> 2 1 -6.20 -3.90 -0.03687837 0.601762595 -6.236878 -3.2982374 2
#> 3 1 -14.20 -5.80 1.70521092 -1.014166795 -12.494789 -6.8141668 2
#> 4 1 -2.10 -13.20 -0.79496022 0.977414323 -2.894960 -12.2225857 1
#> 5 1 -1.70 -4.30 0.26777387 1.531307962 -1.432226 -2.7686920 1
#> 6 1 -6.90 -1.55 0.41951447 1.725749555 -6.480486 0.1757496 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3780 -35150 8575
#> initial value 998.131940
#> iter 2 value 861.971581
#> iter 3 value 845.379050
#> iter 4 value 843.787778
#> iter 5 value 799.229883
#> iter 6 value 791.889621
#> iter 7 value 790.842214
#> iter 8 value 790.807692
#> iter 9 value 790.807162
#> iter 10 value 790.807042
#> iter 11 value 790.806921
#> iter 12 value 790.806837
#> iter 12 value 790.806837
#> iter 12 value 790.806837
#> final value 790.806837
#> converged
#> This is Run number 329
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.3236141 0.03215306 -1.026386 -12.167847 1
#> 2 1 -6.20 -3.90 0.6260122 2.61415117 -5.573988 -1.285849 2
#> 3 1 -14.20 -5.80 -1.3390005 0.93032192 -15.539000 -4.869678 2
#> 4 1 -2.10 -13.20 -0.7630594 1.49770858 -2.863059 -11.702291 1
#> 5 1 -1.70 -4.30 2.3454360 1.08200492 0.645436 -3.217995 1
#> 6 1 -6.90 -1.55 -1.0245496 0.25987953 -7.924550 -1.290120 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4800 -38700 7800
#> initial value 998.131940
#> iter 2 value 820.418563
#> iter 3 value 817.149290
#> iter 4 value 813.544399
#> iter 5 value 766.727417
#> iter 6 value 756.808717
#> iter 7 value 755.349228
#> iter 8 value 755.324180
#> iter 9 value 755.323964
#> iter 10 value 755.323920
#> iter 10 value 755.323917
#> iter 11 value 755.323821
#> iter 12 value 755.323729
#> iter 12 value 755.323720
#> iter 12 value 755.323715
#> final value 755.323715
#> converged
#> This is Run number 330
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.0189692 -0.3721740 -0.3310308 -12.5721740 1
#> 2 1 -6.20 -3.90 0.4956781 4.4816717 -5.7043219 0.5816717 2
#> 3 1 -14.20 -5.80 0.4973945 2.6714371 -13.7026055 -3.1285629 2
#> 4 1 -2.10 -13.20 -1.8922248 0.7376183 -3.9922248 -12.4623817 1
#> 5 1 -1.70 -4.30 0.9183052 -1.3090862 -0.7816948 -5.6090862 1
#> 6 1 -6.90 -1.55 2.2704836 1.2340701 -4.6295164 -0.3159299 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4660 -36375 8025
#> initial value 998.131940
#> iter 2 value 850.962064
#> iter 3 value 837.172515
#> iter 4 value 836.287512
#> iter 5 value 794.285280
#> iter 6 value 786.286638
#> iter 7 value 785.019516
#> iter 8 value 784.975732
#> iter 9 value 784.975011
#> iter 10 value 784.974823
#> iter 11 value 784.974596
#> iter 12 value 784.974448
#> iter 12 value 784.974448
#> iter 12 value 784.974448
#> final value 784.974448
#> converged
#> This is Run number 331
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.9453089 1.7746221 -1.404691 -10.425378 1
#> 2 1 -6.20 -3.90 1.2556415 0.9431160 -4.944359 -2.956884 2
#> 3 1 -14.20 -5.80 3.4296126 3.0384339 -10.770387 -2.761566 2
#> 4 1 -2.10 -13.20 -1.5479551 0.3365692 -3.647955 -12.863431 1
#> 5 1 -1.70 -4.30 -0.2420292 -1.2409274 -1.942029 -5.540927 1
#> 6 1 -6.90 -1.55 -0.4752975 -0.5160674 -7.375298 -2.066067 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4420 -37350 9150
#> initial value 998.131940
#> iter 2 value 830.520661
#> iter 3 value 812.540472
#> iter 4 value 811.657374
#> iter 5 value 772.155317
#> iter 6 value 764.259078
#> iter 7 value 763.389165
#> iter 8 value 763.349504
#> iter 9 value 763.348839
#> iter 10 value 763.348606
#> iter 11 value 763.348331
#> iter 12 value 763.348220
#> iter 12 value 763.348220
#> iter 12 value 763.348220
#> final value 763.348220
#> converged
#> This is Run number 332
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.03339504 -0.1049376 -3.383395 -12.304938 1
#> 2 1 -6.20 -3.90 3.62585381 -0.6275640 -2.574146 -4.527564 1
#> 3 1 -14.20 -5.80 1.23429176 -0.1763396 -12.965708 -5.976340 2
#> 4 1 -2.10 -13.20 -0.15793238 0.1065355 -2.257932 -13.093465 1
#> 5 1 -1.70 -4.30 -0.03423124 1.3329344 -1.734231 -2.967066 1
#> 6 1 -6.90 -1.55 0.48816616 2.9540936 -6.411834 1.404094 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4280 -36525 7750
#> initial value 998.131940
#> iter 2 value 850.455631
#> iter 3 value 849.940365
#> iter 4 value 846.679557
#> iter 5 value 792.216104
#> iter 6 value 782.973325
#> iter 7 value 781.462733
#> iter 8 value 781.438048
#> iter 9 value 781.437828
#> iter 10 value 781.437669
#> iter 10 value 781.437665
#> iter 11 value 781.437648
#> iter 12 value 781.437623
#> iter 12 value 781.437623
#> iter 12 value 781.437618
#> final value 781.437618
#> converged
#> This is Run number 333
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.568098196 0.9504155 -1.7819018 -11.249584 1
#> 2 1 -6.20 -3.90 -0.007041905 1.8301929 -6.2070419 -2.069807 2
#> 3 1 -14.20 -5.80 0.233002634 4.1630888 -13.9669974 -1.636911 2
#> 4 1 -2.10 -13.20 1.460384231 1.8244712 -0.6396158 -11.375529 1
#> 5 1 -1.70 -4.30 1.358434785 0.8916840 -0.3415652 -3.408316 1
#> 6 1 -6.90 -1.55 -1.310040824 0.8948230 -8.2100408 -0.655177 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5200 -37825 8475
#> initial value 998.131940
#> iter 2 value 828.787138
#> iter 3 value 814.130654
#> iter 4 value 813.885419
#> iter 5 value 775.730796
#> iter 6 value 767.324172
#> iter 7 value 766.333111
#> iter 8 value 766.293342
#> iter 9 value 766.292636
#> iter 10 value 766.292565
#> iter 11 value 766.292199
#> iter 12 value 766.291805
#> iter 12 value 766.291805
#> iter 12 value 766.291805
#> final value 766.291805
#> converged
#> This is Run number 334
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.0258353 0.7171625 -1.3241647 -11.482838 1
#> 2 1 -6.20 -3.90 -1.2152341 1.6388323 -7.4152341 -2.261168 2
#> 3 1 -14.20 -5.80 0.6182004 -1.4916628 -13.5817996 -7.291663 2
#> 4 1 -2.10 -13.20 1.3316871 -0.5448819 -0.7683129 -13.744882 1
#> 5 1 -1.70 -4.30 3.0630830 2.2708661 1.3630830 -2.029134 1
#> 6 1 -6.90 -1.55 3.8530886 -1.5848449 -3.0469114 -3.134845 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4040 -37375 9100
#> initial value 998.131940
#> iter 2 value 830.233918
#> iter 3 value 829.148920
#> iter 4 value 825.650362
#> iter 5 value 771.012272
#> iter 6 value 761.751413
#> iter 7 value 760.120142
#> iter 8 value 760.097359
#> iter 9 value 760.097269
#> iter 10 value 760.097162
#> iter 10 value 760.097157
#> iter 11 value 760.097139
#> iter 11 value 760.097138
#> iter 11 value 760.097138
#> final value 760.097138
#> converged
#> This is Run number 335
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.3328294 4.2298384 -1.017171 -7.9701616 1
#> 2 1 -6.20 -3.90 0.1168348 1.3899381 -6.083165 -2.5100619 2
#> 3 1 -14.20 -5.80 0.4635420 0.9743641 -13.736458 -4.8256359 2
#> 4 1 -2.10 -13.20 0.1926337 -1.4799982 -1.907366 -14.6799982 1
#> 5 1 -1.70 -4.30 0.3569191 3.2783579 -1.343081 -1.0216421 2
#> 6 1 -6.90 -1.55 -0.9431867 0.7344258 -7.843187 -0.8155742 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3840 -37750 8650
#> initial value 998.131940
#> iter 2 value 827.901111
#> iter 3 value 823.548219
#> iter 4 value 817.914759
#> iter 5 value 766.129174
#> iter 6 value 756.706826
#> iter 7 value 755.083296
#> iter 8 value 755.059760
#> iter 9 value 755.059706
#> iter 10 value 755.059632
#> iter 10 value 755.059632
#> iter 11 value 755.059618
#> iter 11 value 755.059608
#> iter 11 value 755.059608
#> final value 755.059608
#> converged
#> This is Run number 336
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.05405272 -0.3121723 -2.404053 -12.512172 1
#> 2 1 -6.20 -3.90 -1.35406534 -0.4370171 -7.554065 -4.337017 2
#> 3 1 -14.20 -5.80 0.39407759 -0.4219773 -13.805922 -6.221977 2
#> 4 1 -2.10 -13.20 -0.41750973 3.4435164 -2.517510 -9.756484 1
#> 5 1 -1.70 -4.30 3.42920838 -0.5422797 1.729208 -4.842280 1
#> 6 1 -6.90 -1.55 1.20834702 -0.2204736 -5.691653 -1.770474 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5300 -39400 8100
#> initial value 998.131940
#> iter 2 value 808.210534
#> iter 3 value 805.820358
#> iter 4 value 803.945561
#> iter 5 value 758.885395
#> iter 6 value 748.876812
#> iter 7 value 747.450515
#> iter 8 value 747.426124
#> iter 8 value 747.426116
#> final value 747.426116
#> converged
#> This is Run number 337
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.3615146 0.465841127 0.01151455 -11.734159 1
#> 2 1 -6.20 -3.90 1.4266693 0.868963752 -4.77333073 -3.031036 2
#> 3 1 -14.20 -5.80 -0.1050037 -0.898553133 -14.30500368 -6.698553 2
#> 4 1 -2.10 -13.20 0.8394285 4.060986348 -1.26057151 -9.139014 1
#> 5 1 -1.70 -4.30 1.0660875 -0.005384643 -0.63391255 -4.305385 1
#> 6 1 -6.90 -1.55 0.8312409 -1.249616579 -6.06875905 -2.799617 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3940 -36100 8550
#> initial value 998.131940
#> iter 2 value 850.628266
#> iter 3 value 833.991148
#> iter 4 value 832.085029
#> iter 5 value 788.834745
#> iter 6 value 781.113573
#> iter 7 value 779.981581
#> iter 8 value 779.938385
#> iter 9 value 779.937675
#> iter 10 value 779.937557
#> iter 11 value 779.937456
#> iter 12 value 779.937369
#> iter 12 value 779.937369
#> iter 12 value 779.937369
#> final value 779.937369
#> converged
#> This is Run number 338
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.13481131 1.8549120 -2.4848113 -10.3450880 1
#> 2 1 -6.20 -3.90 -0.18783667 0.6275378 -6.3878367 -3.2724622 2
#> 3 1 -14.20 -5.80 0.08094756 0.9279929 -14.1190524 -4.8720071 2
#> 4 1 -2.10 -13.20 1.31875065 0.5862374 -0.7812493 -12.6137626 1
#> 5 1 -1.70 -4.30 1.01715741 -0.9772870 -0.6828426 -5.2772870 1
#> 6 1 -6.90 -1.55 0.14061554 0.9068241 -6.7593845 -0.6431759 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4420 -37450 8700
#> initial value 998.131940
#> iter 2 value 832.253048
#> iter 3 value 831.871384
#> iter 4 value 829.359243
#> iter 5 value 775.889588
#> iter 6 value 766.476079
#> iter 7 value 764.915595
#> iter 8 value 764.893199
#> iter 9 value 764.893103
#> iter 10 value 764.892827
#> iter 10 value 764.892825
#> iter 10 value 764.892824
#> final value 764.892824
#> converged
#> This is Run number 339
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.4806763 -0.3434773 -1.869324 -12.543477 1
#> 2 1 -6.20 -3.90 -0.7311430 1.3957551 -6.931143 -2.504245 2
#> 3 1 -14.20 -5.80 -0.3393032 0.5332388 -14.539303 -5.266761 2
#> 4 1 -2.10 -13.20 -1.5747877 4.1202421 -3.674788 -9.079758 1
#> 5 1 -1.70 -4.30 -1.8668259 0.7690169 -3.566826 -3.530983 2
#> 6 1 -6.90 -1.55 0.0567027 0.3727198 -6.843297 -1.177280 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4940 -37750 7375
#> initial value 998.131940
#> iter 2 value 836.501650
#> iter 3 value 835.328063
#> iter 4 value 832.756866
#> iter 5 value 783.329100
#> iter 6 value 773.548146
#> iter 7 value 772.051236
#> iter 8 value 772.021740
#> iter 9 value 772.021622
#> iter 10 value 772.021260
#> iter 10 value 772.021258
#> iter 11 value 772.021212
#> iter 12 value 772.021155
#> iter 12 value 772.021147
#> iter 12 value 772.021145
#> final value 772.021145
#> converged
#> This is Run number 340
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.8428087 -0.08063064 0.4928087 -12.2806306 1
#> 2 1 -6.20 -3.90 -0.3494448 0.45031491 -6.5494448 -3.4496851 2
#> 3 1 -14.20 -5.80 -0.7005161 -0.75202841 -14.9005161 -6.5520284 2
#> 4 1 -2.10 -13.20 1.2314487 0.23353287 -0.8685513 -12.9664671 1
#> 5 1 -1.70 -4.30 -0.3562897 -0.60162847 -2.0562897 -4.9016285 1
#> 6 1 -6.90 -1.55 0.7220403 0.93117733 -6.1779597 -0.6188227 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5420 -38350 6650
#> initial value 998.131940
#> iter 2 value 831.917922
#> iter 3 value 830.353555
#> iter 4 value 827.936134
#> iter 5 value 782.067862
#> iter 6 value 771.993065
#> iter 7 value 770.431270
#> iter 8 value 770.394641
#> iter 9 value 770.394533
#> iter 10 value 770.394282
#> iter 10 value 770.394281
#> iter 11 value 770.394269
#> iter 12 value 770.394232
#> iter 12 value 770.394232
#> iter 12 value 770.394230
#> final value 770.394230
#> converged
#> This is Run number 341
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.6648172 0.1902768 -3.0148172 -12.009723 1
#> 2 1 -6.20 -3.90 -0.7299907 2.5162544 -6.9299907 -1.383746 2
#> 3 1 -14.20 -5.80 1.9522680 1.7075664 -12.2477320 -4.092434 2
#> 4 1 -2.10 -13.20 2.2515854 -1.2463174 0.1515854 -14.446317 1
#> 5 1 -1.70 -4.30 0.4594931 -0.5560680 -1.2405069 -4.856068 1
#> 6 1 -6.90 -1.55 2.6000194 0.5341917 -4.2999806 -1.015808 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4940 -37825 8375
#> initial value 998.131940
#> iter 2 value 829.420865
#> iter 3 value 814.593036
#> iter 4 value 813.838305
#> iter 5 value 775.081647
#> iter 6 value 766.682842
#> iter 7 value 765.571508
#> iter 8 value 765.523262
#> iter 9 value 765.522337
#> iter 10 value 765.522292
#> iter 11 value 765.522025
#> iter 12 value 765.521669
#> iter 12 value 765.521669
#> iter 12 value 765.521669
#> final value 765.521669
#> converged
#> This is Run number 342
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.6243097 0.1174706 -2.974310 -12.0825294 1
#> 2 1 -6.20 -3.90 1.4999443 -0.8013762 -4.700056 -4.7013762 1
#> 3 1 -14.20 -5.80 -0.8400997 -0.4029012 -15.040100 -6.2029012 2
#> 4 1 -2.10 -13.20 -0.9653595 1.1948907 -3.065360 -12.0051093 1
#> 5 1 -1.70 -4.30 0.5619034 0.8299371 -1.138097 -3.4700629 1
#> 6 1 -6.90 -1.55 0.3607815 1.9144086 -6.539218 0.3644086 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4660 -38200 7575
#> initial value 998.131940
#> iter 2 value 828.911659
#> iter 3 value 825.761727
#> iter 4 value 821.824442
#> iter 5 value 773.714562
#> iter 6 value 763.866047
#> iter 7 value 762.379185
#> iter 8 value 762.353146
#> iter 9 value 762.352912
#> iter 10 value 762.352890
#> iter 10 value 762.352888
#> iter 11 value 762.352868
#> iter 12 value 762.352795
#> iter 12 value 762.352790
#> iter 12 value 762.352780
#> final value 762.352780
#> converged
#> This is Run number 343
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.4892242 0.5897127 -1.860776 -11.610287 1
#> 2 1 -6.20 -3.90 0.9877185 1.1073731 -5.212281 -2.792627 2
#> 3 1 -14.20 -5.80 -0.8685674 2.8156903 -15.068567 -2.984310 2
#> 4 1 -2.10 -13.20 -0.5260037 -0.6761472 -2.626004 -13.876147 1
#> 5 1 -1.70 -4.30 -0.3720512 1.7510678 -2.072051 -2.548932 1
#> 6 1 -6.90 -1.55 0.1896357 -1.3148288 -6.710364 -2.864829 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5020 -37675 7525
#> initial value 998.131940
#> iter 2 value 836.707100
#> iter 3 value 836.234282
#> iter 4 value 834.209621
#> iter 5 value 784.175921
#> iter 6 value 774.426170
#> iter 7 value 772.930076
#> iter 8 value 772.900182
#> iter 9 value 772.900034
#> iter 10 value 772.899653
#> iter 11 value 772.899629
#> iter 12 value 772.899439
#> iter 12 value 772.899439
#> iter 12 value 772.899439
#> final value 772.899439
#> converged
#> This is Run number 344
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.09388583 1.968030160 -2.256114 -10.231970 1
#> 2 1 -6.20 -3.90 4.29283488 -0.161408392 -1.907165 -4.061408 1
#> 3 1 -14.20 -5.80 0.02505046 0.008504598 -14.174950 -5.791495 2
#> 4 1 -2.10 -13.20 0.44894600 0.639437085 -1.651054 -12.560563 1
#> 5 1 -1.70 -4.30 -0.85119844 -0.107543965 -2.551198 -4.407544 1
#> 6 1 -6.90 -1.55 0.93272524 -0.865274423 -5.967275 -2.415274 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4900 -39200 7900
#> initial value 998.131940
#> iter 2 value 812.414262
#> iter 3 value 808.579023
#> iter 4 value 804.960195
#> iter 5 value 759.771488
#> iter 6 value 749.798322
#> iter 7 value 748.363417
#> iter 8 value 748.339039
#> iter 9 value 748.338935
#> iter 10 value 748.338571
#> iter 10 value 748.338561
#> iter 11 value 748.338511
#> iter 11 value 748.338504
#> iter 11 value 748.338501
#> final value 748.338501
#> converged
#> This is Run number 345
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.6368384 -1.5719205 -1.713162 -13.771921 1
#> 2 1 -6.20 -3.90 -0.3814138 0.6502442 -6.581414 -3.249756 2
#> 3 1 -14.20 -5.80 1.7802192 -0.7996534 -12.419781 -6.599653 2
#> 4 1 -2.10 -13.20 -0.4202401 -1.0784503 -2.520240 -14.278450 1
#> 5 1 -1.70 -4.30 0.7905430 -0.2944579 -0.909457 -4.594458 1
#> 6 1 -6.90 -1.55 2.1565441 -0.4206706 -4.743456 -1.970671 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5260 -38975 8375
#> initial value 998.131940
#> iter 2 value 812.859220
#> iter 3 value 811.411150
#> iter 4 value 810.091384
#> iter 5 value 762.950810
#> iter 6 value 753.044135
#> iter 7 value 751.574684
#> iter 8 value 751.551055
#> iter 9 value 751.550891
#> iter 10 value 751.550402
#> iter 10 value 751.550401
#> iter 10 value 751.550395
#> final value 751.550395
#> converged
#> This is Run number 346
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.1846255 -0.8965648 -1.1653745 -13.096565 1
#> 2 1 -6.20 -3.90 0.4464393 2.8688027 -5.7535607 -1.031197 2
#> 3 1 -14.20 -5.80 0.3236778 0.9421250 -13.8763222 -4.857875 2
#> 4 1 -2.10 -13.20 -0.2979886 0.3751373 -2.3979886 -12.824863 1
#> 5 1 -1.70 -4.30 1.5441655 0.8126519 -0.1558345 -3.487348 1
#> 6 1 -6.90 -1.55 0.4068959 -0.4614455 -6.4931041 -2.011445 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5000 -38725 9325
#> initial value 998.131940
#> iter 2 value 810.013955
#> iter 3 value 808.970048
#> iter 4 value 808.019637
#> iter 5 value 758.018767
#> iter 6 value 748.406896
#> iter 7 value 746.852543
#> iter 8 value 746.830282
#> iter 9 value 746.829963
#> iter 10 value 746.829834
#> iter 10 value 746.829824
#> iter 10 value 746.829824
#> final value 746.829824
#> converged
#> This is Run number 347
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.4121215 1.5528802 -2.762122 -10.6471198 1
#> 2 1 -6.20 -3.90 1.4092585 0.6026812 -4.790741 -3.2973188 2
#> 3 1 -14.20 -5.80 1.2208087 0.1665696 -12.979191 -5.6334304 2
#> 4 1 -2.10 -13.20 -0.4504359 1.7127610 -2.550436 -11.4872390 1
#> 5 1 -1.70 -4.30 -0.7336525 -0.6945650 -2.433652 -4.9945650 1
#> 6 1 -6.90 -1.55 0.0815609 0.9401294 -6.818439 -0.6098706 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4540 -38800 9125
#> initial value 998.131940
#> iter 2 value 810.184489
#> iter 3 value 807.209052
#> iter 4 value 804.356523
#> iter 5 value 755.062416
#> iter 6 value 745.525249
#> iter 7 value 743.959010
#> iter 8 value 743.934783
#> iter 9 value 743.934569
#> iter 10 value 743.934435
#> iter 10 value 743.934430
#> iter 10 value 743.934430
#> final value 743.934430
#> converged
#> This is Run number 348
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.5015715 1.0594119 -0.8484285 -11.1405881 1
#> 2 1 -6.20 -3.90 3.3432611 -0.5466615 -2.8567389 -4.4466615 1
#> 3 1 -14.20 -5.80 1.8423747 5.2175165 -12.3576253 -0.5824835 2
#> 4 1 -2.10 -13.20 0.7438291 -0.4760446 -1.3561709 -13.6760446 1
#> 5 1 -1.70 -4.30 0.8662467 -0.6281226 -0.8337533 -4.9281226 1
#> 6 1 -6.90 -1.55 -0.5520316 -0.2359703 -7.4520316 -1.7859703 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4600 -37525 7750
#> initial value 998.131940
#> iter 2 value 837.315645
#> iter 3 value 835.832299
#> iter 4 value 832.701324
#> iter 5 value 781.718182
#> iter 6 value 772.098115
#> iter 7 value 770.598166
#> iter 8 value 770.572207
#> iter 9 value 770.571892
#> iter 10 value 770.571782
#> iter 10 value 770.571779
#> iter 11 value 770.571760
#> iter 12 value 770.571701
#> iter 12 value 770.571700
#> iter 12 value 770.571698
#> final value 770.571698
#> converged
#> This is Run number 349
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.2588168 0.9466098 -2.091183 -11.253390 1
#> 2 1 -6.20 -3.90 -0.5067760 1.3309883 -6.706776 -2.569012 2
#> 3 1 -14.20 -5.80 -0.4059966 2.4095002 -14.605997 -3.390500 2
#> 4 1 -2.10 -13.20 -0.2186545 -1.0721353 -2.318654 -14.272135 1
#> 5 1 -1.70 -4.30 0.8688000 0.5195806 -0.831200 -3.780419 1
#> 6 1 -6.90 -1.55 -0.4139487 3.1344057 -7.313949 1.584406 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4880 -37675 7775
#> initial value 998.131940
#> iter 2 value 835.213850
#> iter 3 value 834.600581
#> iter 4 value 832.404093
#> iter 5 value 781.832012
#> iter 6 value 772.134762
#> iter 7 value 770.641841
#> iter 8 value 770.614211
#> iter 9 value 770.613840
#> iter 10 value 770.613619
#> iter 11 value 770.613593
#> iter 12 value 770.613510
#> iter 12 value 770.613510
#> iter 12 value 770.613510
#> final value 770.613510
#> converged
#> This is Run number 350
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.1850442 -1.9085254 -3.53504425 -14.108525 1
#> 2 1 -6.20 -3.90 2.3496479 0.2835548 -3.85035209 -3.616445 2
#> 3 1 -14.20 -5.80 0.4707051 -0.7012381 -13.72929492 -6.501238 2
#> 4 1 -2.10 -13.20 0.9992192 0.5121621 -1.10078076 -12.687838 1
#> 5 1 -1.70 -4.30 1.6303417 -0.4631115 -0.06965833 -4.763111 1
#> 6 1 -6.90 -1.55 3.0592815 -0.0319308 -3.84071847 -1.581931 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5040 -36325 7350
#> initial value 998.131940
#> iter 2 value 855.655712
#> iter 3 value 844.304044
#> iter 4 value 843.608121
#> iter 5 value 801.261649
#> iter 6 value 793.188970
#> iter 7 value 791.602610
#> iter 8 value 791.550451
#> iter 9 value 791.549687
#> iter 10 value 791.549482
#> iter 11 value 791.549210
#> iter 12 value 791.549052
#> iter 12 value 791.549052
#> iter 12 value 791.549052
#> final value 791.549052
#> converged
#> This is Run number 351
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.02725301 -0.07871375 -2.322747 -12.278714 1
#> 2 1 -6.20 -3.90 0.44469648 0.42041939 -5.755304 -3.479581 2
#> 3 1 -14.20 -5.80 1.04522481 -0.41606128 -13.154775 -6.216061 2
#> 4 1 -2.10 -13.20 0.15561969 0.68066569 -1.944380 -12.519334 1
#> 5 1 -1.70 -4.30 -0.34403593 -0.52488190 -2.044036 -4.824882 1
#> 6 1 -6.90 -1.55 0.09023588 -0.57255445 -6.809764 -2.122554 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5360 -39125 8025
#> initial value 998.131940
#> iter 2 value 812.828852
#> iter 3 value 811.144174
#> iter 4 value 809.614531
#> iter 5 value 763.696158
#> iter 6 value 753.672789
#> iter 7 value 752.233554
#> iter 8 value 752.208006
#> iter 9 value 752.207689
#> iter 10 value 752.207453
#> iter 11 value 752.207422
#> iter 12 value 752.207163
#> iter 12 value 752.207163
#> iter 12 value 752.207163
#> final value 752.207163
#> converged
#> This is Run number 352
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.4932167 0.3573756 -1.8567833 -11.842624 1
#> 2 1 -6.20 -3.90 -1.3268986 0.4158702 -7.5268986 -3.484130 2
#> 3 1 -14.20 -5.80 0.2286973 0.5076002 -13.9713027 -5.292400 2
#> 4 1 -2.10 -13.20 -0.9213876 -1.4873946 -3.0213876 -14.687395 1
#> 5 1 -1.70 -4.30 1.1164906 0.1165619 -0.5835094 -4.183438 1
#> 6 1 -6.90 -1.55 -1.0190904 -0.3117040 -7.9190904 -1.861704 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5300 -39625 7775
#> initial value 998.131940
#> iter 2 value 806.750988
#> iter 3 value 803.618306
#> iter 4 value 801.046348
#> iter 5 value 757.489005
#> iter 6 value 747.382988
#> iter 7 value 745.987785
#> iter 8 value 745.962597
#> iter 9 value 745.962393
#> iter 10 value 745.961934
#> iter 10 value 745.961933
#> iter 11 value 745.961902
#> iter 12 value 745.961853
#> iter 12 value 745.961849
#> iter 12 value 745.961846
#> final value 745.961846
#> converged
#> This is Run number 353
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.7170833 2.5733882 -3.067083 -9.6266118 1
#> 2 1 -6.20 -3.90 0.6529054 1.8761164 -5.547095 -2.0238836 2
#> 3 1 -14.20 -5.80 2.6729008 -0.3976310 -11.527099 -6.1976310 2
#> 4 1 -2.10 -13.20 0.7721255 -0.2293782 -1.327875 -13.4293782 1
#> 5 1 -1.70 -4.30 0.6514440 -0.7152350 -1.048556 -5.0152350 1
#> 6 1 -6.90 -1.55 2.5120085 1.2303612 -4.387991 -0.3196388 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5120 -39075 8250
#> initial value 998.131940
#> iter 2 value 812.166368
#> iter 3 value 809.947693
#> iter 4 value 807.922350
#> iter 5 value 761.386914
#> iter 6 value 751.475741
#> iter 7 value 750.021328
#> iter 8 value 749.997426
#> iter 9 value 749.997279
#> iter 10 value 749.996765
#> iter 10 value 749.996758
#> iter 11 value 749.996709
#> iter 12 value 749.996693
#> iter 12 value 749.996693
#> iter 12 value 749.996688
#> final value 749.996688
#> converged
#> This is Run number 354
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.9593125 3.1568158 -3.309313 -9.043184 1
#> 2 1 -6.20 -3.90 0.8035982 -0.2137574 -5.396402 -4.113757 2
#> 3 1 -14.20 -5.80 3.0211218 0.0174555 -11.178878 -5.782545 2
#> 4 1 -2.10 -13.20 -1.4069203 1.4065448 -3.506920 -11.793455 1
#> 5 1 -1.70 -4.30 -0.3215421 0.4220955 -2.021542 -3.877905 1
#> 6 1 -6.90 -1.55 0.5420814 0.1349934 -6.357919 -1.415007 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3300 -35775 8150
#> initial value 998.131940
#> iter 2 value 856.390439
#> iter 3 value 853.539316
#> iter 4 value 847.826197
#> iter 5 value 789.761415
#> iter 6 value 780.852346
#> iter 7 value 779.221403
#> iter 8 value 779.200258
#> iter 9 value 779.200242
#> iter 10 value 779.200222
#> iter 11 value 779.200206
#> iter 12 value 779.200194
#> iter 12 value 779.200194
#> iter 12 value 779.200194
#> final value 779.200194
#> converged
#> This is Run number 355
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.9130030 -0.5354161 -3.2630030 -12.7354161 1
#> 2 1 -6.20 -3.90 4.6493690 2.4731354 -1.5506310 -1.4268646 2
#> 3 1 -14.20 -5.80 -0.1586258 2.6252377 -14.3586258 -3.1747623 2
#> 4 1 -2.10 -13.20 -1.4270052 1.0014141 -3.5270052 -12.1985859 1
#> 5 1 -1.70 -4.30 1.3353345 -0.7633856 -0.3646655 -5.0633856 1
#> 6 1 -6.90 -1.55 1.0115954 1.6759113 -5.8884046 0.1259113 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4360 -38575 8000
#> initial value 998.131940
#> iter 2 value 820.773784
#> iter 3 value 815.769247
#> iter 4 value 810.554168
#> iter 5 value 763.155982
#> iter 6 value 753.357496
#> iter 7 value 751.850293
#> iter 8 value 751.826264
#> iter 9 value 751.826205
#> iter 10 value 751.826054
#> iter 10 value 751.826047
#> iter 10 value 751.826038
#> final value 751.826038
#> converged
#> This is Run number 356
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.2673822 -0.4425560 -2.617382 -12.642556 1
#> 2 1 -6.20 -3.90 -0.6103810 0.5189101 -6.810381 -3.381090 2
#> 3 1 -14.20 -5.80 -1.2198702 -0.1028806 -15.419870 -5.902881 2
#> 4 1 -2.10 -13.20 -0.6940676 -0.3398060 -2.794068 -13.539806 1
#> 5 1 -1.70 -4.30 -0.3623592 -0.5632029 -2.062359 -4.863203 1
#> 6 1 -6.90 -1.55 3.4075988 0.8266540 -3.492401 -0.723346 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4920 -38300 8125
#> initial value 998.131940
#> iter 2 value 824.280168
#> iter 3 value 822.916682
#> iter 4 value 820.722446
#> iter 5 value 771.626461
#> iter 6 value 761.831671
#> iter 7 value 760.348396
#> iter 8 value 760.323333
#> iter 9 value 760.323000
#> iter 10 value 760.322777
#> iter 11 value 760.322755
#> iter 12 value 760.322652
#> iter 12 value 760.322652
#> iter 12 value 760.322652
#> final value 760.322652
#> converged
#> This is Run number 357
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.04024916 1.3536944 -2.390249 -10.8463056 1
#> 2 1 -6.20 -3.90 -0.21442790 -0.3396637 -6.414428 -4.2396637 2
#> 3 1 -14.20 -5.80 0.73330105 -0.2023386 -13.466699 -6.0023386 2
#> 4 1 -2.10 -13.20 -0.13240561 0.4959580 -2.232406 -12.7040420 1
#> 5 1 -1.70 -4.30 2.75512332 0.5772776 1.055123 -3.7227224 1
#> 6 1 -6.90 -1.55 0.29672144 1.0355686 -6.603279 -0.5144314 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4620 -36500 7725
#> initial value 998.131940
#> iter 2 value 851.138948
#> iter 3 value 838.003282
#> iter 4 value 836.659162
#> iter 5 value 794.303189
#> iter 6 value 786.211620
#> iter 7 value 784.748440
#> iter 8 value 784.694857
#> iter 9 value 784.693989
#> iter 10 value 784.693821
#> iter 11 value 784.693634
#> iter 12 value 784.693503
#> iter 12 value 784.693503
#> iter 12 value 784.693503
#> final value 784.693503
#> converged
#> This is Run number 358
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.0980772 0.8544942 -1.251923 -11.345506 1
#> 2 1 -6.20 -3.90 -0.0453205 -0.2242260 -6.245320 -4.124226 2
#> 3 1 -14.20 -5.80 1.8688299 0.3509649 -12.331170 -5.449035 2
#> 4 1 -2.10 -13.20 0.2958235 1.1600146 -1.804177 -12.039985 1
#> 5 1 -1.70 -4.30 0.5372542 -1.1002943 -1.162746 -5.400294 1
#> 6 1 -6.90 -1.55 -1.5984372 -0.6500652 -8.498437 -2.200065 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5000 -38350 7525
#> initial value 998.131940
#> iter 2 value 827.178317
#> iter 3 value 825.209564
#> iter 4 value 822.441111
#> iter 5 value 774.818113
#> iter 6 value 764.886907
#> iter 7 value 763.418276
#> iter 8 value 763.390383
#> iter 9 value 763.390030
#> iter 10 value 763.389855
#> iter 10 value 763.389854
#> iter 11 value 763.389815
#> iter 12 value 763.389788
#> iter 12 value 763.389787
#> iter 12 value 763.389782
#> final value 763.389782
#> converged
#> This is Run number 359
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.5656040 -0.5418719 0.2156040 -12.74187185 1
#> 2 1 -6.20 -3.90 2.0919263 -0.7147554 -4.1080737 -4.61475538 1
#> 3 1 -14.20 -5.80 2.9202250 1.0211659 -11.2797750 -4.77883407 2
#> 4 1 -2.10 -13.20 0.4856633 -0.3165639 -1.6143367 -13.51656390 1
#> 5 1 -1.70 -4.30 2.2662467 -0.3031476 0.5662467 -4.60314761 1
#> 6 1 -6.90 -1.55 0.7659175 1.5254841 -6.1340825 -0.02451594 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3520 -35325 9125
#> initial value 998.131940
#> iter 2 value 855.837566
#> iter 3 value 836.901798
#> iter 4 value 835.091158
#> iter 5 value 791.021389
#> iter 6 value 783.817984
#> iter 7 value 782.922565
#> iter 8 value 782.889931
#> iter 9 value 782.889419
#> iter 10 value 782.889318
#> iter 11 value 782.889222
#> iter 12 value 782.889146
#> iter 12 value 782.889146
#> iter 12 value 782.889146
#> final value 782.889146
#> converged
#> This is Run number 360
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.3616998 -1.3274841 -1.988300 -13.527484 1
#> 2 1 -6.20 -3.90 0.3440959 0.7921910 -5.855904 -3.107809 2
#> 3 1 -14.20 -5.80 -0.8539081 2.3750007 -15.053908 -3.424999 2
#> 4 1 -2.10 -13.20 -0.6520002 -0.2052735 -2.752000 -13.405274 1
#> 5 1 -1.70 -4.30 -0.3327177 0.8926853 -2.032718 -3.407315 1
#> 6 1 -6.90 -1.55 1.9245888 -0.3060775 -4.975411 -1.856078 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4020 -36000 8775
#> initial value 998.131940
#> iter 2 value 850.477007
#> iter 3 value 833.417475
#> iter 4 value 832.034289
#> iter 5 value 789.331384
#> iter 6 value 781.718467
#> iter 7 value 780.717200
#> iter 8 value 780.680305
#> iter 9 value 780.679679
#> iter 10 value 780.679539
#> iter 11 value 780.679386
#> iter 12 value 780.679275
#> iter 12 value 780.679275
#> iter 12 value 780.679275
#> final value 780.679275
#> converged
#> This is Run number 361
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.8125219 -0.14448129 -1.537478 -12.344481 1
#> 2 1 -6.20 -3.90 -0.4058512 1.46576371 -6.605851 -2.434236 2
#> 3 1 -14.20 -5.80 1.2509710 -0.30881613 -12.949029 -6.108816 2
#> 4 1 -2.10 -13.20 -0.1160869 -1.36223617 -2.216087 -14.562236 1
#> 5 1 -1.70 -4.30 -0.8137025 -0.59355456 -2.513702 -4.893555 1
#> 6 1 -6.90 -1.55 0.3535598 -0.06685588 -6.546440 -1.616856 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4820 -36650 7575
#> initial value 998.131940
#> iter 2 value 850.142546
#> iter 3 value 837.709710
#> iter 4 value 836.585439
#> iter 5 value 794.661852
#> iter 6 value 786.488407
#> iter 7 value 784.962493
#> iter 8 value 784.906932
#> iter 9 value 784.906035
#> iter 10 value 784.905849
#> iter 11 value 784.905628
#> iter 12 value 784.905479
#> iter 12 value 784.905479
#> iter 12 value 784.905479
#> final value 784.905479
#> converged
#> This is Run number 362
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.41667219 1.0259871 -1.933328 -11.1740129 1
#> 2 1 -6.20 -3.90 -1.10481858 -0.5895523 -7.304819 -4.4895523 2
#> 3 1 -14.20 -5.80 0.85362258 -0.9780296 -13.346377 -6.7780296 2
#> 4 1 -2.10 -13.20 0.47161334 -0.2051299 -1.628387 -13.4051299 1
#> 5 1 -1.70 -4.30 -0.82335686 0.2377046 -2.523357 -4.0622954 1
#> 6 1 -6.90 -1.55 -0.05726535 2.0811237 -6.957265 0.5311237 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5300 -37925 7500
#> initial value 998.131940
#> iter 2 value 833.380402
#> iter 3 value 833.307704
#> iter 4 value 831.927023
#> iter 5 value 782.829644
#> iter 6 value 772.959988
#> iter 7 value 771.459781
#> iter 8 value 771.427580
#> iter 9 value 771.427553
#> iter 10 value 771.427098
#> iter 10 value 771.427093
#> iter 11 value 771.427010
#> iter 12 value 771.426963
#> iter 13 value 771.426863
#> iter 14 value 771.426768
#> iter 15 value 771.426711
#> iter 15 value 771.426709
#> iter 15 value 771.426709
#> final value 771.426709
#> converged
#> This is Run number 363
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.0319117 -0.32232246 -1.3180883 -12.522322 1
#> 2 1 -6.20 -3.90 2.5591554 -1.51283062 -3.6408446 -5.412831 1
#> 3 1 -14.20 -5.80 2.0385169 0.29091156 -12.1614831 -5.509088 2
#> 4 1 -2.10 -13.20 0.7341922 -0.66802925 -1.3658078 -13.868029 1
#> 5 1 -1.70 -4.30 1.6768152 -0.35699609 -0.0231848 -4.656996 1
#> 6 1 -6.90 -1.55 3.3963502 -0.09066931 -3.5036498 -1.640669 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5060 -38575 6850
#> initial value 998.131940
#> iter 2 value 827.621372
#> iter 3 value 824.321264
#> iter 4 value 820.557081
#> iter 5 value 775.225503
#> iter 6 value 765.122933
#> iter 7 value 763.607487
#> iter 8 value 763.575720
#> iter 9 value 763.575684
#> iter 10 value 763.575550
#> iter 10 value 763.575550
#> iter 11 value 763.575532
#> iter 11 value 763.575530
#> iter 11 value 763.575530
#> final value 763.575530
#> converged
#> This is Run number 364
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.29979394 -0.6037298 -2.6497939 -12.8037298 1
#> 2 1 -6.20 -3.90 0.03807352 -0.1663083 -6.1619265 -4.0663083 2
#> 3 1 -14.20 -5.80 2.72995932 1.9812275 -11.4700407 -3.8187725 2
#> 4 1 -2.10 -13.20 1.90996878 1.1388078 -0.1900312 -12.0611922 1
#> 5 1 -1.70 -4.30 0.25892334 -0.2321796 -1.4410767 -4.5321796 1
#> 6 1 -6.90 -1.55 0.03012699 1.0433253 -6.8698730 -0.5066747 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5000 -36275 6325
#> initial value 998.131940
#> iter 2 value 861.584523
#> iter 3 value 861.523344
#> iter 4 value 859.337440
#> iter 5 value 807.350677
#> iter 6 value 798.125719
#> iter 7 value 796.476223
#> iter 8 value 796.440430
#> iter 9 value 796.440323
#> iter 10 value 796.440172
#> iter 10 value 796.440172
#> iter 11 value 796.440143
#> iter 11 value 796.440138
#> iter 11 value 796.440136
#> final value 796.440136
#> converged
#> This is Run number 365
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.01219397 0.99723082 -2.362194 -11.20276918 1
#> 2 1 -6.20 -3.90 0.40405388 0.92371048 -5.795946 -2.97628952 2
#> 3 1 -14.20 -5.80 -0.86655613 2.36137305 -15.066556 -3.43862695 2
#> 4 1 -2.10 -13.20 0.95352422 1.05295476 -1.146476 -12.14704524 1
#> 5 1 -1.70 -4.30 0.01023586 0.05682467 -1.689764 -4.24317533 1
#> 6 1 -6.90 -1.55 0.91569490 1.53576201 -5.984305 -0.01423799 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4280 -36900 7700
#> initial value 998.131940
#> iter 2 value 845.831101
#> iter 3 value 844.239232
#> iter 4 value 840.488750
#> iter 5 value 787.476003
#> iter 6 value 778.081914
#> iter 7 value 776.562961
#> iter 8 value 776.538196
#> iter 9 value 776.537983
#> iter 10 value 776.537886
#> iter 10 value 776.537885
#> iter 10 value 776.537876
#> final value 776.537876
#> converged
#> This is Run number 366
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.6498272 -0.59861619 -1.70017282 -12.7986162 1
#> 2 1 -6.20 -3.90 -0.4667719 2.46168700 -6.66677190 -1.4383130 2
#> 3 1 -14.20 -5.80 4.0090419 -0.83283052 -10.19095813 -6.6328305 2
#> 4 1 -2.10 -13.20 1.1494080 -0.01759811 -0.95059204 -13.2175981 1
#> 5 1 -1.70 -4.30 1.6530773 1.69424169 -0.04692274 -2.6057583 1
#> 6 1 -6.90 -1.55 2.4524643 0.56926992 -4.44753569 -0.9807301 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4360 -37900 7675
#> initial value 998.131940
#> iter 2 value 832.383563
#> iter 3 value 828.549410
#> iter 4 value 823.821572
#> iter 5 value 774.533144
#> iter 6 value 764.802990
#> iter 7 value 763.285501
#> iter 8 value 763.260523
#> iter 9 value 763.260403
#> iter 10 value 763.260322
#> iter 10 value 763.260321
#> iter 10 value 763.260312
#> final value 763.260312
#> converged
#> This is Run number 367
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.0012587 1.3007304 -1.3487413 -10.89926959 1
#> 2 1 -6.20 -3.90 0.4371126 0.6676350 -5.7628874 -3.23236499 2
#> 3 1 -14.20 -5.80 6.3081166 0.2094593 -7.8918834 -5.59054070 2
#> 4 1 -2.10 -13.20 1.2640702 -0.6684124 -0.8359298 -13.86841245 1
#> 5 1 -1.70 -4.30 -0.5608723 4.3784805 -2.2608723 0.07848048 2
#> 6 1 -6.90 -1.55 -1.2975348 3.8186456 -8.1975348 2.26864562 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4120 -37175 8700
#> initial value 998.131940
#> iter 2 value 835.759147
#> iter 3 value 834.829143
#> iter 4 value 831.380967
#> iter 5 value 776.967391
#> iter 6 value 767.674711
#> iter 7 value 766.090007
#> iter 8 value 766.067846
#> iter 9 value 766.067774
#> iter 10 value 766.067564
#> iter 10 value 766.067553
#> iter 11 value 766.067541
#> iter 12 value 766.067529
#> iter 12 value 766.067529
#> iter 12 value 766.067527
#> final value 766.067527
#> converged
#> This is Run number 368
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.4277897 0.2171758 -2.777790 -11.982824 1
#> 2 1 -6.20 -3.90 -1.5631224 1.3302739 -7.763122 -2.569726 2
#> 3 1 -14.20 -5.80 1.7974787 0.9849808 -12.402521 -4.815019 2
#> 4 1 -2.10 -13.20 -1.6154727 1.1655980 -3.715473 -12.034402 1
#> 5 1 -1.70 -4.30 1.5427620 0.5009822 -0.157238 -3.799018 1
#> 6 1 -6.90 -1.55 -0.2435272 -0.9651862 -7.143527 -2.515186 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4580 -35750 7600
#> initial value 998.131940
#> iter 2 value 861.323766
#> iter 3 value 848.752306
#> iter 4 value 847.665556
#> iter 5 value 803.990012
#> iter 6 value 796.185463
#> iter 7 value 794.725810
#> iter 8 value 794.678772
#> iter 9 value 794.678081
#> iter 10 value 794.677910
#> iter 11 value 794.677696
#> iter 12 value 794.677571
#> iter 12 value 794.677571
#> iter 12 value 794.677571
#> final value 794.677571
#> converged
#> This is Run number 369
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.1087193 -0.8489135 -2.2412807 -13.0489135 1
#> 2 1 -6.20 -3.90 -0.4060392 -0.5196784 -6.6060392 -4.4196784 2
#> 3 1 -14.20 -5.80 0.1924797 1.7171083 -14.0075203 -4.0828917 2
#> 4 1 -2.10 -13.20 1.1559293 -0.1117271 -0.9440707 -13.3117271 1
#> 5 1 -1.70 -4.30 0.9393868 -1.6484525 -0.7606132 -5.9484525 1
#> 6 1 -6.90 -1.55 -0.5963037 2.3394375 -7.4963037 0.7894375 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4620 -39425 8650
#> initial value 998.131940
#> iter 2 value 804.098937
#> iter 3 value 799.223940
#> iter 4 value 795.230262
#> iter 5 value 749.486085
#> iter 6 value 739.781742
#> iter 7 value 738.285736
#> iter 8 value 738.261470
#> iter 9 value 738.261279
#> iter 10 value 738.261095
#> iter 11 value 738.261065
#> iter 12 value 738.261001
#> iter 12 value 738.261001
#> iter 12 value 738.261001
#> final value 738.261001
#> converged
#> This is Run number 370
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.0383507 -1.4976387 -2.3883507 -13.697639 1
#> 2 1 -6.20 -3.90 1.2589814 1.0972449 -4.9410186 -2.802755 2
#> 3 1 -14.20 -5.80 1.8608068 0.0618252 -12.3391932 -5.738175 2
#> 4 1 -2.10 -13.20 2.5282412 2.8785026 0.4282412 -10.321497 1
#> 5 1 -1.70 -4.30 0.4304900 1.3051306 -1.2695100 -2.994869 1
#> 6 1 -6.90 -1.55 0.3967506 0.2209532 -6.5032494 -1.329047 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4740 -37725 7425
#> initial value 998.131940
#> iter 2 value 836.497521
#> iter 3 value 834.586024
#> iter 4 value 831.344444
#> iter 5 value 781.781882
#> iter 6 value 772.034232
#> iter 7 value 770.535598
#> iter 8 value 770.507857
#> iter 9 value 770.507656
#> iter 10 value 770.507490
#> iter 10 value 770.507490
#> iter 11 value 770.507441
#> iter 12 value 770.507410
#> iter 12 value 770.507410
#> iter 12 value 770.507401
#> final value 770.507401
#> converged
#> This is Run number 371
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.15715989 0.1404241 -2.192840 -12.0595759 1
#> 2 1 -6.20 -3.90 0.43102490 -1.4566955 -5.768975 -5.3566955 2
#> 3 1 -14.20 -5.80 2.84253510 1.3263784 -11.357465 -4.4736216 2
#> 4 1 -2.10 -13.20 -0.09311038 0.5107775 -2.193110 -12.6892225 1
#> 5 1 -1.70 -4.30 -1.34759194 -0.3666849 -3.047592 -4.6666849 1
#> 6 1 -6.90 -1.55 1.05536911 2.2733148 -5.844631 0.7233148 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4840 -37800 7775
#> initial value 998.131940
#> iter 2 value 833.464447
#> iter 3 value 832.420401
#> iter 4 value 829.957372
#> iter 5 value 779.836661
#> iter 6 value 770.110450
#> iter 7 value 768.621442
#> iter 8 value 768.594392
#> iter 9 value 768.594005
#> iter 10 value 768.593833
#> iter 11 value 768.593818
#> iter 12 value 768.593734
#> iter 12 value 768.593734
#> iter 12 value 768.593734
#> final value 768.593734
#> converged
#> This is Run number 372
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.7738066 -1.0689014 -3.123807 -13.268901 1
#> 2 1 -6.20 -3.90 0.8018479 2.3106060 -5.398152 -1.589394 2
#> 3 1 -14.20 -5.80 2.6053475 -1.0013615 -11.594653 -6.801362 2
#> 4 1 -2.10 -13.20 0.1501226 1.4641017 -1.949877 -11.735898 1
#> 5 1 -1.70 -4.30 -1.0008023 -0.5840676 -2.700802 -4.884068 1
#> 6 1 -6.90 -1.55 0.2258377 -0.4666577 -6.674162 -2.016658 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4500 -36100 7625
#> initial value 998.131940
#> iter 2 value 856.770061
#> iter 3 value 843.823416
#> iter 4 value 842.358218
#> iter 5 value 799.011442
#> iter 6 value 791.063319
#> iter 7 value 789.558782
#> iter 8 value 789.505895
#> iter 9 value 789.505085
#> iter 10 value 789.504932
#> iter 11 value 789.504758
#> iter 12 value 789.504641
#> iter 12 value 789.504641
#> iter 12 value 789.504641
#> final value 789.504641
#> converged
#> This is Run number 373
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.2795170 -1.2102909 -2.0704830 -13.4102909 1
#> 2 1 -6.20 -3.90 0.5119078 -0.5124592 -5.6880922 -4.4124592 2
#> 3 1 -14.20 -5.80 0.3909908 -1.8717791 -13.8090092 -7.6717791 2
#> 4 1 -2.10 -13.20 1.7430471 5.9984772 -0.3569529 -7.2015228 1
#> 5 1 -1.70 -4.30 1.1478513 0.4984250 -0.5521487 -3.8015750 1
#> 6 1 -6.90 -1.55 1.6004749 1.8942859 -5.2995251 0.3442859 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5380 -37700 7300
#> initial value 998.131940
#> iter 2 value 837.638211
#> iter 3 value 826.469149
#> iter 4 value 825.689619
#> iter 5 value 786.253051
#> iter 6 value 777.657011
#> iter 7 value 776.000204
#> iter 8 value 775.933840
#> iter 9 value 775.932702
#> iter 10 value 775.932478
#> iter 11 value 775.932201
#> iter 12 value 775.932001
#> iter 12 value 775.932001
#> iter 12 value 775.932001
#> final value 775.932001
#> converged
#> This is Run number 374
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 2.7997693 -0.6087297 0.4497693 -12.8087297 1
#> 2 1 -6.20 -3.90 1.1691240 0.2891552 -5.0308760 -3.6108448 2
#> 3 1 -14.20 -5.80 0.3740109 -0.4132555 -13.8259891 -6.2132555 2
#> 4 1 -2.10 -13.20 4.4897640 1.0074934 2.3897640 -12.1925066 1
#> 5 1 -1.70 -4.30 -0.3140891 0.2805144 -2.0140891 -4.0194856 1
#> 6 1 -6.90 -1.55 1.5529358 0.8682154 -5.3470642 -0.6817846 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5000 -38000 7525
#> initial value 998.131940
#> iter 2 value 832.163255
#> iter 3 value 830.941600
#> iter 4 value 828.537437
#> iter 5 value 779.649730
#> iter 6 value 769.808306
#> iter 7 value 768.324911
#> iter 8 value 768.296080
#> iter 9 value 768.295797
#> iter 10 value 768.295749
#> iter 10 value 768.295742
#> iter 11 value 768.295613
#> iter 12 value 768.295470
#> iter 12 value 768.295461
#> iter 12 value 768.295461
#> final value 768.295461
#> converged
#> This is Run number 375
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.10825421 2.6102605 -2.4582542 -9.5897395 1
#> 2 1 -6.20 -3.90 4.07953664 1.9653566 -2.1204634 -1.9346434 2
#> 3 1 -14.20 -5.80 -0.59442822 -0.6164941 -14.7944282 -6.4164941 2
#> 4 1 -2.10 -13.20 -0.19225758 -0.8159667 -2.2922576 -14.0159667 1
#> 5 1 -1.70 -4.30 1.29118556 2.2682028 -0.4088144 -2.0317972 1
#> 6 1 -6.90 -1.55 -0.04740679 1.6902346 -6.9474068 0.1402346 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4660 -37400 7800
#> initial value 998.131940
#> iter 2 value 838.760847
#> iter 3 value 837.929299
#> iter 4 value 835.232297
#> iter 5 value 783.663892
#> iter 6 value 774.083661
#> iter 7 value 772.583535
#> iter 8 value 772.557161
#> iter 9 value 772.556821
#> iter 10 value 772.556645
#> iter 10 value 772.556634
#> iter 11 value 772.556612
#> iter 12 value 772.556582
#> iter 12 value 772.556575
#> iter 12 value 772.556574
#> final value 772.556574
#> converged
#> This is Run number 376
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 4.3835045 0.5551160 2.0335045 -11.644884 1
#> 2 1 -6.20 -3.90 0.6310401 1.2078091 -5.5689599 -2.692191 2
#> 3 1 -14.20 -5.80 -1.2714413 -1.7292705 -15.4714413 -7.529270 2
#> 4 1 -2.10 -13.20 -0.2045139 0.4067189 -2.3045139 -12.793281 1
#> 5 1 -1.70 -4.30 1.2313419 0.8381974 -0.4686581 -3.461803 1
#> 6 1 -6.90 -1.55 1.2515222 -0.3125951 -5.6484778 -1.862595 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5460 -37600 6300
#> initial value 998.131940
#> iter 2 value 844.167762
#> iter 3 value 843.492770
#> iter 4 value 841.476704
#> iter 5 value 793.783305
#> iter 6 value 783.979258
#> iter 7 value 782.294534
#> iter 8 value 782.252893
#> iter 9 value 782.252753
#> iter 10 value 782.252579
#> iter 10 value 782.252579
#> iter 11 value 782.252544
#> iter 12 value 782.252528
#> iter 12 value 782.252528
#> iter 12 value 782.252527
#> final value 782.252527
#> converged
#> This is Run number 377
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.5988669 -0.62283788 -2.948867 -12.8228379 1
#> 2 1 -6.20 -3.90 0.4624482 -0.60613924 -5.737552 -4.5061392 2
#> 3 1 -14.20 -5.80 1.6198048 1.03484604 -12.580195 -4.7651540 2
#> 4 1 -2.10 -13.20 0.6132407 0.09141809 -1.486759 -13.1085819 1
#> 5 1 -1.70 -4.30 -0.6956512 4.16384021 -2.395651 -0.1361598 2
#> 6 1 -6.90 -1.55 -0.6658098 0.51918544 -7.565810 -1.0308146 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4460 -37025 8675
#> initial value 998.131940
#> iter 2 value 838.191981
#> iter 3 value 821.890197
#> iter 4 value 820.814533
#> iter 5 value 780.256532
#> iter 6 value 772.234957
#> iter 7 value 771.200961
#> iter 8 value 771.158424
#> iter 9 value 771.157646
#> iter 10 value 771.157630
#> iter 11 value 771.157420
#> iter 12 value 771.157113
#> iter 12 value 771.157113
#> iter 12 value 771.157113
#> final value 771.157113
#> converged
#> This is Run number 378
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.6167933 -0.1271693 -1.733207 -12.327169 1
#> 2 1 -6.20 -3.90 2.5101533 2.5940287 -3.689847 -1.305971 2
#> 3 1 -14.20 -5.80 0.1456338 2.2243211 -14.054366 -3.575679 2
#> 4 1 -2.10 -13.20 -0.3324381 0.9052657 -2.432438 -12.294734 1
#> 5 1 -1.70 -4.30 0.4737975 0.8830924 -1.226202 -3.416908 1
#> 6 1 -6.90 -1.55 1.0070042 0.3681268 -5.892996 -1.181873 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4720 -39425 7525
#> initial value 998.131940
#> iter 2 value 811.128071
#> iter 3 value 805.143850
#> iter 4 value 799.684060
#> iter 5 value 756.387318
#> iter 6 value 746.309999
#> iter 7 value 744.869023
#> iter 8 value 744.843318
#> iter 9 value 744.843259
#> iter 10 value 744.843163
#> iter 10 value 744.843159
#> iter 10 value 744.843159
#> final value 744.843159
#> converged
#> This is Run number 379
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.5740542 0.52490289 -0.7759458 -11.6750971 1
#> 2 1 -6.20 -3.90 0.5202579 3.44441487 -5.6797421 -0.4555851 2
#> 3 1 -14.20 -5.80 -0.3321624 0.73308919 -14.5321624 -5.0669108 2
#> 4 1 -2.10 -13.20 0.1123449 0.99708774 -1.9876551 -12.2029123 1
#> 5 1 -1.70 -4.30 1.9437587 0.01391648 0.2437587 -4.2860835 1
#> 6 1 -6.90 -1.55 1.0834542 0.04657514 -5.8165458 -1.5034249 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5400 -38500 8250
#> initial value 998.131940
#> iter 2 value 820.621147
#> iter 3 value 820.394709
#> iter 4 value 819.628810
#> iter 5 value 771.130760
#> iter 6 value 761.212425
#> iter 7 value 759.721700
#> iter 8 value 759.696137
#> iter 9 value 759.695940
#> iter 10 value 759.695791
#> iter 11 value 759.695715
#> iter 12 value 759.695370
#> iter 12 value 759.695370
#> iter 12 value 759.695370
#> final value 759.695370
#> converged
#> This is Run number 380
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.08957112 0.28596373 -3.43957112 -11.91403627 1
#> 2 1 -6.20 -3.90 -1.43793546 0.04154968 -7.63793546 -3.85845032 2
#> 3 1 -14.20 -5.80 1.64409680 1.87728319 -12.55590320 -3.92271681 2
#> 4 1 -2.10 -13.20 -0.09666726 -0.72005535 -2.19666726 -13.92005535 1
#> 5 1 -1.70 -4.30 1.67472182 -0.71078901 -0.02527818 -5.01078901 1
#> 6 1 -6.90 -1.55 0.33081861 1.51620162 -6.56918139 -0.03379838 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5640 -40725 8025
#> initial value 998.131940
#> iter 2 value 787.726254
#> iter 3 value 783.819884
#> iter 4 value 781.844212
#> iter 5 value 741.781627
#> iter 6 value 731.764236
#> iter 7 value 730.418412
#> iter 8 value 730.394397
#> iter 9 value 730.394130
#> iter 10 value 730.393551
#> iter 10 value 730.393542
#> iter 10 value 730.393540
#> final value 730.393540
#> converged
#> This is Run number 381
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.2078319 -0.1296165 -2.142168 -12.3296165 1
#> 2 1 -6.20 -3.90 0.3659737 -0.8664973 -5.834026 -4.7664973 2
#> 3 1 -14.20 -5.80 4.0268485 0.3728212 -10.173151 -5.4271788 2
#> 4 1 -2.10 -13.20 -0.2954929 2.3993759 -2.395493 -10.8006241 1
#> 5 1 -1.70 -4.30 -0.7734906 -1.2627542 -2.473491 -5.5627542 1
#> 6 1 -6.90 -1.55 -0.9068679 0.5947578 -7.806868 -0.9552422 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4340 -36250 8025
#> initial value 998.131940
#> iter 2 value 852.385663
#> iter 3 value 838.008026
#> iter 4 value 836.462161
#> iter 5 value 793.569503
#> iter 6 value 785.635008
#> iter 7 value 784.308708
#> iter 8 value 784.260255
#> iter 9 value 784.259466
#> iter 10 value 784.259318
#> iter 11 value 784.259166
#> iter 12 value 784.259053
#> iter 12 value 784.259053
#> iter 12 value 784.259053
#> final value 784.259053
#> converged
#> This is Run number 382
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.1497147 -1.1230205 -1.200285 -13.32302051 1
#> 2 1 -6.20 -3.90 0.4819791 3.9758295 -5.718021 0.07582949 2
#> 3 1 -14.20 -5.80 -0.4438387 -0.3673674 -14.643839 -6.16736738 2
#> 4 1 -2.10 -13.20 -0.1286389 0.2109087 -2.228639 -12.98909131 1
#> 5 1 -1.70 -4.30 -0.3027404 -1.1136509 -2.002740 -5.41365085 1
#> 6 1 -6.90 -1.55 -0.5286406 -0.6931785 -7.428641 -2.24317847 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3860 -36950 8625
#> initial value 998.131940
#> iter 2 value 839.007093
#> iter 3 value 837.244536
#> iter 4 value 832.807372
#> iter 5 value 777.863995
#> iter 6 value 768.648239
#> iter 7 value 767.040295
#> iter 8 value 767.018192
#> iter 9 value 767.018142
#> iter 10 value 767.017996
#> iter 10 value 767.017990
#> iter 10 value 767.017983
#> final value 767.017983
#> converged
#> This is Run number 383
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.9506147 -1.0987883 -1.3993853 -13.2987883 1
#> 2 1 -6.20 -3.90 1.2823716 1.5328989 -4.9176284 -2.3671011 2
#> 3 1 -14.20 -5.80 -0.9801270 -0.4991820 -15.1801270 -6.2991820 2
#> 4 1 -2.10 -13.20 -0.7064763 0.4224302 -2.8064763 -12.7775698 1
#> 5 1 -1.70 -4.30 0.7910758 -0.4370879 -0.9089242 -4.7370879 1
#> 6 1 -6.90 -1.55 1.5015844 2.2532828 -5.3984156 0.7032828 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4360 -38325 8550
#> initial value 998.131940
#> iter 2 value 820.915182
#> iter 3 value 817.606581
#> iter 4 value 813.621117
#> iter 5 value 763.926516
#> iter 6 value 754.320297
#> iter 7 value 752.779973
#> iter 8 value 752.756925
#> iter 9 value 752.756829
#> iter 10 value 752.756611
#> iter 10 value 752.756610
#> iter 10 value 752.756599
#> final value 752.756599
#> converged
#> This is Run number 384
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.26480922 0.72066593 -2.614809 -11.479334 1
#> 2 1 -6.20 -3.90 0.11713983 1.24473574 -6.082860 -2.655264 2
#> 3 1 -14.20 -5.80 0.09608222 -0.02680112 -14.103918 -5.826801 2
#> 4 1 -2.10 -13.20 -0.46361642 2.13745838 -2.563616 -11.062542 1
#> 5 1 -1.70 -4.30 2.81026054 1.74416685 1.110261 -2.555833 1
#> 6 1 -6.90 -1.55 1.72614492 0.05871183 -5.173855 -1.491288 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4520 -37175 6900
#> initial value 998.131940
#> iter 2 value 846.741983
#> iter 3 value 843.847588
#> iter 4 value 839.782813
#> iter 5 value 789.484992
#> iter 6 value 779.858840
#> iter 7 value 778.290257
#> iter 8 value 778.260545
#> iter 9 value 778.260516
#> iter 10 value 778.260437
#> iter 10 value 778.260433
#> iter 10 value 778.260429
#> final value 778.260429
#> converged
#> This is Run number 385
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.7190516 0.2300190 -3.0690516 -11.969981 1
#> 2 1 -6.20 -3.90 -1.1038844 -0.6520466 -7.3038844 -4.552047 2
#> 3 1 -14.20 -5.80 0.7812419 -0.5999802 -13.4187581 -6.399980 2
#> 4 1 -2.10 -13.20 -0.9093837 1.0772270 -3.0093837 -12.122773 1
#> 5 1 -1.70 -4.30 1.0285688 0.9369974 -0.6714312 -3.363003 1
#> 6 1 -6.90 -1.55 1.8367627 0.3374118 -5.0632373 -1.212588 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4760 -35825 7600
#> initial value 998.131940
#> iter 2 value 860.465605
#> iter 3 value 848.196132
#> iter 4 value 847.428715
#> iter 5 value 804.207756
#> iter 6 value 796.366687
#> iter 7 value 794.934012
#> iter 8 value 794.889590
#> iter 9 value 794.888951
#> iter 10 value 794.888766
#> iter 11 value 794.888525
#> iter 12 value 794.888390
#> iter 12 value 794.888390
#> iter 12 value 794.888390
#> final value 794.888390
#> converged
#> This is Run number 386
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 4.12142246 -0.14167331 1.7714225 -12.3416733 1
#> 2 1 -6.20 -3.90 -0.65678170 0.17529614 -6.8567817 -3.7247039 2
#> 3 1 -14.20 -5.80 0.59916706 6.12200984 -13.6008329 0.3220098 2
#> 4 1 -2.10 -13.20 1.17549919 2.78021853 -0.9245008 -10.4197815 1
#> 5 1 -1.70 -4.30 1.19929007 0.02830958 -0.5007099 -4.2716904 1
#> 6 1 -6.90 -1.55 -0.05661805 0.73914649 -6.9566181 -0.8108535 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5080 -37725 8025
#> initial value 998.131940
#> iter 2 value 833.042227
#> iter 3 value 819.484162
#> iter 4 value 818.747363
#> iter 5 value 779.659880
#> iter 6 value 771.173961
#> iter 7 value 769.912836
#> iter 8 value 769.860754
#> iter 9 value 769.859773
#> iter 10 value 769.859558
#> iter 11 value 769.859295
#> iter 12 value 769.859095
#> iter 12 value 769.859095
#> iter 12 value 769.859095
#> final value 769.859095
#> converged
#> This is Run number 387
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.6541701 3.4091118 -3.0041701 -8.790888 1
#> 2 1 -6.20 -3.90 -1.3954942 -0.5978117 -7.5954942 -4.497812 2
#> 3 1 -14.20 -5.80 0.6364991 -0.8695243 -13.5635009 -6.669524 2
#> 4 1 -2.10 -13.20 1.1514899 2.7936829 -0.9485101 -10.406317 1
#> 5 1 -1.70 -4.30 0.9025736 -0.8443995 -0.7974264 -5.144400 1
#> 6 1 -6.90 -1.55 -1.7368481 -0.6793527 -8.6368481 -2.229353 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4760 -37175 7500
#> initial value 998.131940
#> iter 2 value 843.600337
#> iter 3 value 843.145762
#> iter 4 value 840.661855
#> iter 5 value 788.976070
#> iter 6 value 779.420732
#> iter 7 value 777.917382
#> iter 8 value 777.888857
#> iter 9 value 777.888764
#> iter 10 value 777.888395
#> iter 10 value 777.888388
#> iter 11 value 777.888319
#> iter 12 value 777.888267
#> iter 13 value 777.888244
#> iter 13 value 777.888234
#> iter 13 value 777.888234
#> final value 777.888234
#> converged
#> This is Run number 388
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.5703117 0.6647250 -2.9203117 -11.5352750 1
#> 2 1 -6.20 -3.90 2.5472377 -0.9256033 -3.6527623 -4.8256033 1
#> 3 1 -14.20 -5.80 0.5465586 1.0350317 -13.6534414 -4.7649683 2
#> 4 1 -2.10 -13.20 0.5439516 -0.1382368 -1.5560484 -13.3382368 1
#> 5 1 -1.70 -4.30 1.5680589 0.3419098 -0.1319411 -3.9580902 1
#> 6 1 -6.90 -1.55 -0.7941112 2.5146662 -7.6941112 0.9646662 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5260 -38575 7925
#> initial value 998.131940
#> iter 2 value 821.577857
#> iter 3 value 820.587459
#> iter 4 value 819.064058
#> iter 5 value 771.366148
#> iter 6 value 761.414891
#> iter 7 value 759.949591
#> iter 8 value 759.922384
#> iter 9 value 759.921881
#> iter 10 value 759.921756
#> iter 11 value 759.921718
#> iter 12 value 759.921564
#> iter 12 value 759.921564
#> iter 12 value 759.921564
#> final value 759.921564
#> converged
#> This is Run number 389
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.23223113 0.4517157 -1.1177689 -11.748284 1
#> 2 1 -6.20 -3.90 -1.10383143 0.2912761 -7.3038314 -3.608724 2
#> 3 1 -14.20 -5.80 -0.31425122 -0.8174202 -14.5142512 -6.617420 2
#> 4 1 -2.10 -13.20 0.07986887 1.1652809 -2.0201311 -12.034719 1
#> 5 1 -1.70 -4.30 1.97517649 1.5060980 0.2751765 -2.793902 1
#> 6 1 -6.90 -1.55 -0.42206344 -0.5916667 -7.3220634 -2.141667 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4940 -37100 6275
#> initial value 998.131940
#> iter 2 value 851.034848
#> iter 3 value 849.013981
#> iter 4 value 845.829782
#> iter 5 value 796.572666
#> iter 6 value 786.957421
#> iter 7 value 785.275124
#> iter 8 value 785.237498
#> iter 9 value 785.237438
#> iter 10 value 785.237412
#> iter 11 value 785.237398
#> iter 11 value 785.237396
#> iter 11 value 785.237396
#> final value 785.237396
#> converged
#> This is Run number 390
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.82367162 0.93435456 -0.5263284 -11.2656454 1
#> 2 1 -6.20 -3.90 -0.36632330 0.78592504 -6.5663233 -3.1140750 2
#> 3 1 -14.20 -5.80 -0.03008677 -0.03219793 -14.2300868 -5.8321979 2
#> 4 1 -2.10 -13.20 0.25996045 1.78262219 -1.8400395 -11.4173778 1
#> 5 1 -1.70 -4.30 -1.16930031 -0.16047565 -2.8693003 -4.4604757 1
#> 6 1 -6.90 -1.55 3.60148084 1.23276762 -3.2985192 -0.3172324 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4680 -39175 8725
#> initial value 998.131940
#> iter 2 value 807.422432
#> iter 3 value 803.604223
#> iter 4 value 800.345121
#> iter 5 value 753.371351
#> iter 6 value 743.681296
#> iter 7 value 742.174344
#> iter 8 value 742.150787
#> iter 9 value 742.150601
#> iter 10 value 742.150378
#> iter 10 value 742.150374
#> iter 10 value 742.150373
#> final value 742.150373
#> converged
#> This is Run number 391
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.8459655 0.4993639 -3.1959655 -11.700636 1
#> 2 1 -6.20 -3.90 1.9125264 0.9995615 -4.2874736 -2.900439 2
#> 3 1 -14.20 -5.80 -0.8175543 0.1450347 -15.0175543 -5.654965 2
#> 4 1 -2.10 -13.20 -0.5522547 0.7049207 -2.6522547 -12.495079 1
#> 5 1 -1.70 -4.30 2.0634114 -1.0929580 0.3634114 -5.392958 1
#> 6 1 -6.90 -1.55 1.1134110 0.1437664 -5.7865890 -1.406234 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4580 -38975 7375
#> initial value 998.131940
#> iter 2 value 818.685380
#> iter 3 value 812.707278
#> iter 4 value 807.017076
#> iter 5 value 762.377174
#> iter 6 value 752.320278
#> iter 7 value 750.837217
#> iter 8 value 750.810536
#> iter 9 value 750.810508
#> iter 10 value 750.810451
#> iter 10 value 750.810451
#> iter 10 value 750.810448
#> final value 750.810448
#> converged
#> This is Run number 392
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.7219584 1.1525429 -3.071958 -11.0474571 1
#> 2 1 -6.20 -3.90 -1.0264287 -0.8383654 -7.226429 -4.7383654 2
#> 3 1 -14.20 -5.80 -0.8196906 0.8769029 -15.019691 -4.9230971 2
#> 4 1 -2.10 -13.20 1.0407520 1.2675953 -1.059248 -11.9324047 1
#> 5 1 -1.70 -4.30 2.7724944 0.4346216 1.072494 -3.8653784 1
#> 6 1 -6.90 -1.55 4.7069648 2.0616965 -2.193035 0.5116965 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4520 -38350 8750
#> initial value 998.131940
#> iter 2 value 819.331327
#> iter 3 value 817.030177
#> iter 4 value 814.047611
#> iter 5 value 763.865603
#> iter 6 value 754.277764
#> iter 7 value 752.734175
#> iter 8 value 752.711408
#> iter 9 value 752.711280
#> iter 10 value 752.711038
#> iter 10 value 752.711038
#> iter 10 value 752.711027
#> final value 752.711027
#> converged
#> This is Run number 393
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.8468311 2.7825943 -1.503169 -9.417406 1
#> 2 1 -6.20 -3.90 -0.5020686 0.3033119 -6.702069 -3.596688 2
#> 3 1 -14.20 -5.80 0.8529034 0.8596187 -13.347097 -4.940381 2
#> 4 1 -2.10 -13.20 0.6413661 0.4556450 -1.458634 -12.744355 1
#> 5 1 -1.70 -4.30 -0.2418135 1.0630302 -1.941814 -3.236970 1
#> 6 1 -6.90 -1.55 4.4775389 -0.7780850 -2.422461 -2.328085 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3400 -36575 8400
#> initial value 998.131940
#> iter 2 value 844.787450
#> iter 3 value 840.738278
#> iter 4 value 834.450526
#> iter 5 value 778.847302
#> iter 6 value 769.690712
#> iter 7 value 768.022398
#> iter 8 value 767.999817
#> iter 9 value 767.999796
#> iter 10 value 767.999767
#> iter 11 value 767.999755
#> iter 11 value 767.999752
#> iter 11 value 767.999752
#> final value 767.999752
#> converged
#> This is Run number 394
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 0.5740885 -1.01289205 -1.775911 -13.2128921 1
#> 2 1 -6.20 -3.90 3.3634263 0.54912452 -2.836574 -3.3508755 1
#> 3 1 -14.20 -5.80 -0.6710949 -0.01873935 -14.871095 -5.8187393 2
#> 4 1 -2.10 -13.20 0.2721623 0.26094431 -1.827838 -12.9390557 1
#> 5 1 -1.70 -4.30 -0.9094226 2.86411616 -2.609423 -1.4358838 2
#> 6 1 -6.90 -1.55 1.9269930 1.27023020 -4.973007 -0.2797698 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5640 -39525 7050
#> initial value 998.131940
#> iter 2 value 812.356210
#> iter 3 value 810.037455
#> iter 4 value 807.799660
#> iter 5 value 765.223948
#> iter 6 value 754.903046
#> iter 7 value 753.485551
#> iter 8 value 753.454456
#> iter 9 value 753.454134
#> iter 10 value 753.453914
#> iter 10 value 753.453914
#> iter 11 value 753.453879
#> iter 12 value 753.453826
#> iter 12 value 753.453826
#> iter 12 value 753.453824
#> final value 753.453824
#> converged
#> This is Run number 395
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.33920371 8.0540122 -2.6892037 -4.145988 1
#> 2 1 -6.20 -3.90 -0.10092657 -0.1459024 -6.3009266 -4.045902 2
#> 3 1 -14.20 -5.80 0.60128564 -0.3050105 -13.5987144 -6.105011 2
#> 4 1 -2.10 -13.20 -0.09838651 2.0532490 -2.1983865 -11.146751 1
#> 5 1 -1.70 -4.30 1.98073719 0.8760067 0.2807372 -3.423993 1
#> 6 1 -6.90 -1.55 2.36280382 0.5466067 -4.5371962 -1.003393 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4460 -36950 8275
#> initial value 998.131940
#> iter 2 value 841.793511
#> iter 3 value 826.666629
#> iter 4 value 825.207725
#> iter 5 value 783.942900
#> iter 6 value 775.817520
#> iter 7 value 774.589436
#> iter 8 value 774.539850
#> iter 9 value 774.538962
#> iter 10 value 774.538805
#> iter 11 value 774.538646
#> iter 12 value 774.538517
#> iter 12 value 774.538517
#> iter 12 value 774.538517
#> final value 774.538517
#> converged
#> This is Run number 396
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -0.2792462 1.44365076 -2.6292462 -10.7563492 1
#> 2 1 -6.20 -3.90 2.3920830 0.47338210 -3.8079170 -3.4266179 2
#> 3 1 -14.20 -5.80 0.4421800 -1.43053370 -13.7578200 -7.2305337 2
#> 4 1 -2.10 -13.20 0.2942482 -0.03396997 -1.8057518 -13.2339700 1
#> 5 1 -1.70 -4.30 1.9065882 0.18394331 0.2065882 -4.1160567 1
#> 6 1 -6.90 -1.55 0.5166763 0.91151409 -6.3833237 -0.6384859 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4340 -36450 7875
#> initial value 998.131940
#> iter 2 value 850.728706
#> iter 3 value 836.645801
#> iter 4 value 834.787304
#> iter 5 value 791.906899
#> iter 6 value 783.861315
#> iter 7 value 782.429809
#> iter 8 value 782.375528
#> iter 9 value 782.374662
#> iter 10 value 782.374533
#> iter 11 value 782.374415
#> iter 12 value 782.374317
#> iter 12 value 782.374317
#> iter 12 value 782.374317
#> final value 782.374317
#> converged
#> This is Run number 397
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 1.24679274 -0.94695837 -1.103207 -13.146958 1
#> 2 1 -6.20 -3.90 -1.53843329 -0.91023924 -7.738433 -4.810239 2
#> 3 1 -14.20 -5.80 -0.60267665 1.88883708 -14.802677 -3.911163 2
#> 4 1 -2.10 -13.20 -0.74050486 -0.05015285 -2.840505 -13.250153 1
#> 5 1 -1.70 -4.30 -0.06687904 3.18949453 -1.766879 -1.110505 2
#> 6 1 -6.90 -1.55 -1.03717391 -0.49589979 -7.937174 -2.045900 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4940 -37800 7950
#> initial value 998.131940
#> iter 2 value 832.438119
#> iter 3 value 832.023035
#> iter 4 value 830.135806
#> iter 5 value 779.620434
#> iter 6 value 769.903510
#> iter 7 value 768.408998
#> iter 8 value 768.381973
#> iter 9 value 768.381526
#> iter 10 value 768.381403
#> iter 11 value 768.381362
#> iter 12 value 768.381244
#> iter 12 value 768.381244
#> iter 12 value 768.381244
#> final value 768.381244
#> converged
#> This is Run number 398
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 -1.4116950 2.44868539 -3.761695 -9.7513146 1
#> 2 1 -6.20 -3.90 1.2726209 0.01469254 -4.927379 -3.8853075 2
#> 3 1 -14.20 -5.80 -0.4593436 2.39422218 -14.659344 -3.4057778 2
#> 4 1 -2.10 -13.20 1.2404560 0.17449694 -0.859544 -13.0255031 1
#> 5 1 -1.70 -4.30 3.3835869 2.06900874 1.683587 -2.2309913 1
#> 6 1 -6.90 -1.55 -0.2572011 1.75339580 -7.157201 0.2033958 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4700 -39550 8425
#> initial value 998.131940
#> iter 2 value 803.705574
#> iter 3 value 798.639544
#> iter 4 value 794.486155
#> iter 5 value 749.681730
#> iter 6 value 739.889408
#> iter 7 value 738.424001
#> iter 8 value 738.400011
#> iter 9 value 738.399836
#> iter 10 value 738.399621
#> iter 11 value 738.399591
#> iter 12 value 738.399519
#> iter 12 value 738.399519
#> iter 12 value 738.399519
#> final value 738.399519
#> converged
#> This is Run number 399
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 5.1707790 1.06931489 2.8207790 -11.130685 1
#> 2 1 -6.20 -3.90 -0.8109065 1.18764035 -7.0109065 -2.712360 2
#> 3 1 -14.20 -5.80 -0.6439281 0.05275428 -14.8439281 -5.747246 2
#> 4 1 -2.10 -13.20 -1.1308746 0.29903660 -3.2308746 -12.900963 1
#> 5 1 -1.70 -4.30 1.9340263 0.87969791 0.2340263 -3.420302 1
#> 6 1 -6.90 -1.55 2.0264300 3.65774324 -4.8735700 2.107743 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4820 -39650 9050
#> initial value 998.131940
#> iter 2 value 797.991341
#> iter 3 value 793.832846
#> iter 4 value 791.165113
#> iter 5 value 745.268243
#> iter 6 value 735.667264
#> iter 7 value 734.150649
#> iter 8 value 734.125104
#> iter 9 value 734.124790
#> iter 10 value 734.124635
#> iter 11 value 734.124569
#> iter 12 value 734.124538
#> iter 12 value 734.124538
#> iter 12 value 734.124538
#> final value 734.124538
#> converged
#> This is Run number 400
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 12 60 25 0 20 200 100 1
#> 2 1 16 20 100 50 40 50 0 1
#> 3 1 17 20 200 0 80 100 100 1
#> 4 1 25 60 50 100 20 200 50 1
#> 5 1 29 20 50 100 80 50 0 1
#> 6 1 32 40 100 25 80 25 50 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -2.35 -12.20 3.5472686 -0.43690816 1.197269 -12.636908 1
#> 2 1 -6.20 -3.90 1.6787391 -0.02663212 -4.521261 -3.926632 2
#> 3 1 -14.20 -5.80 0.3494467 -0.63970916 -13.850553 -6.439709 2
#> 4 1 -2.10 -13.20 -0.8775397 0.59397960 -2.977540 -12.606020 1
#> 5 1 -1.70 -4.30 -1.2042629 0.47372007 -2.904263 -3.826280 1
#> 6 1 -6.90 -1.55 1.4858822 -1.38827550 -5.414118 -2.938276 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5640 -38450 6950
#> initial value 998.131940
#> iter 2 value 828.878564
#> iter 3 value 828.297326
#> iter 4 value 826.887151
#> iter 5 value 780.708037
#> iter 6 value 770.599433
#> iter 7 value 769.073964
#> iter 8 value 769.036883
#> iter 9 value 769.036691
#> iter 10 value 769.036170
#> iter 11 value 769.036150
#> iter 12 value 769.036066
#> iter 12 value 769.036066
#> iter 12 value 769.036066
#> final value 769.036066
#> converged
#>
#>
#> ================ ==== === ===== ==== ====== ===== ===== ===== ===== ======== ===
#> \ vars n mean sd median min max range skew kurtosis se
#> ================ ==== === ===== ==== ====== ===== ===== ===== ===== ======== ===
#> est_bpreis 1 400 -0.01 0.00 -0.01 -0.01 0.00 0.01 -0.23 0.02 0
#> est_blade 2 400 -0.01 0.00 -0.01 -0.02 -0.01 0.00 -0.07 -0.14 0
#> est_bwarte 3 400 0.01 0.00 0.01 0.00 0.01 0.01 0.14 0.02 0
#> rob_pval0_bpreis 4 400 0.00 0.01 0.00 0.00 0.10 0.10 6.48 50.41 0
#> rob_pval0_blade 5 400 0.00 0.00 0.00 0.00 0.00 0.00 NaN NaN 0
#> rob_pval0_bwarte 6 400 0.00 0.00 0.00 0.00 0.02 0.02 7.02 54.24 0
#> ================ ==== === ===== ==== ====== ===== ===== ===== ===== ======== ===
#>
#> FALSE TRUE
#> 1.5 98.5
#> 'simple' is deprecated and will be removed in the future. Use 'exact' instead.
#> bcoeff_lookup already exists; skipping modification.
#> Utility function used in simulation, ie the true utility:
#>
#> $u1
#> $u1$v1
#> V.1 ~ bpreis * alt1.x1 + blade * alt1.x2 + bwarte * alt1.x3
#> <environment: 0x5cc5fe6cc2d8>
#>
#> $u1$v2
#> V.2 ~ bpreis * alt2.x1 + blade * alt2.x2 + bwarte * alt2.x3
#> <environment: 0x5cc5fd8b4648>
#>
#>
#> $u2
#> $u2$v1
#> V.1 ~ bpreis * alt1.x1
#> <environment: 0x5cc5fa36b508>
#>
#> $u2$v2
#> V.2 ~ bpreis * alt2.x1
#> <environment: 0x5cc5fac617c0>
#> 'destype' is deprecated. Please use 'designtype' instead.
#> New names:
#>
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.5469877 0.2652209 -3.7530123 -1.434779 2
#> 2 1 -1.35 -13.20 0.2921204 0.3512947 -1.0578796 -12.848705 1
#> 3 1 -2.05 -14.20 -0.9242458 -0.4746341 -2.9742458 -14.674634 1
#> 4 1 -1.55 -3.10 3.7040281 0.5012953 2.1540281 -2.598705 1
#> 5 1 -1.90 -3.60 2.4394138 1.9346467 0.5394138 -1.665353 1
#> 6 1 -13.70 -1.85 -0.3828294 0.1145080 -14.0828294 -1.735492 2
#>
#>
#> Transformed utility function (type: simple ):
#> [1] "U_1 = @bpreis * $alt1_x1 + @blade * $alt1_x2 + @bwarte * $alt1_x3 ;U_2 = @bpreis * $alt2_x1 + @blade * $alt2_x2 + @bwarte * $alt2_x3 ;"
#> This is Run number 1
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.05382619 -1.1576939 -4.2461738 -2.8576939 2
#> 2 1 -1.35 -13.20 0.76693153 1.5168406 -0.5830685 -11.6831594 1
#> 3 1 -2.05 -14.20 2.59102744 -0.3493519 0.5410274 -14.5493519 1
#> 4 1 -1.55 -3.10 0.03210815 -0.3090358 -1.5178918 -3.4090358 1
#> 5 1 -1.90 -3.60 1.36618213 0.8593138 -0.5338179 -2.7406862 1
#> 6 1 -13.70 -1.85 3.12215769 1.0586479 -10.5778423 -0.7913521 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4000 -39225 10100
#> initial value 998.131940
#> iter 2 value 781.559570
#> iter 3 value 762.015998
#> iter 4 value 759.985798
#> iter 5 value 730.675751
#> iter 6 value 724.225867
#> iter 7 value 723.478520
#> iter 8 value 723.439672
#> iter 9 value 723.439589
#> iter 10 value 723.439504
#> iter 11 value 723.439432
#> iter 12 value 723.439402
#> iter 12 value 723.439402
#> iter 12 value 723.439402
#> final value 723.439402
#> converged
#> This is Run number 2
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.2006406 0.4494358 -3.099359 -1.2505642 2
#> 2 1 -1.35 -13.20 -0.5747190 2.4358704 -1.924719 -10.7641296 1
#> 3 1 -2.05 -14.20 -0.8671666 -0.3042701 -2.917167 -14.5042701 1
#> 4 1 -1.55 -3.10 -0.5824677 1.4327064 -2.132468 -1.6672936 2
#> 5 1 -1.90 -3.60 -0.4600896 1.6003239 -2.360090 -1.9996761 2
#> 6 1 -13.70 -1.85 1.9933071 2.1605038 -11.706693 0.3105038 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4060 -39575 9450
#> initial value 998.131940
#> iter 2 value 780.858389
#> iter 3 value 763.086061
#> iter 4 value 759.951387
#> iter 5 value 730.626253
#> iter 6 value 723.805360
#> iter 7 value 722.935724
#> iter 8 value 722.892921
#> iter 9 value 722.892877
#> iter 9 value 722.892872
#> iter 9 value 722.892872
#> final value 722.892872
#> converged
#> This is Run number 3
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.1256750 -0.4726284 -4.425675e+00 -2.172628 2
#> 2 1 -1.35 -13.20 -0.4661533 0.4526024 -1.816153e+00 -12.747398 1
#> 3 1 -2.05 -14.20 0.6240372 0.5070144 -1.425963e+00 -13.692986 1
#> 4 1 -1.55 -3.10 1.1065793 1.1722847 -4.434207e-01 -1.927715 1
#> 5 1 -1.90 -3.60 1.9004657 -0.7194325 4.657214e-04 -4.319433 1
#> 6 1 -13.70 -1.85 2.2125980 -0.2502288 -1.148740e+01 -2.100229 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4120 -37850 9425
#> initial value 998.131940
#> iter 2 value 807.473380
#> iter 3 value 790.631616
#> iter 4 value 789.210898
#> iter 5 value 757.294623
#> iter 6 value 750.456315
#> iter 7 value 749.624246
#> iter 8 value 749.595905
#> iter 9 value 749.595724
#> iter 10 value 749.595698
#> iter 11 value 749.595667
#> iter 12 value 749.595653
#> iter 12 value 749.595653
#> iter 12 value 749.595653
#> final value 749.595653
#> converged
#> This is Run number 4
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 6.5375608 0.4506559 2.2375608 -1.2493441 1
#> 2 1 -1.35 -13.20 0.5217834 0.8686365 -0.8282166 -12.3313635 1
#> 3 1 -2.05 -14.20 1.7839714 1.8723842 -0.2660286 -12.3276158 1
#> 4 1 -1.55 -3.10 -0.4118957 1.6275816 -1.9618957 -1.4724184 2
#> 5 1 -1.90 -3.60 1.6989791 -0.7391706 -0.2010209 -4.3391706 1
#> 6 1 -13.70 -1.85 0.8800060 1.1789354 -12.8199940 -0.6710646 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2800 -36525 10950
#> initial value 998.131940
#> iter 2 value 812.926616
#> iter 3 value 788.996107
#> iter 4 value 786.756647
#> iter 5 value 752.039350
#> iter 6 value 746.404596
#> iter 7 value 745.792413
#> iter 8 value 745.768708
#> iter 9 value 745.768653
#> iter 10 value 745.768609
#> iter 10 value 745.768607
#> iter 10 value 745.768598
#> final value 745.768598
#> converged
#> This is Run number 5
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.3992615 2.8048256 -1.9007385 1.104826 2
#> 2 1 -1.35 -13.20 1.1224635 1.1048061 -0.2275365 -12.095194 1
#> 3 1 -2.05 -14.20 -0.2354874 0.6778520 -2.2854874 -13.522148 1
#> 4 1 -1.55 -3.10 -0.1190669 1.4370336 -1.6690669 -1.662966 2
#> 5 1 -1.90 -3.60 0.7799506 -0.5826479 -1.1200494 -4.182648 1
#> 6 1 -13.70 -1.85 0.6110906 0.7376301 -13.0889094 -1.112370 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3500 -37175 9125
#> initial value 998.131940
#> iter 2 value 818.684405
#> iter 3 value 801.486201
#> iter 4 value 798.610658
#> iter 5 value 763.522267
#> iter 6 value 756.673851
#> iter 7 value 755.721196
#> iter 8 value 755.693419
#> iter 9 value 755.693325
#> iter 9 value 755.693322
#> iter 9 value 755.693321
#> final value 755.693321
#> converged
#> This is Run number 6
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.2449917 0.4252392 -3.0550083 -1.2747608 2
#> 2 1 -1.35 -13.20 0.6133298 2.4682248 -0.7366702 -10.7317752 1
#> 3 1 -2.05 -14.20 -0.1924058 0.5484934 -2.2424058 -13.6515066 1
#> 4 1 -1.55 -3.10 0.9109317 0.3887122 -0.6390683 -2.7112878 1
#> 5 1 -1.90 -3.60 -0.3777203 0.7758778 -2.2777203 -2.8241222 1
#> 6 1 -13.70 -1.85 -0.2219318 0.8996832 -13.9219318 -0.9503168 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3360 -36825 11325
#> initial value 998.131940
#> iter 2 value 806.428137
#> iter 3 value 782.456171
#> iter 4 value 781.751279
#> iter 5 value 749.443473
#> iter 6 value 743.919927
#> iter 7 value 743.404982
#> iter 8 value 743.384148
#> iter 9 value 743.384072
#> iter 10 value 743.383854
#> iter 11 value 743.383842
#> iter 12 value 743.383773
#> iter 12 value 743.383773
#> iter 12 value 743.383773
#> final value 743.383773
#> converged
#> This is Run number 7
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.2555138 0.48260313 -4.04448618 -1.217397 2
#> 2 1 -1.35 -13.20 1.3104744 -0.05915726 -0.03952559 -13.259157 1
#> 3 1 -2.05 -14.20 -0.3867722 -0.53916194 -2.43677224 -14.739162 1
#> 4 1 -1.55 -3.10 0.7135984 0.29726860 -0.83640160 -2.802731 1
#> 5 1 -1.90 -3.60 0.8023801 0.60891523 -1.09761988 -2.991085 1
#> 6 1 -13.70 -1.85 3.7663395 0.62562153 -9.93366054 -1.224378 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2900 -36500 10300
#> initial value 998.131940
#> iter 2 value 818.632506
#> iter 3 value 796.991928
#> iter 4 value 794.338766
#> iter 5 value 758.662900
#> iter 6 value 752.627218
#> iter 7 value 751.909770
#> iter 8 value 751.886009
#> iter 9 value 751.885946
#> iter 9 value 751.885937
#> iter 9 value 751.885937
#> final value 751.885937
#> converged
#> This is Run number 8
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -1.0726274 0.1560654 -5.3726274 -1.5439346 2
#> 2 1 -1.35 -13.20 0.8907068 -0.5979800 -0.4592932 -13.7979800 1
#> 3 1 -2.05 -14.20 -1.3929626 0.4125810 -3.4429626 -13.7874190 1
#> 4 1 -1.55 -3.10 1.1518793 -0.3477345 -0.3981207 -3.4477345 1
#> 5 1 -1.90 -3.60 1.5967332 -0.1425273 -0.3032668 -3.7425273 1
#> 6 1 -13.70 -1.85 0.4373354 1.0375641 -13.2626646 -0.8124359 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4340 -37550 9325
#> initial value 998.131940
#> iter 2 value 812.634378
#> iter 3 value 796.609329
#> iter 4 value 795.783434
#> iter 5 value 763.678982
#> iter 6 value 756.816852
#> iter 7 value 755.989514
#> iter 8 value 755.963584
#> iter 9 value 755.963372
#> iter 10 value 755.963344
#> iter 11 value 755.963294
#> iter 12 value 755.963254
#> iter 12 value 755.963254
#> iter 12 value 755.963254
#> final value 755.963254
#> converged
#> This is Run number 9
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.5994028 -0.07374626 -2.7005972 -1.7737463 2
#> 2 1 -1.35 -13.20 0.8996715 1.78931885 -0.4503285 -11.4106812 1
#> 3 1 -2.05 -14.20 -0.0330885 -0.43946402 -2.0830885 -14.6394640 1
#> 4 1 -1.55 -3.10 1.3529570 0.25326949 -0.1970430 -2.8467305 1
#> 5 1 -1.90 -3.60 0.9909023 1.03056192 -0.9090977 -2.5694381 1
#> 6 1 -13.70 -1.85 3.2654966 1.16031656 -10.4345034 -0.6896834 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4720 -36025 8475
#> initial value 998.131940
#> iter 2 value 839.347079
#> iter 3 value 826.646741
#> iter 4 value 826.436137
#> iter 5 value 791.362908
#> iter 6 value 784.577440
#> iter 7 value 783.556475
#> iter 8 value 783.532403
#> iter 9 value 783.532222
#> iter 10 value 783.532175
#> iter 11 value 783.532104
#> iter 12 value 783.532065
#> iter 12 value 783.532065
#> iter 12 value 783.532065
#> final value 783.532065
#> converged
#> This is Run number 10
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.0821378 -0.4327229 -3.2178622 -2.132723 2
#> 2 1 -1.35 -13.20 1.0755924 0.2678658 -0.2744076 -12.932134 1
#> 3 1 -2.05 -14.20 2.9433383 0.1578782 0.8933383 -14.042122 1
#> 4 1 -1.55 -3.10 0.6620746 0.8101378 -0.8879254 -2.289862 1
#> 5 1 -1.90 -3.60 -0.7451380 -0.2154410 -2.6451380 -3.815441 1
#> 6 1 -13.70 -1.85 -0.9069444 -0.4052363 -14.6069444 -2.255236 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3400 -35450 9450
#> initial value 998.131940
#> iter 2 value 839.443052
#> iter 3 value 821.927230
#> iter 4 value 820.481429
#> iter 5 value 783.789564
#> iter 6 value 777.566750
#> iter 7 value 776.764495
#> iter 8 value 776.745718
#> iter 9 value 776.745589
#> iter 10 value 776.745571
#> iter 11 value 776.745551
#> iter 12 value 776.745537
#> iter 12 value 776.745537
#> iter 12 value 776.745537
#> final value 776.745537
#> converged
#> This is Run number 11
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.4343189 0.5238402 -4.7343189 -1.1761598 2
#> 2 1 -1.35 -13.20 -0.2142344 0.2281255 -1.5642344 -12.9718745 1
#> 3 1 -2.05 -14.20 0.2002572 1.0697175 -1.8497428 -13.1302825 1
#> 4 1 -1.55 -3.10 1.1721299 3.4586616 -0.3778701 0.3586616 2
#> 5 1 -1.90 -3.60 -0.4219491 2.5889815 -2.3219491 -1.0110185 2
#> 6 1 -13.70 -1.85 -0.6229243 1.2022856 -14.3229243 -0.6477144 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3800 -37900 10250
#> initial value 998.131940
#> iter 2 value 800.368017
#> iter 3 value 780.456495
#> iter 4 value 779.088736
#> iter 5 value 747.552954
#> iter 6 value 741.201449
#> iter 7 value 740.512979
#> iter 8 value 740.485063
#> iter 9 value 740.484960
#> iter 10 value 740.484862
#> iter 10 value 740.484862
#> iter 11 value 740.484846
#> iter 12 value 740.484830
#> iter 12 value 740.484830
#> iter 12 value 740.484828
#> final value 740.484828
#> converged
#> This is Run number 12
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.03845864 -1.0242932 -4.338459 -2.724293 2
#> 2 1 -1.35 -13.20 0.20712175 0.8574136 -1.142878 -12.342586 1
#> 3 1 -2.05 -14.20 -0.28291500 -0.3659374 -2.332915 -14.565937 1
#> 4 1 -1.55 -3.10 0.20198238 1.1661545 -1.348018 -1.933846 1
#> 5 1 -1.90 -3.60 -0.25581810 0.1341704 -2.155818 -3.465830 1
#> 6 1 -13.70 -1.85 -0.16492800 -0.2039991 -13.864928 -2.053999 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4400 -38250 9250
#> initial value 998.131940
#> iter 2 value 802.946452
#> iter 3 value 786.998341
#> iter 4 value 785.811731
#> iter 5 value 754.904472
#> iter 6 value 747.906621
#> iter 7 value 747.057143
#> iter 8 value 747.027188
#> iter 9 value 747.026982
#> iter 10 value 747.026949
#> iter 11 value 747.026911
#> iter 12 value 747.026893
#> iter 12 value 747.026893
#> iter 12 value 747.026893
#> final value 747.026893
#> converged
#> This is Run number 13
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.0291596 -0.5846641 -2.270840 -2.2846641 1
#> 2 1 -1.35 -13.20 -0.3833716 2.1357967 -1.733372 -11.0642033 1
#> 3 1 -2.05 -14.20 0.5206070 2.0885141 -1.529393 -12.1114859 1
#> 4 1 -1.55 -3.10 -0.2029468 1.1698324 -1.752947 -1.9301676 1
#> 5 1 -1.90 -3.60 0.2870776 2.6009628 -1.612922 -0.9990372 2
#> 6 1 -13.70 -1.85 1.7265487 3.1056215 -11.973451 1.2556215 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3560 -35950 9025
#> initial value 998.131940
#> iter 2 value 836.091780
#> iter 3 value 819.853676
#> iter 4 value 818.041525
#> iter 5 value 781.550007
#> iter 6 value 774.986724
#> iter 7 value 774.052380
#> iter 8 value 774.029432
#> iter 9 value 774.029283
#> iter 10 value 774.029270
#> iter 10 value 774.029261
#> iter 10 value 774.029257
#> final value 774.029257
#> converged
#> This is Run number 14
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.05670603 -0.0417180 -4.2432940 -1.74171800 2
#> 2 1 -1.35 -13.20 1.11925682 0.8151164 -0.2307432 -12.38488360 1
#> 3 1 -2.05 -14.20 -1.20959017 -0.9876507 -3.2595902 -15.18765072 1
#> 4 1 -1.55 -3.10 -0.97234774 3.0305437 -2.5223477 -0.06945633 2
#> 5 1 -1.90 -3.60 0.98103741 1.0300973 -0.9189626 -2.56990272 1
#> 6 1 -13.70 -1.85 -1.18661479 1.6845675 -14.8866148 -0.16543248 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4400 -37325 7800
#> initial value 998.131940
#> iter 2 value 825.651983
#> iter 3 value 813.511114
#> iter 4 value 811.461807
#> iter 5 value 777.236391
#> iter 6 value 769.845200
#> iter 7 value 768.524768
#> iter 8 value 768.487051
#> iter 9 value 768.486810
#> iter 9 value 768.486800
#> iter 9 value 768.486796
#> final value 768.486796
#> converged
#> This is Run number 15
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.4176024 -1.0549947 -2.8823976 -2.754995 2
#> 2 1 -1.35 -13.20 -0.1961432 0.7609769 -1.5461432 -12.439023 1
#> 3 1 -2.05 -14.20 3.1253109 -0.8694696 1.0753109 -15.069470 1
#> 4 1 -1.55 -3.10 -0.8602572 -0.9100339 -2.4102572 -4.010034 1
#> 5 1 -1.90 -3.60 2.3592684 -0.4520484 0.4592684 -4.052048 1
#> 6 1 -13.70 -1.85 -1.1008318 -0.6478586 -14.8008318 -2.497859 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4220 -37750 8300
#> initial value 998.131940
#> iter 2 value 816.469947
#> iter 3 value 802.674878
#> iter 4 value 800.331644
#> iter 5 value 767.031857
#> iter 6 value 759.698868
#> iter 7 value 758.552459
#> iter 8 value 758.518494
#> iter 9 value 758.518296
#> iter 9 value 758.518286
#> iter 9 value 758.518281
#> final value 758.518281
#> converged
#> This is Run number 16
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.74775938 1.60437403 -3.5522406 -0.09562597 2
#> 2 1 -1.35 -13.20 0.94277891 1.65583759 -0.4072211 -11.54416241 1
#> 3 1 -2.05 -14.20 -0.26510201 1.76132796 -2.3151020 -12.43867204 1
#> 4 1 -1.55 -3.10 0.05695857 -0.97163559 -1.4930414 -4.07163559 1
#> 5 1 -1.90 -3.60 2.74283715 0.02506754 0.8428371 -3.57493246 1
#> 6 1 -13.70 -1.85 2.83456150 0.52320700 -10.8654385 -1.32679300 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3300 -36875 10200
#> initial value 998.131940
#> iter 2 value 814.836257
#> iter 3 value 794.337623
#> iter 4 value 792.351638
#> iter 5 value 758.196052
#> iter 6 value 751.998806
#> iter 7 value 751.286202
#> iter 8 value 751.262095
#> iter 9 value 751.261999
#> iter 10 value 751.261971
#> iter 11 value 751.261953
#> iter 11 value 751.261952
#> iter 11 value 751.261952
#> final value 751.261952
#> converged
#> This is Run number 17
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.1014781 0.5771368 -3.1985219 -1.122863 2
#> 2 1 -1.35 -13.20 -1.2035142 0.9648163 -2.5535142 -12.235184 1
#> 3 1 -2.05 -14.20 -0.4387666 2.6161337 -2.4887666 -11.583866 1
#> 4 1 -1.55 -3.10 0.7195539 0.6302729 -0.8304461 -2.469727 1
#> 5 1 -1.90 -3.60 3.6492326 1.4374621 1.7492326 -2.162538 1
#> 6 1 -13.70 -1.85 0.2585508 0.7378242 -13.4414492 -1.112176 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4020 -38125 10125
#> initial value 998.131940
#> iter 2 value 798.185220
#> iter 3 value 779.037081
#> iter 4 value 777.933526
#> iter 5 value 747.036587
#> iter 6 value 740.565625
#> iter 7 value 739.872910
#> iter 8 value 739.844762
#> iter 9 value 739.844648
#> iter 10 value 739.844529
#> iter 10 value 739.844528
#> iter 11 value 739.844515
#> iter 12 value 739.844487
#> iter 12 value 739.844487
#> iter 12 value 739.844484
#> final value 739.844484
#> converged
#> This is Run number 18
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.90132928 0.92807034 -5.2013293 -0.7719297 2
#> 2 1 -1.35 -13.20 1.99373216 0.70347330 0.6437322 -12.4965267 1
#> 3 1 -2.05 -14.20 -0.04108362 0.31443474 -2.0910836 -13.8855653 1
#> 4 1 -1.55 -3.10 2.20405209 2.21221629 0.6540521 -0.8877837 1
#> 5 1 -1.90 -3.60 -1.13964535 2.27876968 -3.0396453 -1.3212303 2
#> 6 1 -13.70 -1.85 0.46257169 0.04921439 -13.2374283 -1.8007856 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3780 -38225 9775
#> initial value 998.131940
#> iter 2 value 799.140832
#> iter 3 value 780.426398
#> iter 4 value 778.163969
#> iter 5 value 746.426425
#> iter 6 value 739.781662
#> iter 7 value 738.980619
#> iter 8 value 738.948623
#> iter 9 value 738.948534
#> iter 10 value 738.948505
#> iter 10 value 738.948504
#> iter 10 value 738.948501
#> final value 738.948501
#> converged
#> This is Run number 19
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -1.0741845 0.3498269 -5.3741845 -1.3501731 2
#> 2 1 -1.35 -13.20 2.5215430 -0.2210067 1.1715430 -13.4210067 1
#> 3 1 -2.05 -14.20 0.5427005 0.5586853 -1.5072995 -13.6413147 1
#> 4 1 -1.55 -3.10 0.3295907 -0.1709370 -1.2204093 -3.2709370 1
#> 5 1 -1.90 -3.60 1.5182468 -1.2329223 -0.3817532 -4.8329223 1
#> 6 1 -13.70 -1.85 0.3255375 0.9404351 -13.3744625 -0.9095649 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3840 -36400 9625
#> initial value 998.131940
#> iter 2 value 826.176194
#> iter 3 value 808.736934
#> iter 4 value 807.787185
#> iter 5 value 773.479182
#> iter 6 value 767.037814
#> iter 7 value 766.272424
#> iter 8 value 766.251751
#> iter 9 value 766.251592
#> iter 10 value 766.251572
#> iter 11 value 766.251529
#> iter 12 value 766.251493
#> iter 12 value 766.251493
#> iter 12 value 766.251493
#> final value 766.251493
#> converged
#> This is Run number 20
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.3427212 0.94092748 -2.9572788 -0.7590725 2
#> 2 1 -1.35 -13.20 0.4219547 -0.76179453 -0.9280453 -13.9617945 1
#> 3 1 -2.05 -14.20 -0.8931682 0.07232921 -2.9431682 -14.1276708 1
#> 4 1 -1.55 -3.10 0.3588642 0.55020756 -1.1911358 -2.5497924 1
#> 5 1 -1.90 -3.60 -1.5593097 -0.75182061 -3.4593097 -4.3518206 1
#> 6 1 -13.70 -1.85 0.1738337 -0.08602991 -13.5261663 -1.9360299 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3380 -36450 9325
#> initial value 998.131940
#> iter 2 value 827.168271
#> iter 3 value 809.503327
#> iter 4 value 807.157004
#> iter 5 value 771.210739
#> iter 6 value 764.635653
#> iter 7 value 763.747527
#> iter 8 value 763.723621
#> iter 9 value 763.723500
#> iter 9 value 763.723493
#> iter 9 value 763.723490
#> final value 763.723490
#> converged
#> This is Run number 21
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.4469499 -1.0236290 -4.746950 -2.723629 2
#> 2 1 -1.35 -13.20 0.0189455 -0.7125208 -1.331055 -13.912521 1
#> 3 1 -2.05 -14.20 -0.1293122 -0.1225981 -2.179312 -14.322598 1
#> 4 1 -1.55 -3.10 -1.4340205 1.4286238 -2.984021 -1.671376 2
#> 5 1 -1.90 -3.60 0.6817066 1.0093199 -1.218293 -2.590680 1
#> 6 1 -13.70 -1.85 1.0273579 3.1448692 -12.672642 1.294869 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3840 -36925 9050
#> initial value 998.131940
#> iter 2 value 823.036974
#> iter 3 value 806.949262
#> iter 4 value 805.095589
#> iter 5 value 770.651683
#> iter 6 value 763.828673
#> iter 7 value 762.884364
#> iter 8 value 762.857683
#> iter 9 value 762.857502
#> iter 10 value 762.857488
#> iter 10 value 762.857479
#> iter 10 value 762.857475
#> final value 762.857475
#> converged
#> This is Run number 22
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.1948125 -0.3770963 -3.1051875 -2.077096 2
#> 2 1 -1.35 -13.20 0.2782994 -0.1792153 -1.0717006 -13.379215 1
#> 3 1 -2.05 -14.20 -0.1755772 1.3730510 -2.2255772 -12.826949 1
#> 4 1 -1.55 -3.10 0.2894350 -0.3640023 -1.2605650 -3.464002 1
#> 5 1 -1.90 -3.60 1.5714447 -0.4094092 -0.3285553 -4.009409 1
#> 6 1 -13.70 -1.85 3.6052614 0.1353600 -10.0947386 -1.714640 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4540 -36900 9275
#> initial value 998.131940
#> iter 2 value 822.194963
#> iter 3 value 806.853540
#> iter 4 value 806.587280
#> iter 5 value 773.650111
#> iter 6 value 766.876678
#> iter 7 value 766.075309
#> iter 8 value 766.053755
#> iter 9 value 766.053569
#> iter 9 value 766.053558
#> iter 9 value 766.053558
#> final value 766.053558
#> converged
#> This is Run number 23
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.153599485 1.8027130 -4.1464005 0.102713 2
#> 2 1 -1.35 -13.20 0.376221640 -0.7084627 -0.9737784 -13.908463 1
#> 3 1 -2.05 -14.20 1.143438842 0.6304007 -0.9065612 -13.569599 1
#> 4 1 -1.55 -3.10 0.936983308 0.1470791 -0.6130167 -2.952921 1
#> 5 1 -1.90 -3.60 1.635985632 0.1657513 -0.2640144 -3.434249 1
#> 6 1 -13.70 -1.85 0.007804165 -0.3435351 -13.6921958 -2.193535 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3080 -35350 9675
#> initial value 998.131940
#> iter 2 value 838.690048
#> iter 3 value 819.849454
#> iter 4 value 817.979943
#> iter 5 value 780.687387
#> iter 6 value 774.600794
#> iter 7 value 773.835538
#> iter 8 value 773.817420
#> iter 9 value 773.817316
#> iter 9 value 773.817305
#> iter 9 value 773.817300
#> final value 773.817300
#> converged
#> This is Run number 24
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -1.7582394 1.1361467 -6.0582394 -0.5638533 2
#> 2 1 -1.35 -13.20 1.7474992 -0.4923708 0.3974992 -13.6923708 1
#> 3 1 -2.05 -14.20 1.2045757 0.7192137 -0.8454243 -13.4807863 1
#> 4 1 -1.55 -3.10 -0.3037345 -0.5960037 -1.8537345 -3.6960037 1
#> 5 1 -1.90 -3.60 2.8327165 0.8032525 0.9327165 -2.7967475 1
#> 6 1 -13.70 -1.85 -0.2459209 1.0799993 -13.9459209 -0.7700007 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3040 -37350 10700
#> initial value 998.131940
#> iter 2 value 803.852706
#> iter 3 value 780.961296
#> iter 4 value 778.399260
#> iter 5 value 744.757083
#> iter 6 value 738.838124
#> iter 7 value 738.160811
#> iter 8 value 738.131626
#> iter 9 value 738.131574
#> iter 10 value 738.131534
#> iter 11 value 738.131520
#> iter 11 value 738.131512
#> iter 11 value 738.131512
#> final value 738.131512
#> converged
#> This is Run number 25
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.2241496 0.3936844 -2.07585039 -1.3063156 2
#> 2 1 -1.35 -13.20 1.5846225 -0.8436951 0.23462251 -14.0436951 1
#> 3 1 -2.05 -14.20 -0.4266293 -0.1805012 -2.47662925 -14.3805012 1
#> 4 1 -1.55 -3.10 1.6496931 0.2544759 0.09969315 -2.8455241 1
#> 5 1 -1.90 -3.60 1.1523551 0.1575188 -0.74764495 -3.4424812 1
#> 6 1 -13.70 -1.85 1.6147058 1.6011131 -12.08529425 -0.2488869 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4060 -38375 8800
#> initial value 998.131940
#> iter 2 value 803.937227
#> iter 3 value 788.337044
#> iter 4 value 785.544902
#> iter 5 value 753.483789
#> iter 6 value 746.276096
#> iter 7 value 745.273850
#> iter 8 value 745.239927
#> iter 9 value 745.239817
#> iter 9 value 745.239815
#> iter 9 value 745.239813
#> final value 745.239813
#> converged
#> This is Run number 26
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.9500649 -1.0863032 -2.3499351 -2.786303 1
#> 2 1 -1.35 -13.20 -0.4123229 1.7367334 -1.7623229 -11.463267 1
#> 3 1 -2.05 -14.20 1.4390107 2.9380794 -0.6109893 -11.261921 1
#> 4 1 -1.55 -3.10 1.8184782 -0.6711854 0.2684782 -3.771185 1
#> 5 1 -1.90 -3.60 2.1263605 -0.6091263 0.2263605 -4.209126 1
#> 6 1 -13.70 -1.85 -0.1282265 -0.4777694 -13.8282265 -2.327769 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3420 -36325 10550
#> initial value 998.131940
#> iter 2 value 819.741211
#> iter 3 value 798.662883
#> iter 4 value 797.691958
#> iter 5 value 763.819833
#> iter 6 value 757.898451
#> iter 7 value 757.299132
#> iter 8 value 757.280457
#> iter 9 value 757.280364
#> iter 10 value 757.280279
#> iter 11 value 757.280249
#> iter 12 value 757.280236
#> iter 12 value 757.280236
#> iter 12 value 757.280236
#> final value 757.280236
#> converged
#> This is Run number 27
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.0330198 0.48130666 -3.2669802 -1.2186933 2
#> 2 1 -1.35 -13.20 -1.0186796 1.64191075 -2.3686796 -11.5580892 1
#> 3 1 -2.05 -14.20 0.2746398 -0.64257869 -1.7753602 -14.8425787 1
#> 4 1 -1.55 -3.10 0.6778806 0.86622701 -0.8721194 -2.2337730 1
#> 5 1 -1.90 -3.60 -0.3301141 0.07553137 -2.2301141 -3.5244686 1
#> 6 1 -13.70 -1.85 -0.4130348 1.68334681 -14.1130348 -0.1666532 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4240 -37075 7575
#> initial value 998.131940
#> iter 2 value 830.365032
#> iter 3 value 818.446742
#> iter 4 value 816.052736
#> iter 5 value 780.550199
#> iter 6 value 773.108159
#> iter 7 value 771.727497
#> iter 8 value 771.690677
#> iter 9 value 771.690495
#> iter 9 value 771.690489
#> iter 9 value 771.690488
#> final value 771.690488
#> converged
#> This is Run number 28
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.3889718 2.61556777 -3.9110282 0.9155678 2
#> 2 1 -1.35 -13.20 3.4915278 0.48420318 2.1415278 -12.7157968 1
#> 3 1 -2.05 -14.20 -0.3896632 -0.90011560 -2.4396632 -15.1001156 1
#> 4 1 -1.55 -3.10 -0.4079354 -0.01331545 -1.9579354 -3.1133154 1
#> 5 1 -1.90 -3.60 2.7520299 -0.70477169 0.8520299 -4.3047717 1
#> 6 1 -13.70 -1.85 4.0525420 0.32305991 -9.6474580 -1.5269401 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3940 -36625 8475
#> initial value 998.131940
#> iter 2 value 831.007872
#> iter 3 value 816.678187
#> iter 4 value 814.727664
#> iter 5 value 779.223578
#> iter 6 value 772.244506
#> iter 7 value 771.140342
#> iter 8 value 771.111270
#> iter 9 value 771.111081
#> iter 10 value 771.111069
#> iter 10 value 771.111064
#> iter 10 value 771.111064
#> final value 771.111064
#> converged
#> This is Run number 29
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.5237974 0.03115513 -4.8237974 -1.668845 2
#> 2 1 -1.35 -13.20 0.3273560 -1.17450841 -1.0226440 -14.374508 1
#> 3 1 -2.05 -14.20 0.5387210 -0.98911404 -1.5112790 -15.189114 1
#> 4 1 -1.55 -3.10 0.8770052 -0.51105409 -0.6729948 -3.611054 1
#> 5 1 -1.90 -3.60 0.5275517 1.05070462 -1.3724483 -2.549295 1
#> 6 1 -13.70 -1.85 -0.3752493 -0.08416412 -14.0752493 -1.934164 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3400 -36475 10575
#> initial value 998.131940
#> iter 2 value 817.496464
#> iter 3 value 796.238976
#> iter 4 value 795.162320
#> iter 5 value 761.441959
#> iter 6 value 755.509739
#> iter 7 value 754.904686
#> iter 8 value 754.885004
#> iter 9 value 754.884911
#> iter 10 value 754.884825
#> iter 11 value 754.884807
#> iter 12 value 754.884785
#> iter 12 value 754.884785
#> iter 12 value 754.884785
#> final value 754.884785
#> converged
#> This is Run number 30
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.3507037 -1.1155286 -4.650704 -2.8155286 2
#> 2 1 -1.35 -13.20 -0.6231010 0.5357722 -1.973101 -12.6642278 1
#> 3 1 -2.05 -14.20 -0.8684448 0.3145857 -2.918445 -13.8854143 1
#> 4 1 -1.55 -3.10 -0.3278663 3.2709719 -1.877866 0.1709719 2
#> 5 1 -1.90 -3.60 -0.6984556 0.7597418 -2.598456 -2.8402582 1
#> 6 1 -13.70 -1.85 -0.6910435 -1.1014933 -14.391043 -2.9514933 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3440 -35525 8675
#> initial value 998.131940
#> iter 2 value 843.768213
#> iter 3 value 828.312275
#> iter 4 value 826.278209
#> iter 5 value 788.247023
#> iter 6 value 781.666807
#> iter 7 value 780.652945
#> iter 8 value 780.629964
#> iter 9 value 780.629840
#> iter 9 value 780.629831
#> iter 9 value 780.629828
#> final value 780.629828
#> converged
#> This is Run number 31
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.5334379 -0.4343586 -4.83343790 -2.134359 2
#> 2 1 -1.35 -13.20 1.4252089 -0.2276011 0.07520889 -13.427601 1
#> 3 1 -2.05 -14.20 -1.3659080 0.8283056 -3.41590801 -13.371694 1
#> 4 1 -1.55 -3.10 0.1308927 0.9737166 -1.41910732 -2.126283 1
#> 5 1 -1.90 -3.60 -0.7240009 1.5318725 -2.62400085 -2.068128 2
#> 6 1 -13.70 -1.85 1.2874782 0.2149531 -12.41252177 -1.635047 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3520 -34550 10300
#> initial value 998.131940
#> iter 2 value 844.407146
#> iter 3 value 824.918125
#> iter 4 value 824.653201
#> iter 5 value 788.870171
#> iter 6 value 783.270329
#> iter 7 value 782.730096
#> iter 8 value 782.719733
#> iter 9 value 782.719670
#> iter 10 value 782.719655
#> iter 11 value 782.719604
#> iter 12 value 782.719563
#> iter 12 value 782.719563
#> iter 12 value 782.719563
#> final value 782.719563
#> converged
#> This is Run number 32
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.5665609 1.1935615 -4.8665609 -0.5064385 2
#> 2 1 -1.35 -13.20 -0.5818425 0.4646298 -1.9318425 -12.7353702 1
#> 3 1 -2.05 -14.20 0.3397971 2.7627875 -1.7102029 -11.4372125 1
#> 4 1 -1.55 -3.10 -0.3918284 -0.4160263 -1.9418284 -3.5160263 1
#> 5 1 -1.90 -3.60 2.1118849 0.9344290 0.2118849 -2.6655710 1
#> 6 1 -13.70 -1.85 0.3640487 0.7194498 -13.3359513 -1.1305502 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3440 -37525 10775
#> initial value 998.131940
#> iter 2 value 801.266958
#> iter 3 value 779.054344
#> iter 4 value 777.593636
#> iter 5 value 745.426083
#> iter 6 value 739.479234
#> iter 7 value 738.855381
#> iter 8 value 738.828558
#> iter 9 value 738.828477
#> iter 10 value 738.828350
#> iter 10 value 738.828342
#> iter 10 value 738.828342
#> final value 738.828342
#> converged
#> This is Run number 33
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.08007814 0.2459548 -4.2199219 -1.454045 2
#> 2 1 -1.35 -13.20 0.94592172 -0.8353740 -0.4040783 -14.035374 1
#> 3 1 -2.05 -14.20 -0.68246658 0.9336573 -2.7324666 -13.266343 1
#> 4 1 -1.55 -3.10 -0.86424247 0.5313364 -2.4142425 -2.568664 1
#> 5 1 -1.90 -3.60 0.61406679 1.0741716 -1.2859332 -2.525828 1
#> 6 1 -13.70 -1.85 -0.35870461 -0.4524353 -14.0587046 -2.302435 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2700 -35800 9525
#> initial value 998.131940
#> iter 2 value 833.353510
#> iter 3 value 813.691544
#> iter 4 value 810.557613
#> iter 5 value 771.539736
#> iter 6 value 765.220686
#> iter 7 value 764.367235
#> iter 8 value 764.346282
#> iter 9 value 764.346241
#> iter 9 value 764.346239
#> iter 9 value 764.346238
#> final value 764.346238
#> converged
#> This is Run number 34
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.08363643 4.0746499 -4.3836364 2.374650 2
#> 2 1 -1.35 -13.20 1.46851216 1.5432027 0.1185122 -11.656797 1
#> 3 1 -2.05 -14.20 -0.78690146 2.1598364 -2.8369015 -12.040164 1
#> 4 1 -1.55 -3.10 -0.26345384 0.4244812 -1.8134538 -2.675519 1
#> 5 1 -1.90 -3.60 0.24357263 1.6111610 -1.6564274 -1.988839 1
#> 6 1 -13.70 -1.85 2.95222398 0.3871934 -10.7477760 -1.462807 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3480 -36975 9700
#> initial value 998.131940
#> iter 2 value 817.408576
#> iter 3 value 798.735434
#> iter 4 value 796.600323
#> iter 5 value 762.253426
#> iter 6 value 755.749452
#> iter 7 value 754.940710
#> iter 8 value 754.915502
#> iter 9 value 754.915381
#> iter 9 value 754.915373
#> iter 9 value 754.915373
#> final value 754.915373
#> converged
#> This is Run number 35
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.80565055 0.8277831 -3.4943494 -0.8722169 2
#> 2 1 -1.35 -13.20 0.79237310 1.8895867 -0.5576269 -11.3104133 1
#> 3 1 -2.05 -14.20 0.44652947 0.5664685 -1.6034705 -13.6335315 1
#> 4 1 -1.55 -3.10 1.43264896 -0.7330763 -0.1173510 -3.8330763 1
#> 5 1 -1.90 -3.60 0.03977203 0.3157834 -1.8602280 -3.2842166 1
#> 6 1 -13.70 -1.85 0.49964919 0.2903315 -13.2003508 -1.5596685 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3940 -37600 9925
#> initial value 998.131940
#> iter 2 value 807.322100
#> iter 3 value 788.788201
#> iter 4 value 787.623500
#> iter 5 value 755.563303
#> iter 6 value 749.034195
#> iter 7 value 748.308429
#> iter 8 value 748.282800
#> iter 9 value 748.282661
#> iter 10 value 748.282593
#> iter 11 value 748.282552
#> iter 11 value 748.282548
#> iter 11 value 748.282548
#> final value 748.282548
#> converged
#> This is Run number 36
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.87410267 -0.3818885 -2.4258973 -2.081888 2
#> 2 1 -1.35 -13.20 0.01539307 1.2154860 -1.3346069 -11.984514 1
#> 3 1 -2.05 -14.20 1.76014749 -0.8430551 -0.2898525 -15.043055 1
#> 4 1 -1.55 -3.10 0.35987293 -0.3918332 -1.1901271 -3.491833 1
#> 5 1 -1.90 -3.60 -1.03722017 1.0258463 -2.9372202 -2.574154 2
#> 6 1 -13.70 -1.85 -1.17607245 -0.6798428 -14.8760725 -2.529843 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2720 -37350 10925
#> initial value 998.131940
#> iter 2 value 801.487178
#> iter 3 value 777.013271
#> iter 4 value 773.717579
#> iter 5 value 739.278981
#> iter 6 value 733.556351
#> iter 7 value 732.874605
#> iter 8 value 732.842251
#> iter 9 value 732.842220
#> iter 10 value 732.842203
#> iter 11 value 732.842186
#> iter 11 value 732.842180
#> iter 11 value 732.842180
#> final value 732.842180
#> converged
#> This is Run number 37
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.822530469 0.8279944 -2.477470 -0.8720056 2
#> 2 1 -1.35 -13.20 -0.254057245 0.6836334 -1.604057 -12.5163666 1
#> 3 1 -2.05 -14.20 -0.706735193 0.1322340 -2.756735 -14.0677660 1
#> 4 1 -1.55 -3.10 0.008619609 -0.2694211 -1.541380 -3.3694211 1
#> 5 1 -1.90 -3.60 0.846751440 0.5298287 -1.053249 -3.0701713 1
#> 6 1 -13.70 -1.85 1.390983544 -0.1083463 -12.309016 -1.9583463 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3300 -35225 10275
#> initial value 998.131940
#> iter 2 value 836.063194
#> iter 3 value 815.999617
#> iter 4 value 815.151143
#> iter 5 value 779.494754
#> iter 6 value 773.711802
#> iter 7 value 773.108357
#> iter 8 value 773.094013
#> iter 9 value 773.093920
#> iter 10 value 773.093884
#> iter 11 value 773.093839
#> iter 12 value 773.093825
#> iter 12 value 773.093825
#> iter 12 value 773.093825
#> final value 773.093825
#> converged
#> This is Run number 38
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.8783302 1.20226708 -3.4216698 -0.49773292 2
#> 2 1 -1.35 -13.20 -0.6217646 -1.14768234 -1.9717646 -14.34768234 1
#> 3 1 -2.05 -14.20 -0.2418918 -0.44997244 -2.2918918 -14.64997244 1
#> 4 1 -1.55 -3.10 1.3124067 0.85873941 -0.2375933 -2.24126059 1
#> 5 1 -1.90 -3.60 1.3248909 0.07919136 -0.5751091 -3.52080864 1
#> 6 1 -13.70 -1.85 0.5820208 1.90729397 -13.1179792 0.05729397 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3380 -36750 9425
#> initial value 998.131940
#> iter 2 value 822.375283
#> iter 3 value 804.306226
#> iter 4 value 801.802785
#> iter 5 value 766.377596
#> iter 6 value 759.780061
#> iter 7 value 758.904647
#> iter 8 value 758.879554
#> iter 9 value 758.879444
#> iter 9 value 758.879439
#> iter 9 value 758.879436
#> final value 758.879436
#> converged
#> This is Run number 39
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.65888769 -0.489183894 -3.6411123 -2.189184 2
#> 2 1 -1.35 -13.20 -0.89508469 0.561896614 -2.2450847 -12.638103 1
#> 3 1 -2.05 -14.20 2.85489445 -0.003656874 0.8048944 -14.203657 1
#> 4 1 -1.55 -3.10 -0.40348203 0.526574338 -1.9534820 -2.573426 1
#> 5 1 -1.90 -3.60 0.57649368 -1.335079555 -1.3235063 -4.935080 1
#> 6 1 -13.70 -1.85 -0.02539681 0.101377641 -13.7253968 -1.748622 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3060 -35775 10175
#> initial value 998.131940
#> iter 2 value 829.482595
#> iter 3 value 808.958327
#> iter 4 value 807.181896
#> iter 5 value 771.195783
#> iter 6 value 765.238687
#> iter 7 value 764.557050
#> iter 8 value 764.538407
#> iter 9 value 764.538310
#> iter 10 value 764.538293
#> iter 11 value 764.538274
#> iter 11 value 764.538267
#> iter 11 value 764.538267
#> final value 764.538267
#> converged
#> This is Run number 40
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.8432649 1.9921211 -1.4567351 0.2921211 2
#> 2 1 -1.35 -13.20 0.4931781 -0.5064490 -0.8568219 -13.7064490 1
#> 3 1 -2.05 -14.20 1.4246658 -1.3697065 -0.6253342 -15.5697065 1
#> 4 1 -1.55 -3.10 1.3705718 -1.1128632 -0.1794282 -4.2128632 1
#> 5 1 -1.90 -3.60 0.6668333 0.1701533 -1.2331667 -3.4298467 1
#> 6 1 -13.70 -1.85 2.2852311 1.3127905 -11.4147689 -0.5372095 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4380 -37375 9550
#> initial value 998.131940
#> iter 2 value 813.540703
#> iter 3 value 797.015409
#> iter 4 value 796.525075
#> iter 5 value 764.447136
#> iter 6 value 757.710099
#> iter 7 value 756.954642
#> iter 8 value 756.931525
#> iter 9 value 756.931343
#> iter 10 value 756.931287
#> iter 11 value 756.931214
#> iter 12 value 756.931184
#> iter 12 value 756.931184
#> iter 12 value 756.931184
#> final value 756.931184
#> converged
#> This is Run number 41
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.600244400 1.1091749 -4.900244 -0.5908251 2
#> 2 1 -1.35 -13.20 0.253514130 -0.3749894 -1.096486 -13.5749894 1
#> 3 1 -2.05 -14.20 0.700730099 1.7698894 -1.349270 -12.4301106 1
#> 4 1 -1.55 -3.10 -0.001891537 -0.2674200 -1.551892 -3.3674200 1
#> 5 1 -1.90 -3.60 -0.647796483 -0.4449195 -2.547796 -4.0449195 1
#> 6 1 -13.70 -1.85 0.211613954 1.5735321 -13.488386 -0.2764679 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3460 -35875 8725
#> initial value 998.131940
#> iter 2 value 838.943804
#> iter 3 value 823.252615
#> iter 4 value 821.034275
#> iter 5 value 783.534143
#> iter 6 value 776.853168
#> iter 7 value 775.836174
#> iter 8 value 775.812232
#> iter 9 value 775.812107
#> iter 9 value 775.812100
#> iter 9 value 775.812097
#> final value 775.812097
#> converged
#> This is Run number 42
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.24957679 -0.3948731 -4.0504232 -2.094873 2
#> 2 1 -1.35 -13.20 0.03336209 1.1966457 -1.3166379 -12.003354 1
#> 3 1 -2.05 -14.20 -0.71294207 -0.2600094 -2.7629421 -14.460009 1
#> 4 1 -1.55 -3.10 1.34541151 0.2366671 -0.2045885 -2.863333 1
#> 5 1 -1.90 -3.60 1.45464030 0.3955862 -0.4453597 -3.204414 1
#> 6 1 -13.70 -1.85 -1.08028654 -0.3703269 -14.7802865 -2.220327 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3780 -38500 10150
#> initial value 998.131940
#> iter 2 value 792.182846
#> iter 3 value 772.282235
#> iter 4 value 770.266272
#> iter 5 value 739.395284
#> iter 6 value 732.971244
#> iter 7 value 732.234286
#> iter 8 value 732.200592
#> iter 9 value 732.200513
#> iter 10 value 732.200439
#> iter 11 value 732.200418
#> iter 12 value 732.200399
#> iter 12 value 732.200399
#> iter 12 value 732.200399
#> final value 732.200399
#> converged
#> This is Run number 43
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.4915665 0.6206025 -4.7915665 -1.0793975 2
#> 2 1 -1.35 -13.20 1.5905451 0.1742261 0.2405451 -13.0257739 1
#> 3 1 -2.05 -14.20 -0.1594701 -0.1731825 -2.2094701 -14.3731825 1
#> 4 1 -1.55 -3.10 1.7165452 -1.1116179 0.1665452 -4.2116179 1
#> 5 1 -1.90 -3.60 0.3365563 -0.9920252 -1.5634437 -4.5920252 1
#> 6 1 -13.70 -1.85 0.2658008 1.0943812 -13.4341992 -0.7556188 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4160 -37200 8675
#> initial value 998.131940
#> iter 2 value 821.916855
#> iter 3 value 807.343245
#> iter 4 value 805.688078
#> iter 5 value 771.894290
#> iter 6 value 764.846957
#> iter 7 value 763.807120
#> iter 8 value 763.777202
#> iter 9 value 763.776977
#> iter 10 value 763.776958
#> iter 10 value 763.776947
#> iter 10 value 763.776940
#> final value 763.776940
#> converged
#> This is Run number 44
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.07986532 1.3613011 -4.2201347 -0.33869889 2
#> 2 1 -1.35 -13.20 1.74433253 2.0599726 0.3943325 -11.14002745 1
#> 3 1 -2.05 -14.20 -0.19417378 0.1784068 -2.2441738 -14.02159324 1
#> 4 1 -1.55 -3.10 0.25170222 3.0887365 -1.2982978 -0.01126347 2
#> 5 1 -1.90 -3.60 1.66712729 0.4689360 -0.2328727 -3.13106397 1
#> 6 1 -13.70 -1.85 0.58596474 -0.1098035 -13.1140353 -1.95980348 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2940 -36475 10000
#> initial value 998.131940
#> iter 2 value 821.321115
#> iter 3 value 800.670065
#> iter 4 value 797.838283
#> iter 5 value 761.656026
#> iter 6 value 755.447505
#> iter 7 value 754.674482
#> iter 8 value 754.650669
#> iter 9 value 754.650605
#> iter 9 value 754.650603
#> iter 9 value 754.650603
#> final value 754.650603
#> converged
#> This is Run number 45
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.2458805 0.10629460 -4.5458805 -1.593705 2
#> 2 1 -1.35 -13.20 1.1198212 0.07414584 -0.2301788 -13.125854 1
#> 3 1 -2.05 -14.20 3.4492419 0.95945640 1.3992419 -13.240544 1
#> 4 1 -1.55 -3.10 -1.4295397 -0.75556042 -2.9795397 -3.855560 1
#> 5 1 -1.90 -3.60 2.1307332 2.02945786 0.2307332 -1.570542 1
#> 6 1 -13.70 -1.85 0.2489761 2.67464799 -13.4510239 0.824648 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3940 -35625 9300
#> initial value 998.131940
#> iter 2 value 838.753266
#> iter 3 value 822.686723
#> iter 4 value 822.050059
#> iter 5 value 786.456664
#> iter 6 value 780.095517
#> iter 7 value 779.288241
#> iter 8 value 779.269712
#> iter 9 value 779.269565
#> iter 10 value 779.269531
#> iter 11 value 779.269483
#> iter 12 value 779.269454
#> iter 12 value 779.269454
#> iter 12 value 779.269454
#> final value 779.269454
#> converged
#> This is Run number 46
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.2959515 2.1706267 -3.00404845 0.4706267 2
#> 2 1 -1.35 -13.20 1.4355996 -0.4855768 0.08559965 -13.6855768 1
#> 3 1 -2.05 -14.20 -0.3728636 3.2788218 -2.42286360 -10.9211782 1
#> 4 1 -1.55 -3.10 1.4860496 0.2204187 -0.06395036 -2.8795813 1
#> 5 1 -1.90 -3.60 -1.1216762 1.1847441 -3.02167625 -2.4152559 2
#> 6 1 -13.70 -1.85 0.2121813 2.5976092 -13.48781872 0.7476092 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3420 -36600 10375
#> initial value 998.131940
#> iter 2 value 817.404265
#> iter 3 value 796.770166
#> iter 4 value 795.473008
#> iter 5 value 761.620147
#> iter 6 value 755.552881
#> iter 7 value 754.904803
#> iter 8 value 754.883847
#> iter 9 value 754.883744
#> iter 10 value 754.883683
#> iter 11 value 754.883651
#> iter 11 value 754.883646
#> iter 11 value 754.883646
#> final value 754.883646
#> converged
#> This is Run number 47
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.5224686 -0.9042366 -4.8224686 -2.604237 2
#> 2 1 -1.35 -13.20 0.7583581 2.7669659 -0.5916419 -10.433034 1
#> 3 1 -2.05 -14.20 0.6855731 -0.3210096 -1.3644269 -14.521010 1
#> 4 1 -1.55 -3.10 0.7964004 -1.2907509 -0.7535996 -4.390751 1
#> 5 1 -1.90 -3.60 -1.1457974 0.9694768 -3.0457974 -2.630523 2
#> 6 1 -13.70 -1.85 0.5820358 0.6813319 -13.1179642 -1.168668 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3200 -37225 10575
#> initial value 998.131940
#> iter 2 value 806.862567
#> iter 3 value 784.826840
#> iter 4 value 782.702470
#> iter 5 value 749.241949
#> iter 6 value 743.232227
#> iter 7 value 742.561002
#> iter 8 value 742.534227
#> iter 9 value 742.534157
#> iter 10 value 742.534108
#> iter 10 value 742.534106
#> iter 10 value 742.534096
#> final value 742.534096
#> converged
#> This is Run number 48
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.20327945 0.92616227 -4.5032794 -0.7738377 2
#> 2 1 -1.35 -13.20 -1.51886635 -1.20435313 -2.8688663 -14.4043531 1
#> 3 1 -2.05 -14.20 -0.14780385 2.22039960 -2.1978038 -11.9796004 1
#> 4 1 -1.55 -3.10 0.94329627 0.07421779 -0.6067037 -3.0257822 1
#> 5 1 -1.90 -3.60 0.01302895 0.76435022 -1.8869710 -2.8356498 1
#> 6 1 -13.70 -1.85 1.03013733 4.39721816 -12.6698627 2.5472182 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3940 -37325 9675
#> initial value 998.131940
#> iter 2 value 813.105209
#> iter 3 value 795.391477
#> iter 4 value 794.150754
#> iter 5 value 761.380026
#> iter 6 value 754.760921
#> iter 7 value 753.984863
#> iter 8 value 753.959869
#> iter 9 value 753.959704
#> iter 10 value 753.959669
#> iter 11 value 753.959629
#> iter 12 value 753.959617
#> iter 12 value 753.959617
#> iter 12 value 753.959617
#> final value 753.959617
#> converged
#> This is Run number 49
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.138709125 0.2387965 -2.161291 -1.4612035 2
#> 2 1 -1.35 -13.20 -0.004639869 2.9257721 -1.354640 -10.2742279 1
#> 3 1 -2.05 -14.20 0.065843481 0.1178580 -1.984157 -14.0821420 1
#> 4 1 -1.55 -3.10 -1.585212711 3.3562159 -3.135213 0.2562159 2
#> 5 1 -1.90 -3.60 0.406848330 0.2351549 -1.493152 -3.3648451 1
#> 6 1 -13.70 -1.85 0.985196101 -0.9466293 -12.714804 -2.7966293 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3520 -38400 10550
#> initial value 998.131940
#> iter 2 value 790.291256
#> iter 3 value 768.611228
#> iter 4 value 766.400780
#> iter 5 value 735.196943
#> iter 6 value 729.073622
#> iter 7 value 728.373981
#> iter 8 value 728.339056
#> iter 9 value 728.338986
#> iter 10 value 728.338907
#> iter 11 value 728.338852
#> iter 12 value 728.338837
#> iter 12 value 728.338837
#> iter 12 value 728.338837
#> final value 728.338837
#> converged
#> This is Run number 50
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.4695854 -0.2276799 -3.8304146 -1.927680 2
#> 2 1 -1.35 -13.20 0.7605393 0.3487866 -0.5894607 -12.851213 1
#> 3 1 -2.05 -14.20 3.5738905 0.7689458 1.5238905 -13.431054 1
#> 4 1 -1.55 -3.10 0.1764405 0.2624325 -1.3735595 -2.837567 1
#> 5 1 -1.90 -3.60 2.3891970 -1.6480856 0.4891970 -5.248086 1
#> 6 1 -13.70 -1.85 0.1333175 -0.6278360 -13.5666825 -2.477836 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3960 -38325 10325
#> initial value 998.131940
#> iter 2 value 793.608429
#> iter 3 value 773.657329
#> iter 4 value 772.488965
#> iter 5 value 741.985596
#> iter 6 value 735.640869
#> iter 7 value 734.968237
#> iter 8 value 734.938383
#> iter 9 value 734.938283
#> iter 10 value 734.938127
#> iter 10 value 734.938122
#> iter 10 value 734.938122
#> final value 734.938122
#> converged
#> This is Run number 51
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.2436145 0.02476129 -4.5436145 -1.675239 2
#> 2 1 -1.35 -13.20 -0.1441018 3.13272465 -1.4941018 -10.067275 1
#> 3 1 -2.05 -14.20 1.1769652 0.36283047 -0.8730348 -13.837170 1
#> 4 1 -1.55 -3.10 1.3669967 -0.13787985 -0.1830033 -3.237880 1
#> 5 1 -1.90 -3.60 0.1783193 -0.65408907 -1.7216807 -4.254089 1
#> 6 1 -13.70 -1.85 0.5718605 -1.36390675 -13.1281395 -3.213907 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3880 -36750 9875
#> initial value 998.131940
#> iter 2 value 819.609956
#> iter 3 value 801.403444
#> iter 4 value 800.557561
#> iter 5 value 767.136075
#> iter 6 value 760.726428
#> iter 7 value 760.014110
#> iter 8 value 759.993139
#> iter 9 value 759.992991
#> iter 10 value 759.992942
#> iter 11 value 759.992887
#> iter 12 value 759.992872
#> iter 12 value 759.992872
#> iter 12 value 759.992872
#> final value 759.992872
#> converged
#> This is Run number 52
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.8363902 -0.7489393 -3.4636098 -2.4489393 2
#> 2 1 -1.35 -13.20 2.8307556 0.2323005 1.4807556 -12.9676995 1
#> 3 1 -2.05 -14.20 0.6612769 0.3075115 -1.3887231 -13.8924885 1
#> 4 1 -1.55 -3.10 1.7615865 -0.5850805 0.2115865 -3.6850805 1
#> 5 1 -1.90 -3.60 1.1051487 3.0481182 -0.7948513 -0.5518818 2
#> 6 1 -13.70 -1.85 -0.2909534 1.4111602 -13.9909534 -0.4388398 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3760 -37900 9850
#> initial value 998.131940
#> iter 2 value 803.373283
#> iter 3 value 784.540424
#> iter 4 value 782.594776
#> iter 5 value 750.449319
#> iter 6 value 743.871397
#> iter 7 value 743.095186
#> iter 8 value 743.065808
#> iter 9 value 743.065698
#> iter 10 value 743.065663
#> iter 11 value 743.065652
#> iter 11 value 743.065642
#> iter 11 value 743.065642
#> final value 743.065642
#> converged
#> This is Run number 53
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.3278683 -0.7989263 -1.9721317 -2.4989263 1
#> 2 1 -1.35 -13.20 -0.2728445 0.3001745 -1.6228445 -12.8998255 1
#> 3 1 -2.05 -14.20 1.6141297 0.5850346 -0.4358703 -13.6149654 1
#> 4 1 -1.55 -3.10 -1.3704965 0.5814338 -2.9204965 -2.5185662 2
#> 5 1 -1.90 -3.60 1.4917879 2.4372791 -0.4082121 -1.1627209 1
#> 6 1 -13.70 -1.85 -0.3550697 2.7732537 -14.0550697 0.9232537 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3260 -36475 8650
#> initial value 998.131940
#> iter 2 value 831.184669
#> iter 3 value 814.862024
#> iter 4 value 811.732113
#> iter 5 value 773.693706
#> iter 6 value 766.741225
#> iter 7 value 765.688503
#> iter 8 value 765.663779
#> iter 9 value 765.663728
#> iter 9 value 765.663726
#> iter 9 value 765.663726
#> final value 765.663726
#> converged
#> This is Run number 54
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.88187878 -0.4991303 -5.181879 -2.19913027 2
#> 2 1 -1.35 -13.20 -1.24244946 0.4722082 -2.592449 -12.72779181 1
#> 3 1 -2.05 -14.20 0.07854368 0.3828924 -1.971456 -13.81710758 1
#> 4 1 -1.55 -3.10 0.11361489 -0.7195421 -1.436385 -3.81954208 1
#> 5 1 -1.90 -3.60 -1.41143618 -0.5929770 -3.311436 -4.19297703 1
#> 6 1 -13.70 -1.85 0.45469016 1.7730973 -13.245310 -0.07690267 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3900 -36025 9525
#> initial value 998.131940
#> iter 2 value 831.932364
#> iter 3 value 815.025445
#> iter 4 value 814.300856
#> iter 5 value 779.475359
#> iter 6 value 773.084631
#> iter 7 value 772.315932
#> iter 8 value 772.296838
#> iter 9 value 772.296685
#> iter 9 value 772.296674
#> iter 9 value 772.296674
#> final value 772.296674
#> converged
#> This is Run number 55
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.27292548 0.8043133 -4.572925 -0.8956867 2
#> 2 1 -1.35 -13.20 -0.02699911 -0.0896911 -1.376999 -13.2896911 1
#> 3 1 -2.05 -14.20 -0.29702839 -1.3170017 -2.347028 -15.5170017 1
#> 4 1 -1.55 -3.10 2.71059154 2.5612652 1.160592 -0.5387348 1
#> 5 1 -1.90 -3.60 0.32903451 -1.2068651 -1.570965 -4.8068651 1
#> 6 1 -13.70 -1.85 0.33963532 0.2844811 -13.360365 -1.5655189 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3420 -35975 8750
#> initial value 998.131940
#> iter 2 value 837.422981
#> iter 3 value 821.527582
#> iter 4 value 819.168764
#> iter 5 value 781.671756
#> iter 6 value 774.962350
#> iter 7 value 773.947321
#> iter 8 value 773.923301
#> iter 9 value 773.923184
#> iter 9 value 773.923178
#> iter 9 value 773.923176
#> final value 773.923176
#> converged
#> This is Run number 56
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.9446641 -0.6913950 -3.3553359 -2.391395 2
#> 2 1 -1.35 -13.20 1.1260203 1.2888237 -0.2239797 -11.911176 1
#> 3 1 -2.05 -14.20 0.2988398 -0.7932995 -1.7511602 -14.993300 1
#> 4 1 -1.55 -3.10 0.7503515 0.6752538 -0.7996485 -2.424746 1
#> 5 1 -1.90 -3.60 1.1767635 -0.1093214 -0.7232365 -3.709321 1
#> 6 1 -13.70 -1.85 0.5342798 1.0419060 -13.1657202 -0.808094 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3520 -37400 9475
#> initial value 998.131940
#> iter 2 value 813.081511
#> iter 3 value 794.922641
#> iter 4 value 792.271042
#> iter 5 value 758.180539
#> iter 6 value 751.478783
#> iter 7 value 750.605412
#> iter 8 value 750.577135
#> iter 9 value 750.577037
#> iter 9 value 750.577036
#> iter 9 value 750.577036
#> final value 750.577036
#> converged
#> This is Run number 57
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -1.3139111 0.6566839 -5.6139111 -1.043316 2
#> 2 1 -1.35 -13.20 0.1115677 1.0436169 -1.2384323 -12.156383 1
#> 3 1 -2.05 -14.20 1.5832227 -1.0479592 -0.4667773 -15.247959 1
#> 4 1 -1.55 -3.10 2.0566259 0.5858678 0.5066259 -2.514132 1
#> 5 1 -1.90 -3.60 0.3212783 -0.6839197 -1.5787217 -4.283920 1
#> 6 1 -13.70 -1.85 -0.1880876 0.8050426 -13.8880876 -1.044957 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3540 -37150 9225
#> initial value 998.131940
#> iter 2 value 818.397139
#> iter 3 value 801.057318
#> iter 4 value 798.414623
#> iter 5 value 763.637756
#> iter 6 value 756.847993
#> iter 7 value 755.923008
#> iter 8 value 755.895604
#> iter 9 value 755.895492
#> iter 9 value 755.895488
#> iter 9 value 755.895486
#> final value 755.895486
#> converged
#> This is Run number 58
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.8115374 0.1259506 -3.4884626 -1.574049 2
#> 2 1 -1.35 -13.20 0.4675415 -0.3970284 -0.8824585 -13.597028 1
#> 3 1 -2.05 -14.20 1.1873444 0.1840598 -0.8626556 -14.015940 1
#> 4 1 -1.55 -3.10 -0.1893475 0.9033120 -1.7393475 -2.196688 1
#> 5 1 -1.90 -3.60 -1.4870134 1.2577064 -3.3870134 -2.342294 2
#> 6 1 -13.70 -1.85 0.3259185 0.1718174 -13.3740815 -1.678183 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3540 -39050 10750
#> initial value 998.131940
#> iter 2 value 778.724187
#> iter 3 value 756.192634
#> iter 4 value 753.719245
#> iter 5 value 723.642057
#> iter 6 value 717.704598
#> iter 7 value 716.997061
#> iter 8 value 716.954766
#> iter 9 value 716.954693
#> iter 10 value 716.954662
#> iter 11 value 716.954575
#> iter 12 value 716.954447
#> iter 12 value 716.954447
#> iter 12 value 716.954447
#> final value 716.954447
#> converged
#> This is Run number 59
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.6047280 0.3773397 -4.9047280 -1.322660 2
#> 2 1 -1.35 -13.20 1.1476856 1.4088746 -0.2023144 -11.791125 1
#> 3 1 -2.05 -14.20 0.1751192 0.3477712 -1.8748808 -13.852229 1
#> 4 1 -1.55 -3.10 0.8681075 1.4860436 -0.6818925 -1.613956 1
#> 5 1 -1.90 -3.60 -0.3707588 0.4804608 -2.2707588 -3.119539 1
#> 6 1 -13.70 -1.85 -0.6558904 1.0659160 -14.3558904 -0.784084 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3340 -36000 10650
#> initial value 998.131940
#> iter 2 value 823.171071
#> iter 3 value 801.718665
#> iter 4 value 800.844489
#> iter 5 value 766.632193
#> iter 6 value 760.840458
#> iter 7 value 760.268920
#> iter 8 value 760.251984
#> iter 9 value 760.251899
#> iter 10 value 760.251813
#> iter 11 value 760.251781
#> iter 12 value 760.251769
#> iter 12 value 760.251769
#> iter 12 value 760.251769
#> final value 760.251769
#> converged
#> This is Run number 60
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.57514785 -1.62627390 -4.875148 -3.326274 2
#> 2 1 -1.35 -13.20 0.05377485 3.59338681 -1.296225 -9.606613 1
#> 3 1 -2.05 -14.20 0.69813234 0.18714773 -1.351868 -14.012852 1
#> 4 1 -1.55 -3.10 3.79992092 2.05232134 2.249921 -1.047679 1
#> 5 1 -1.90 -3.60 0.04734092 -1.29772212 -1.852659 -4.897722 1
#> 6 1 -13.70 -1.85 0.32667199 0.06677307 -13.373328 -1.783227 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3020 -36025 9550
#> initial value 998.131940
#> iter 2 value 830.760983
#> iter 3 value 811.790294
#> iter 4 value 809.145682
#> iter 5 value 771.901750
#> iter 6 value 765.550074
#> iter 7 value 764.710501
#> iter 8 value 764.688766
#> iter 9 value 764.688684
#> iter 9 value 764.688680
#> iter 9 value 764.688678
#> final value 764.688678
#> converged
#> This is Run number 61
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.5307987 -0.502689922 -2.7692013 -2.202690 2
#> 2 1 -1.35 -13.20 1.0394877 1.635539672 -0.3105123 -11.564460 1
#> 3 1 -2.05 -14.20 1.0967165 1.112453791 -0.9532835 -13.087546 1
#> 4 1 -1.55 -3.10 -0.1387617 1.307037188 -1.6887617 -1.792963 1
#> 5 1 -1.90 -3.60 1.5193536 0.009860834 -0.3806464 -3.590139 1
#> 6 1 -13.70 -1.85 0.1266054 -1.039518284 -13.5733946 -2.889518 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3500 -35625 9200
#> initial value 998.131940
#> iter 2 value 839.058478
#> iter 3 value 822.367535
#> iter 4 value 820.804340
#> iter 5 value 784.104698
#> iter 6 value 777.719102
#> iter 7 value 776.846896
#> iter 8 value 776.826217
#> iter 9 value 776.826076
#> iter 10 value 776.826059
#> iter 11 value 776.826044
#> iter 12 value 776.826031
#> iter 12 value 776.826031
#> iter 12 value 776.826031
#> final value 776.826031
#> converged
#> This is Run number 62
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.3473705 2.2920967 -3.9526295 0.5920967 2
#> 2 1 -1.35 -13.20 1.1834431 -1.3895652 -0.1665569 -14.5895652 1
#> 3 1 -2.05 -14.20 1.6050912 1.3957129 -0.4449088 -12.8042871 1
#> 4 1 -1.55 -3.10 0.1175296 1.7878840 -1.4324704 -1.3121160 2
#> 5 1 -1.90 -3.60 0.7136243 0.5065159 -1.1863757 -3.0934841 1
#> 6 1 -13.70 -1.85 -0.2320520 0.7995876 -13.9320520 -1.0504124 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3500 -36375 10575
#> initial value 998.131940
#> iter 2 value 818.954730
#> iter 3 value 797.948761
#> iter 4 value 797.132415
#> iter 5 value 763.523089
#> iter 6 value 757.594371
#> iter 7 value 757.005748
#> iter 8 value 756.987365
#> iter 9 value 756.987273
#> iter 10 value 756.987172
#> iter 11 value 756.987146
#> iter 12 value 756.987126
#> iter 12 value 756.987126
#> iter 12 value 756.987126
#> final value 756.987126
#> converged
#> This is Run number 63
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.3075441 0.5541875 -2.99245591 -1.145812 2
#> 2 1 -1.35 -13.20 1.3315740 0.5623091 -0.01842597 -12.637691 1
#> 3 1 -2.05 -14.20 -1.3794989 0.4400511 -3.42949885 -13.759949 1
#> 4 1 -1.55 -3.10 1.5349523 -0.3906656 -0.01504769 -3.490666 1
#> 5 1 -1.90 -3.60 -0.0784647 -0.9186792 -1.97846470 -4.518679 1
#> 6 1 -13.70 -1.85 -0.4509328 -0.8309991 -14.15093279 -2.680999 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3340 -36900 9975
#> initial value 998.131940
#> iter 2 value 816.249074
#> iter 3 value 796.494034
#> iter 4 value 794.345904
#> iter 5 value 759.955293
#> iter 6 value 753.624277
#> iter 7 value 752.866685
#> iter 8 value 752.842056
#> iter 9 value 752.841954
#> iter 10 value 752.841938
#> iter 11 value 752.841923
#> iter 11 value 752.841921
#> iter 11 value 752.841921
#> final value 752.841921
#> converged
#> This is Run number 64
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.04696908 0.3459612 -3.2530309 -1.3540388 2
#> 2 1 -1.35 -13.20 0.74167109 2.6689502 -0.6083289 -10.5310498 1
#> 3 1 -2.05 -14.20 1.16498827 0.3442178 -0.8850117 -13.8557822 1
#> 4 1 -1.55 -3.10 0.07138125 3.7843574 -1.4786187 0.6843574 2
#> 5 1 -1.90 -3.60 1.33257503 2.7208431 -0.5674250 -0.8791569 1
#> 6 1 -13.70 -1.85 0.53128191 -1.1585245 -13.1687181 -3.0085245 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3940 -36825 9625
#> initial value 998.131940
#> iter 2 value 820.462286
#> iter 3 value 803.072553
#> iter 4 value 802.090129
#> iter 5 value 768.546894
#> iter 6 value 761.998515
#> iter 7 value 761.226875
#> iter 8 value 761.204475
#> iter 9 value 761.204305
#> iter 10 value 761.204277
#> iter 11 value 761.204233
#> iter 12 value 761.204203
#> iter 12 value 761.204203
#> iter 12 value 761.204203
#> final value 761.204203
#> converged
#> This is Run number 65
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 3.452717 -0.5333500 -0.8472825 -2.233350 1
#> 2 1 -1.35 -13.20 0.380567 2.1813423 -0.9694330 -11.018658 1
#> 3 1 -2.05 -14.20 -1.014419 1.7292447 -3.0644189 -12.470755 1
#> 4 1 -1.55 -3.10 3.199249 1.3424933 1.6492490 -1.757507 1
#> 5 1 -1.90 -3.60 2.539451 -0.4042975 0.6394510 -4.004298 1
#> 6 1 -13.70 -1.85 0.351458 -0.4003640 -13.3485420 -2.250364 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4180 -36800 9100
#> initial value 998.131940
#> iter 2 value 824.658616
#> iter 3 value 809.191045
#> iter 4 value 808.253454
#> iter 5 value 774.430344
#> iter 6 value 767.647523
#> iter 7 value 766.751950
#> iter 8 value 766.727251
#> iter 9 value 766.727041
#> iter 10 value 766.727009
#> iter 11 value 766.726971
#> iter 12 value 766.726941
#> iter 12 value 766.726941
#> iter 12 value 766.726941
#> final value 766.726941
#> converged
#> This is Run number 66
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.3750048 1.27230408 -3.9249952 -0.4276959 2
#> 2 1 -1.35 -13.20 1.9095339 2.28817825 0.5595339 -10.9118218 1
#> 3 1 -2.05 -14.20 -0.2929050 0.06765735 -2.3429050 -14.1323426 1
#> 4 1 -1.55 -3.10 0.8450003 0.70579736 -0.7049997 -2.3942026 1
#> 5 1 -1.90 -3.60 1.0775343 0.19044430 -0.8224657 -3.4095557 1
#> 6 1 -13.70 -1.85 1.2401107 -0.95548021 -12.4598893 -2.8054802 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3480 -37450 10600
#> initial value 998.131940
#> iter 2 value 803.806085
#> iter 3 value 782.271459
#> iter 4 value 780.776178
#> iter 5 value 748.374464
#> iter 6 value 742.317023
#> iter 7 value 741.673247
#> iter 8 value 741.647075
#> iter 9 value 741.646990
#> iter 10 value 741.646889
#> iter 10 value 741.646886
#> iter 10 value 741.646876
#> final value 741.646876
#> converged
#> This is Run number 67
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.9274259 1.59313703 -5.2274259 -0.106863 2
#> 2 1 -1.35 -13.20 -0.3787414 0.35464202 -1.7287414 -12.845358 1
#> 3 1 -2.05 -14.20 1.7133033 -1.19607584 -0.3366967 -15.396076 1
#> 4 1 -1.55 -3.10 -0.9370864 0.49760074 -2.4870864 -2.602399 1
#> 5 1 -1.90 -3.60 0.6732683 0.07438315 -1.2267317 -3.525617 1
#> 6 1 -13.70 -1.85 1.6449383 -1.12325426 -12.0550617 -2.973254 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3360 -36275 9925
#> initial value 998.131940
#> iter 2 value 825.168430
#> iter 3 value 805.876425
#> iter 4 value 804.213289
#> iter 5 value 769.115022
#> iter 6 value 762.885214
#> iter 7 value 762.149945
#> iter 8 value 762.129063
#> iter 9 value 762.128941
#> iter 10 value 762.128924
#> iter 11 value 762.128902
#> iter 12 value 762.128890
#> iter 12 value 762.128890
#> iter 12 value 762.128890
#> final value 762.128890
#> converged
#> This is Run number 68
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.3768921 1.6847830 -2.9231079 -0.01521698 2
#> 2 1 -1.35 -13.20 0.8399943 -0.6487689 -0.5100057 -13.84876887 1
#> 3 1 -2.05 -14.20 0.7427929 0.6610394 -1.3072071 -13.53896063 1
#> 4 1 -1.55 -3.10 -0.1618961 1.2772755 -1.7118961 -1.82272454 1
#> 5 1 -1.90 -3.60 -0.0644338 -0.2221791 -1.9644338 -3.82217909 1
#> 6 1 -13.70 -1.85 -1.0373482 0.5354503 -14.7373482 -1.31454974 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3140 -34575 10050
#> initial value 998.131940
#> iter 2 value 845.597459
#> iter 3 value 826.127610
#> iter 4 value 825.155777
#> iter 5 value 788.191756
#> iter 6 value 782.521844
#> iter 7 value 781.899295
#> iter 8 value 781.886287
#> iter 9 value 781.886200
#> iter 10 value 781.886186
#> iter 11 value 781.886153
#> iter 12 value 781.886128
#> iter 12 value 781.886128
#> iter 12 value 781.886128
#> final value 781.886128
#> converged
#> This is Run number 69
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.15020609 1.1285263 -2.1497939 -0.5714737 2
#> 2 1 -1.35 -13.20 1.72910782 0.5119437 0.3791078 -12.6880563 1
#> 3 1 -2.05 -14.20 0.49389509 -1.4895896 -1.5561049 -15.6895896 1
#> 4 1 -1.55 -3.10 -0.02684105 2.7625859 -1.5768410 -0.3374141 2
#> 5 1 -1.90 -3.60 -0.98024388 0.5987154 -2.8802439 -3.0012846 1
#> 6 1 -13.70 -1.85 -0.28484837 0.7405223 -13.9848484 -1.1094777 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3220 -38400 9900
#> initial value 998.131940
#> iter 2 value 794.920317
#> iter 3 value 774.320516
#> iter 4 value 770.204734
#> iter 5 value 736.847354
#> iter 6 value 730.357836
#> iter 7 value 729.497005
#> iter 8 value 729.458042
#> iter 9 value 729.458026
#> iter 9 value 729.458023
#> iter 9 value 729.458019
#> final value 729.458019
#> converged
#> This is Run number 70
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.17620657 -0.8217496 -2.1237934 -2.521750 1
#> 2 1 -1.35 -13.20 1.59801014 -1.1902539 0.2480101 -14.390254 1
#> 3 1 -2.05 -14.20 0.54258144 -0.8997256 -1.5074186 -15.099726 1
#> 4 1 -1.55 -3.10 2.68768583 1.2672532 1.1376858 -1.832747 1
#> 5 1 -1.90 -3.60 0.47684813 -0.4272589 -1.4231519 -4.027259 1
#> 6 1 -13.70 -1.85 -0.03354702 -0.6189660 -13.7335470 -2.468966 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3700 -35475 9450
#> initial value 998.131940
#> iter 2 value 839.429626
#> iter 3 value 822.535622
#> iter 4 value 821.665831
#> iter 5 value 785.689597
#> iter 6 value 779.447314
#> iter 7 value 778.668749
#> iter 8 value 778.650890
#> iter 9 value 778.650753
#> iter 9 value 778.650750
#> iter 9 value 778.650750
#> final value 778.650750
#> converged
#> This is Run number 71
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.7373377 1.4938269 -1.5626623 -0.2061731 2
#> 2 1 -1.35 -13.20 -0.5069441 4.3793387 -1.8569441 -8.8206613 1
#> 3 1 -2.05 -14.20 -1.2440745 1.9920504 -3.2940745 -12.2079496 1
#> 4 1 -1.55 -3.10 1.3379003 -1.1655314 -0.2120997 -4.2655314 1
#> 5 1 -1.90 -3.60 1.1820278 0.2777094 -0.7179722 -3.3222906 1
#> 6 1 -13.70 -1.85 1.3781475 4.0976314 -12.3218525 2.2476314 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2780 -34975 10275
#> initial value 998.131940
#> iter 2 value 838.452751
#> iter 3 value 817.296930
#> iter 4 value 815.548737
#> iter 5 value 778.292606
#> iter 6 value 772.625012
#> iter 7 value 771.990384
#> iter 8 value 771.974993
#> iter 9 value 771.974913
#> iter 9 value 771.974902
#> iter 9 value 771.974902
#> final value 771.974902
#> converged
#> This is Run number 72
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.0433060042 1.33531366 -4.3433060 -0.3646863 2
#> 2 1 -1.35 -13.20 0.5793897463 0.04245014 -0.7706103 -13.1575499 1
#> 3 1 -2.05 -14.20 0.8367294825 4.67149324 -1.2132705 -9.5285068 1
#> 4 1 -1.55 -3.10 -0.0009280698 -0.29777328 -1.5509281 -3.3977733 1
#> 5 1 -1.90 -3.60 2.1727689823 1.32420403 0.2727690 -2.2757960 1
#> 6 1 -13.70 -1.85 -1.0392354888 1.53114656 -14.7392355 -0.3188534 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3820 -37700 10000
#> initial value 998.131940
#> iter 2 value 805.216824
#> iter 3 value 786.168597
#> iter 4 value 784.717700
#> iter 5 value 752.635507
#> iter 6 value 746.152532
#> iter 7 value 745.424176
#> iter 8 value 745.397219
#> iter 9 value 745.397097
#> iter 10 value 745.397036
#> iter 11 value 745.397016
#> iter 12 value 745.397001
#> iter 12 value 745.397001
#> iter 12 value 745.397001
#> final value 745.397001
#> converged
#> This is Run number 73
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.03901836 1.79743380 -4.260982 0.0974338 2
#> 2 1 -1.35 -13.20 2.40043232 1.48364279 1.050432 -11.7163572 1
#> 3 1 -2.05 -14.20 -0.49827898 1.40538913 -2.548279 -12.7946109 1
#> 4 1 -1.55 -3.10 -0.25700237 0.34157943 -1.807002 -2.7584206 1
#> 5 1 -1.90 -3.60 -0.97880905 0.02117144 -2.878809 -3.5788286 1
#> 6 1 -13.70 -1.85 0.61934432 1.36019128 -13.080656 -0.4898087 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2940 -37400 9875
#> initial value 998.131940
#> iter 2 value 809.362965
#> iter 3 value 788.573204
#> iter 4 value 784.689508
#> iter 5 value 748.983278
#> iter 6 value 742.552344
#> iter 7 value 741.703052
#> iter 8 value 741.671958
#> iter 9 value 741.671944
#> iter 9 value 741.671944
#> iter 9 value 741.671944
#> final value 741.671944
#> converged
#> This is Run number 74
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.77778779 -0.3121138 -3.5222122 -2.012114 2
#> 2 1 -1.35 -13.20 0.49740996 -0.9647594 -0.8525900 -14.164759 1
#> 3 1 -2.05 -14.20 0.02751349 0.7330980 -2.0224865 -13.466902 1
#> 4 1 -1.55 -3.10 1.26637761 0.5125573 -0.2836224 -2.587443 1
#> 5 1 -1.90 -3.60 2.68461993 -0.9802782 0.7846199 -4.580278 1
#> 6 1 -13.70 -1.85 0.33787504 -1.6460347 -13.3621250 -3.496035 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3440 -37850 10200
#> initial value 998.131940
#> iter 2 value 801.116847
#> iter 3 value 780.529520
#> iter 4 value 778.108093
#> iter 5 value 745.493301
#> iter 6 value 739.168165
#> iter 7 value 738.424249
#> iter 8 value 738.393438
#> iter 9 value 738.393370
#> iter 10 value 738.393335
#> iter 10 value 738.393335
#> iter 10 value 738.393335
#> final value 738.393335
#> converged
#> This is Run number 75
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.2411740 -0.02551364 -4.0588260 -1.725513642 2
#> 2 1 -1.35 -13.20 2.1370269 1.03323054 0.7870269 -12.166769460 1
#> 3 1 -2.05 -14.20 0.2698463 -0.11191336 -1.7801537 -14.311913355 1
#> 4 1 -1.55 -3.10 3.0024848 0.25502881 1.4524848 -2.844971187 1
#> 5 1 -1.90 -3.60 -1.2820321 0.55107569 -3.1820321 -3.048924309 2
#> 6 1 -13.70 -1.85 0.1904602 1.84800621 -13.5095398 -0.001993791 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4140 -37050 9675
#> initial value 998.131940
#> iter 2 value 817.102009
#> iter 3 value 799.881495
#> iter 4 value 799.216367
#> iter 5 value 766.414180
#> iter 6 value 759.821229
#> iter 7 value 759.078350
#> iter 8 value 759.056218
#> iter 9 value 759.056050
#> iter 10 value 759.056001
#> iter 11 value 759.055938
#> iter 12 value 759.055913
#> iter 12 value 759.055913
#> iter 12 value 759.055913
#> final value 759.055913
#> converged
#> This is Run number 76
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.18111688 0.6848220 -4.4811169 -1.0151780 2
#> 2 1 -1.35 -13.20 2.04370924 -0.2936445 0.6937092 -13.4936445 1
#> 3 1 -2.05 -14.20 0.08338243 1.4847077 -1.9666176 -12.7152923 1
#> 4 1 -1.55 -3.10 -0.08719662 2.3210186 -1.6371966 -0.7789814 2
#> 5 1 -1.90 -3.60 2.03091326 1.6255957 0.1309133 -1.9744043 1
#> 6 1 -13.70 -1.85 -0.86366791 0.7179319 -14.5636679 -1.1320681 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3460 -36975 9750
#> initial value 998.131940
#> iter 2 value 817.020023
#> iter 3 value 798.159760
#> iter 4 value 796.025825
#> iter 5 value 761.702834
#> iter 6 value 755.226731
#> iter 7 value 754.427681
#> iter 8 value 754.402539
#> iter 9 value 754.402421
#> iter 9 value 754.402412
#> iter 9 value 754.402412
#> final value 754.402412
#> converged
#> This is Run number 77
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.6910533 4.0170131 -3.6089467 2.317013 2
#> 2 1 -1.35 -13.20 2.4957084 0.1782498 1.1457084 -13.021750 1
#> 3 1 -2.05 -14.20 0.4906275 -0.5291859 -1.5593725 -14.729186 1
#> 4 1 -1.55 -3.10 0.9518225 1.7003332 -0.5981775 -1.399667 1
#> 5 1 -1.90 -3.60 -0.6477149 -0.8805364 -2.5477149 -4.480536 1
#> 6 1 -13.70 -1.85 1.4738761 -1.9849382 -12.2261239 -3.834938 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3920 -36625 8600
#> initial value 998.131940
#> iter 2 value 830.196551
#> iter 3 value 815.526503
#> iter 4 value 813.647001
#> iter 5 value 778.292531
#> iter 6 value 771.362619
#> iter 7 value 770.296157
#> iter 8 value 770.267925
#> iter 9 value 770.267736
#> iter 10 value 770.267722
#> iter 10 value 770.267716
#> iter 10 value 770.267714
#> final value 770.267714
#> converged
#> This is Run number 78
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.97643431 -0.6095550 -3.32356569 -2.3095550 2
#> 2 1 -1.35 -13.20 1.27086202 1.7254586 -0.07913798 -11.4745414 1
#> 3 1 -2.05 -14.20 1.76584845 -1.3452982 -0.28415155 -15.5452982 1
#> 4 1 -1.55 -3.10 -0.11853512 0.5019930 -1.66853512 -2.5980070 1
#> 5 1 -1.90 -3.60 1.04346422 -0.1006439 -0.85653578 -3.7006439 1
#> 6 1 -13.70 -1.85 -0.06727317 1.2608061 -13.76727317 -0.5891939 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3580 -36875 9650
#> initial value 998.131940
#> iter 2 value 819.271346
#> iter 3 value 801.015358
#> iter 4 value 799.170961
#> iter 5 value 764.906409
#> iter 6 value 758.389778
#> iter 7 value 757.583406
#> iter 8 value 757.559049
#> iter 9 value 757.558909
#> iter 9 value 757.558900
#> iter 9 value 757.558900
#> final value 757.558900
#> converged
#> This is Run number 79
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.5189971 3.2309616 -4.8189971 1.5309616 2
#> 2 1 -1.35 -13.20 2.2891676 0.3766150 0.9391676 -12.8233850 1
#> 3 1 -2.05 -14.20 1.3297545 -0.6195446 -0.7202455 -14.8195446 1
#> 4 1 -1.55 -3.10 0.3580034 -1.5770421 -1.1919966 -4.6770421 1
#> 5 1 -1.90 -3.60 -0.7848488 -1.0505549 -2.6848488 -4.6505549 1
#> 6 1 -13.70 -1.85 -1.6891570 1.3515482 -15.3891570 -0.4984518 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4220 -37775 10050
#> initial value 998.131940
#> iter 2 value 804.012044
#> iter 3 value 785.603612
#> iter 4 value 785.038622
#> iter 5 value 753.892197
#> iter 6 value 747.373828
#> iter 7 value 746.705325
#> iter 8 value 746.681196
#> iter 9 value 746.681068
#> iter 10 value 746.680927
#> iter 11 value 746.680903
#> iter 12 value 746.680862
#> iter 12 value 746.680862
#> iter 12 value 746.680862
#> final value 746.680862
#> converged
#> This is Run number 80
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 3.01811429 0.1243725 -1.2818857 -1.5756275 1
#> 2 1 -1.35 -13.20 1.21052981 0.6926980 -0.1394702 -12.5073020 1
#> 3 1 -2.05 -14.20 0.02020883 0.1818687 -2.0297912 -14.0181313 1
#> 4 1 -1.55 -3.10 -0.74284270 -1.7219299 -2.2928427 -4.8219299 1
#> 5 1 -1.90 -3.60 0.10082667 2.2240046 -1.7991733 -1.3759954 2
#> 6 1 -13.70 -1.85 1.20294367 1.0353531 -12.4970563 -0.8146469 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4380 -35625 9300
#> initial value 998.131940
#> iter 2 value 838.957660
#> iter 3 value 823.626334
#> iter 4 value 823.517529
#> iter 5 value 788.504933
#> iter 6 value 782.106793
#> iter 7 value 781.346302
#> iter 8 value 781.330199
#> iter 9 value 781.330079
#> iter 10 value 781.330038
#> iter 11 value 781.329973
#> iter 12 value 781.329938
#> iter 12 value 781.329938
#> iter 12 value 781.329938
#> final value 781.329938
#> converged
#> This is Run number 81
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -1.6941556 0.5463599 -5.9941556 -1.153640 2
#> 2 1 -1.35 -13.20 -0.1338268 0.8224504 -1.4838268 -12.377550 1
#> 3 1 -2.05 -14.20 -0.5532381 0.3609000 -2.6032381 -13.839100 1
#> 4 1 -1.55 -3.10 0.5136067 0.5607941 -1.0363933 -2.539206 1
#> 5 1 -1.90 -3.60 2.8461557 0.3276817 0.9461557 -3.272318 1
#> 6 1 -13.70 -1.85 -0.3572658 2.0952900 -14.0572658 0.245290 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3660 -37325 9125
#> initial value 998.131940
#> iter 2 value 816.741228
#> iter 3 value 799.867951
#> iter 4 value 797.285596
#> iter 5 value 762.960428
#> iter 6 value 756.083665
#> iter 7 value 755.138451
#> iter 8 value 755.110056
#> iter 9 value 755.109933
#> iter 9 value 755.109928
#> iter 9 value 755.109925
#> final value 755.109925
#> converged
#> This is Run number 82
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.28217362 0.07585925 -4.5821736 -1.624141 2
#> 2 1 -1.35 -13.20 0.42258010 0.45437697 -0.9274199 -12.745623 1
#> 3 1 -2.05 -14.20 0.26689313 0.41776169 -1.7831069 -13.782238 1
#> 4 1 -1.55 -3.10 0.60961943 1.07842979 -0.9403806 -2.021570 1
#> 5 1 -1.90 -3.60 4.16416235 -0.43860823 2.2641623 -4.038608 1
#> 6 1 -13.70 -1.85 -0.09981244 4.55546953 -13.7998124 2.705470 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3960 -36000 8575
#> initial value 998.131940
#> iter 2 value 838.750118
#> iter 3 value 824.478299
#> iter 4 value 823.099786
#> iter 5 value 786.952536
#> iter 6 value 780.216814
#> iter 7 value 779.165333
#> iter 8 value 779.139273
#> iter 9 value 779.139086
#> iter 10 value 779.139066
#> iter 11 value 779.139046
#> iter 12 value 779.139030
#> iter 12 value 779.139030
#> iter 12 value 779.139030
#> final value 779.139030
#> converged
#> This is Run number 83
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.4077540 -0.8054873 -3.892246 -2.505487 2
#> 2 1 -1.35 -13.20 -0.4571005 0.1007534 -1.807101 -13.099247 1
#> 3 1 -2.05 -14.20 0.2474649 0.4596309 -1.802535 -13.740369 1
#> 4 1 -1.55 -3.10 -1.0329258 1.6666836 -2.582926 -1.433316 2
#> 5 1 -1.90 -3.60 0.2070225 2.0666026 -1.692978 -1.533397 2
#> 6 1 -13.70 -1.85 -0.4719566 0.3635481 -14.171957 -1.486452 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3580 -35400 10250
#> initial value 998.131940
#> iter 2 value 834.339850
#> iter 3 value 814.857093
#> iter 4 value 814.373269
#> iter 5 value 779.387004
#> iter 6 value 773.510161
#> iter 7 value 772.917384
#> iter 8 value 772.903503
#> iter 9 value 772.903411
#> iter 10 value 772.903366
#> iter 11 value 772.903308
#> iter 12 value 772.903288
#> iter 12 value 772.903288
#> iter 12 value 772.903288
#> final value 772.903288
#> converged
#> This is Run number 84
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.66274205 0.4061998 -2.6372579 -1.293800 2
#> 2 1 -1.35 -13.20 0.05859853 -0.6029803 -1.2914015 -13.802980 1
#> 3 1 -2.05 -14.20 0.08277695 2.1183833 -1.9672231 -12.081617 1
#> 4 1 -1.55 -3.10 2.58948829 4.7286082 1.0394883 1.628608 2
#> 5 1 -1.90 -3.60 1.60447765 0.9782006 -0.2955224 -2.621799 1
#> 6 1 -13.70 -1.85 0.70090974 0.5969643 -12.9990903 -1.253036 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3380 -36275 10100
#> initial value 998.131940
#> iter 2 value 823.873606
#> iter 3 value 804.113132
#> iter 4 value 802.669393
#> iter 5 value 767.921160
#> iter 6 value 761.778520
#> iter 7 value 761.085107
#> iter 8 value 761.064976
#> iter 9 value 761.064859
#> iter 10 value 761.064828
#> iter 11 value 761.064797
#> iter 11 value 761.064790
#> iter 11 value 761.064790
#> final value 761.064790
#> converged
#> This is Run number 85
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.3173420 1.6806362 -4.617342 -0.01936381 2
#> 2 1 -1.35 -13.20 0.1153287 0.1480126 -1.234671 -13.05198738 1
#> 3 1 -2.05 -14.20 -0.1785577 -0.7023493 -2.228558 -14.90234934 1
#> 4 1 -1.55 -3.10 3.3582180 -0.2509483 1.808218 -3.35094827 1
#> 5 1 -1.90 -3.60 0.4405335 -0.9774584 -1.459467 -4.57745837 1
#> 6 1 -13.70 -1.85 -0.8578757 2.4653135 -14.557876 0.61531353 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3840 -36775 9425
#> initial value 998.131940
#> iter 2 value 822.508738
#> iter 3 value 805.488640
#> iter 4 value 804.125650
#> iter 5 value 770.030996
#> iter 6 value 763.411629
#> iter 7 value 762.577162
#> iter 8 value 762.553359
#> iter 9 value 762.553183
#> iter 9 value 762.553176
#> iter 9 value 762.553176
#> final value 762.553176
#> converged
#> This is Run number 86
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.9956252 -0.3322170 -3.304375 -2.0322170 2
#> 2 1 -1.35 -13.20 -1.6464101 1.3298604 -2.996410 -11.8701396 1
#> 3 1 -2.05 -14.20 0.2313329 -0.4247437 -1.818667 -14.6247437 1
#> 4 1 -1.55 -3.10 0.4197475 -0.9196600 -1.130252 -4.0196600 1
#> 5 1 -1.90 -3.60 -1.1005569 2.2736595 -3.000557 -1.3263405 2
#> 6 1 -13.70 -1.85 -0.7427043 1.3754036 -14.442704 -0.4745964 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3440 -36575 9675
#> initial value 998.131940
#> iter 2 value 823.053754
#> iter 3 value 804.530594
#> iter 4 value 802.586717
#> iter 5 value 767.613280
#> iter 6 value 761.182563
#> iter 7 value 760.381023
#> iter 8 value 760.357870
#> iter 9 value 760.357741
#> iter 9 value 760.357735
#> iter 9 value 760.357735
#> final value 760.357735
#> converged
#> This is Run number 87
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.0486157 -0.1605494 -3.25138429 -1.860549 2
#> 2 1 -1.35 -13.20 1.4265204 0.9808732 0.07652037 -12.219127 1
#> 3 1 -2.05 -14.20 -0.1163858 2.1064494 -2.16638581 -12.093551 1
#> 4 1 -1.55 -3.10 0.9244315 0.3901726 -0.62556848 -2.709827 1
#> 5 1 -1.90 -3.60 -0.8740805 0.1878181 -2.77408054 -3.412182 1
#> 6 1 -13.70 -1.85 2.2113112 -0.1236224 -11.48868876 -1.973622 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3760 -37600 10125
#> initial value 998.131940
#> iter 2 value 805.658686
#> iter 3 value 786.148851
#> iter 4 value 784.751519
#> iter 5 value 752.558165
#> iter 6 value 746.163937
#> iter 7 value 745.458358
#> iter 8 value 745.432085
#> iter 9 value 745.431970
#> iter 10 value 745.431899
#> iter 10 value 745.431889
#> iter 10 value 745.431889
#> final value 745.431889
#> converged
#> This is Run number 88
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -1.0659667 0.91445986 -5.365967 -0.7855401 2
#> 2 1 -1.35 -13.20 0.1265780 -1.01388720 -1.223422 -14.2138872 1
#> 3 1 -2.05 -14.20 0.7624649 0.12550929 -1.287535 -14.0744907 1
#> 4 1 -1.55 -3.10 -0.5626405 -0.48322232 -2.112641 -3.5832223 1
#> 5 1 -1.90 -3.60 -0.1441639 -0.08388782 -2.044164 -3.6838878 1
#> 6 1 -13.70 -1.85 0.4979436 -0.25933955 -13.202056 -2.1093396 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3340 -37675 11200
#> initial value 998.131940
#> iter 2 value 795.435545
#> iter 3 value 771.533027
#> iter 4 value 770.172661
#> iter 5 value 738.511983
#> iter 6 value 732.857052
#> iter 7 value 732.272748
#> iter 8 value 732.244240
#> iter 9 value 732.244155
#> iter 10 value 732.244008
#> iter 11 value 732.243939
#> iter 12 value 732.243878
#> iter 12 value 732.243878
#> iter 12 value 732.243878
#> final value 732.243878
#> converged
#> This is Run number 89
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.05911316 0.7822313 -4.3591132 -0.9177687 2
#> 2 1 -1.35 -13.20 0.67790854 0.9084010 -0.6720915 -12.2915990 1
#> 3 1 -2.05 -14.20 0.24844580 1.6630864 -1.8015542 -12.5369136 1
#> 4 1 -1.55 -3.10 2.25065254 1.5103896 0.7006525 -1.5896104 1
#> 5 1 -1.90 -3.60 0.12443650 -0.1821530 -1.7755635 -3.7821530 1
#> 6 1 -13.70 -1.85 0.83356556 0.4015417 -12.8664344 -1.4484583 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4180 -37575 8925
#> initial value 998.131940
#> iter 2 value 814.945793
#> iter 3 value 799.645788
#> iter 4 value 798.029395
#> iter 5 value 765.198288
#> iter 6 value 758.170369
#> iter 7 value 757.207070
#> iter 8 value 757.177437
#> iter 9 value 757.177217
#> iter 10 value 757.177198
#> iter 11 value 757.177184
#> iter 12 value 757.177167
#> iter 12 value 757.177167
#> iter 12 value 757.177167
#> final value 757.177167
#> converged
#> This is Run number 90
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.07702465 -0.3787252 -4.2229753 -2.078725 2
#> 2 1 -1.35 -13.20 -0.44297377 -0.1410382 -1.7929738 -13.341038 1
#> 3 1 -2.05 -14.20 2.35965259 -1.3869459 0.3096526 -15.586946 1
#> 4 1 -1.55 -3.10 1.27444313 0.6163459 -0.2755569 -2.483654 1
#> 5 1 -1.90 -3.60 0.48614057 -0.4493496 -1.4138594 -4.049350 1
#> 6 1 -13.70 -1.85 0.17456796 0.4175035 -13.5254320 -1.432497 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3900 -37725 9850
#> initial value 998.131940
#> iter 2 value 806.045254
#> iter 3 value 787.596152
#> iter 4 value 786.168491
#> iter 5 value 754.110107
#> iter 6 value 747.531529
#> iter 7 value 746.779294
#> iter 8 value 746.752215
#> iter 9 value 746.752078
#> iter 10 value 746.752026
#> iter 11 value 746.751993
#> iter 11 value 746.751990
#> iter 11 value 746.751990
#> final value 746.751990
#> converged
#> This is Run number 91
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.03767025 1.61127636 -4.262330 -0.08872364 2
#> 2 1 -1.35 -13.20 2.47673809 -0.62670758 1.126738 -13.82670758 1
#> 3 1 -2.05 -14.20 -0.21457008 0.07697631 -2.264570 -14.12302369 1
#> 4 1 -1.55 -3.10 0.33980014 1.89867451 -1.210200 -1.20132549 2
#> 5 1 -1.90 -3.60 -0.57732262 0.50117966 -2.477323 -3.09882034 1
#> 6 1 -13.70 -1.85 3.34376622 0.22994632 -10.356234 -1.62005368 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2980 -37175 11275
#> initial value 998.131940
#> iter 2 value 801.463143
#> iter 3 value 776.633913
#> iter 4 value 774.744652
#> iter 5 value 741.717004
#> iter 6 value 736.196627
#> iter 7 value 735.612550
#> iter 8 value 735.585218
#> iter 9 value 735.585155
#> iter 10 value 735.585050
#> iter 11 value 735.585006
#> iter 12 value 735.584990
#> iter 12 value 735.584990
#> iter 12 value 735.584990
#> final value 735.584990
#> converged
#> This is Run number 92
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.77303209 0.4127588 -2.5269679 -1.287241 2
#> 2 1 -1.35 -13.20 1.01475369 -0.1496808 -0.3352463 -13.349681 1
#> 3 1 -2.05 -14.20 -0.15735262 0.3493326 -2.2073526 -13.850667 1
#> 4 1 -1.55 -3.10 0.03410139 -0.5183867 -1.5158986 -3.618387 1
#> 5 1 -1.90 -3.60 -0.76812516 2.5304323 -2.6681252 -1.069568 2
#> 6 1 -13.70 -1.85 3.69035574 -0.6221569 -10.0096443 -2.472157 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3700 -37500 9100
#> initial value 998.131940
#> iter 2 value 814.455819
#> iter 3 value 797.661343
#> iter 4 value 795.002548
#> iter 5 value 760.996433
#> iter 6 value 754.073500
#> iter 7 value 753.121948
#> iter 8 value 753.092666
#> iter 9 value 753.092548
#> iter 9 value 753.092544
#> iter 9 value 753.092542
#> final value 753.092542
#> converged
#> This is Run number 93
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.1328549 0.8588373 -3.1671451 -0.8411627 2
#> 2 1 -1.35 -13.20 1.8733558 2.6725177 0.5233558 -10.5274823 1
#> 3 1 -2.05 -14.20 0.2451148 1.8923174 -1.8048852 -12.3076826 1
#> 4 1 -1.55 -3.10 2.4706231 -1.0802855 0.9206231 -4.1802855 1
#> 5 1 -1.90 -3.60 -1.0919508 1.0191154 -2.9919508 -2.5808846 2
#> 6 1 -13.70 -1.85 0.9074224 -0.5797329 -12.7925776 -2.4297329 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3340 -36275 9525
#> initial value 998.131940
#> iter 2 value 828.062488
#> iter 3 value 809.846299
#> iter 4 value 807.738022
#> iter 5 value 771.857602
#> iter 6 value 765.428470
#> iter 7 value 764.595004
#> iter 8 value 764.572557
#> iter 9 value 764.572434
#> iter 9 value 764.572424
#> iter 9 value 764.572420
#> final value 764.572420
#> converged
#> This is Run number 94
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.22870720 0.3151360 -3.071293 -1.384864 2
#> 2 1 -1.35 -13.20 -1.37745156 2.4702617 -2.727452 -10.729738 1
#> 3 1 -2.05 -14.20 0.04418381 -1.7355596 -2.005816 -15.935560 1
#> 4 1 -1.55 -3.10 2.80633831 0.7189246 1.256338 -2.381075 1
#> 5 1 -1.90 -3.60 -0.36982459 -0.9360951 -2.269825 -4.536095 1
#> 6 1 -13.70 -1.85 1.96021036 0.7353112 -11.739790 -1.114689 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2800 -36375 11125
#> initial value 998.131940
#> iter 2 value 813.501683
#> iter 3 value 789.066256
#> iter 4 value 787.141709
#> iter 5 value 752.644765
#> iter 6 value 747.140628
#> iter 7 value 746.566225
#> iter 8 value 746.543985
#> iter 9 value 746.543927
#> iter 10 value 746.543862
#> iter 10 value 746.543862
#> iter 10 value 746.543862
#> final value 746.543862
#> converged
#> This is Run number 95
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.4000612 -0.27976820 -3.8999388 -1.9797682 2
#> 2 1 -1.35 -13.20 0.1225200 0.08329398 -1.2274800 -13.1167060 1
#> 3 1 -2.05 -14.20 1.7679732 -0.92025525 -0.2820268 -15.1202552 1
#> 4 1 -1.55 -3.10 -0.3985476 -0.93006033 -1.9485476 -4.0300603 1
#> 5 1 -1.90 -3.60 4.1058816 0.54258070 2.2058816 -3.0574193 1
#> 6 1 -13.70 -1.85 1.6670153 1.26940852 -12.0329847 -0.5805915 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3460 -36675 9400
#> initial value 998.131940
#> iter 2 value 823.678062
#> iter 3 value 805.906138
#> iter 4 value 803.648213
#> iter 5 value 768.362788
#> iter 6 value 761.769356
#> iter 7 value 760.897152
#> iter 8 value 760.872535
#> iter 9 value 760.872407
#> iter 9 value 760.872399
#> iter 9 value 760.872395
#> final value 760.872395
#> converged
#> This is Run number 96
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.1779113 1.196211 -4.4779113 -0.5037890 2
#> 2 1 -1.35 -13.20 -0.4286503 1.684837 -1.7786503 -11.5151628 1
#> 3 1 -2.05 -14.20 0.8330403 1.329838 -1.2169597 -12.8701624 1
#> 4 1 -1.55 -3.10 1.1293468 -0.498274 -0.4206532 -3.5982740 1
#> 5 1 -1.90 -3.60 0.5987212 4.085377 -1.3012788 0.4853774 2
#> 6 1 -13.70 -1.85 -0.6909367 2.037133 -14.3909367 0.1871335 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4540 -37425 8800
#> initial value 998.131940
#> iter 2 value 818.073424
#> iter 3 value 803.845669
#> iter 4 value 803.028064
#> iter 5 value 770.461469
#> iter 6 value 763.398504
#> iter 7 value 762.431160
#> iter 8 value 762.402497
#> iter 9 value 762.402238
#> iter 10 value 762.402202
#> iter 11 value 762.402160
#> iter 12 value 762.402125
#> iter 12 value 762.402125
#> iter 12 value 762.402125
#> final value 762.402125
#> converged
#> This is Run number 97
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -1.24685162 2.30338301 -5.54685162 0.6033830 2
#> 2 1 -1.35 -13.20 0.36743835 1.49361635 -0.98256165 -11.7063837 1
#> 3 1 -2.05 -14.20 1.63744097 0.61666060 -0.41255903 -13.5833394 1
#> 4 1 -1.55 -3.10 1.63828598 3.64027477 0.08828598 0.5402748 2
#> 5 1 -1.90 -3.60 1.65801862 -0.03194672 -0.24198138 -3.6319467 1
#> 6 1 -13.70 -1.85 0.01710702 0.06704167 -13.68289298 -1.7829583 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3260 -36750 9125
#> initial value 998.131940
#> iter 2 value 824.294082
#> iter 3 value 806.688209
#> iter 4 value 803.607178
#> iter 5 value 767.055702
#> iter 6 value 760.293085
#> iter 7 value 759.338862
#> iter 8 value 759.313150
#> iter 9 value 759.313082
#> iter 9 value 759.313080
#> iter 9 value 759.313079
#> final value 759.313079
#> converged
#> This is Run number 98
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.6083014 -0.9538347 -2.6916986 -2.6538347 2
#> 2 1 -1.35 -13.20 1.4011501 1.2522886 0.0511501 -11.9477114 1
#> 3 1 -2.05 -14.20 1.1297231 0.7488819 -0.9202769 -13.4511181 1
#> 4 1 -1.55 -3.10 -1.6080441 0.3031029 -3.1580441 -2.7968971 2
#> 5 1 -1.90 -3.60 -1.2704653 -0.8999923 -3.1704653 -4.4999923 1
#> 6 1 -13.70 -1.85 0.6285322 2.5278776 -13.0714678 0.6778776 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4240 -38400 9000
#> initial value 998.131940
#> iter 2 value 802.343878
#> iter 3 value 786.652024
#> iter 4 value 784.626275
#> iter 5 value 753.369730
#> iter 6 value 746.251053
#> iter 7 value 745.315747
#> iter 8 value 745.282801
#> iter 9 value 745.282629
#> iter 9 value 745.282625
#> iter 9 value 745.282625
#> final value 745.282625
#> converged
#> This is Run number 99
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.2731929 1.4727437 -4.573193 -0.2272563 2
#> 2 1 -1.35 -13.20 3.7235485 -0.1056002 2.373549 -13.3056002 1
#> 3 1 -2.05 -14.20 -0.7599610 -0.1030752 -2.809961 -14.3030752 1
#> 4 1 -1.55 -3.10 6.0764949 2.0091789 4.526495 -1.0908211 1
#> 5 1 -1.90 -3.60 -0.1508503 0.5300442 -2.050850 -3.0699558 1
#> 6 1 -13.70 -1.85 -0.2331075 -0.2277064 -13.933108 -2.0777064 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3420 -35525 10625
#> initial value 998.131940
#> iter 2 value 829.629276
#> iter 3 value 808.589625
#> iter 4 value 808.052405
#> iter 5 value 773.513960
#> iter 6 value 767.804074
#> iter 7 value 767.262143
#> iter 8 value 767.248159
#> iter 9 value 767.248084
#> iter 10 value 767.248001
#> iter 11 value 767.247952
#> iter 11 value 767.247946
#> iter 11 value 767.247946
#> final value 767.247946
#> converged
#> This is Run number 100
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.0202482759 -0.51444124 -4.2797517 -2.214441 2
#> 2 1 -1.35 -13.20 0.8459905521 3.43849160 -0.5040094 -9.761508 1
#> 3 1 -2.05 -14.20 0.0661488001 -0.02579938 -1.9838512 -14.225799 1
#> 4 1 -1.55 -3.10 -0.4811870615 -0.55274542 -2.0311871 -3.652745 1
#> 5 1 -1.90 -3.60 0.0008644966 -0.49142378 -1.8991355 -4.091424 1
#> 6 1 -13.70 -1.85 0.3824722638 7.60495726 -13.3175277 5.754957 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4020 -37175 8700
#> initial value 998.131940
#> iter 2 value 822.012908
#> iter 3 value 807.089267
#> iter 4 value 805.128915
#> iter 5 value 770.987354
#> iter 6 value 763.952371
#> iter 7 value 762.912833
#> iter 8 value 762.883202
#> iter 9 value 762.883002
#> iter 10 value 762.882988
#> iter 10 value 762.882983
#> iter 10 value 762.882978
#> final value 762.882978
#> converged
#> This is Run number 101
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.79679837 -0.3305181 -5.096798 -2.030518 2
#> 2 1 -1.35 -13.20 -0.12919631 0.2058828 -1.479196 -12.994117 1
#> 3 1 -2.05 -14.20 0.14333261 0.4585691 -1.906667 -13.741431 1
#> 4 1 -1.55 -3.10 1.78091203 -1.1119879 0.230912 -4.211988 1
#> 5 1 -1.90 -3.60 0.60010071 1.0770613 -1.299899 -2.522939 1
#> 6 1 -13.70 -1.85 -0.03503953 1.3834190 -13.735040 -0.466581 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3960 -37150 10025
#> initial value 998.131940
#> iter 2 value 812.982851
#> iter 3 value 794.352459
#> iter 4 value 793.582780
#> iter 5 value 761.050170
#> iter 6 value 754.633023
#> iter 7 value 753.949246
#> iter 8 value 753.927132
#> iter 9 value 753.926996
#> iter 10 value 753.926913
#> iter 11 value 753.926854
#> iter 11 value 753.926851
#> iter 11 value 753.926851
#> final value 753.926851
#> converged
#> This is Run number 102
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 3.0094899 0.1670795 -1.2905101 -1.5329205 1
#> 2 1 -1.35 -13.20 -0.2772743 -0.8553103 -1.6272743 -14.0553103 1
#> 3 1 -2.05 -14.20 0.1932579 2.0982130 -1.8567421 -12.1017870 1
#> 4 1 -1.55 -3.10 0.5314749 -0.2338824 -1.0185251 -3.3338824 1
#> 5 1 -1.90 -3.60 1.4380508 3.1661229 -0.4619492 -0.4338771 2
#> 6 1 -13.70 -1.85 -0.3240042 -0.5331376 -14.0240042 -2.3831376 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4840 -37875 9000
#> initial value 998.131940
#> iter 2 value 810.279279
#> iter 3 value 795.905547
#> iter 4 value 795.552546
#> iter 5 value 764.383652
#> iter 6 value 757.282252
#> iter 7 value 756.417716
#> iter 8 value 756.390819
#> iter 9 value 756.390572
#> iter 10 value 756.390552
#> iter 11 value 756.390480
#> iter 12 value 756.390402
#> iter 12 value 756.390402
#> iter 12 value 756.390402
#> final value 756.390402
#> converged
#> This is Run number 103
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.4543297 -0.3371792 -3.84567034 -2.0371792 2
#> 2 1 -1.35 -13.20 2.4666879 -0.9743404 1.11668790 -14.1743404 1
#> 3 1 -2.05 -14.20 0.5033580 0.6527961 -1.54664198 -13.5472039 1
#> 4 1 -1.55 -3.10 4.0513437 -0.4494784 2.50134367 -3.5494784 1
#> 5 1 -1.90 -3.60 1.8207514 0.5251603 -0.07924858 -3.0748397 1
#> 6 1 -13.70 -1.85 -0.7266075 1.3405695 -14.42660753 -0.5094305 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3260 -36550 9375
#> initial value 998.131940
#> iter 2 value 825.306412
#> iter 3 value 807.162131
#> iter 4 value 804.479974
#> iter 5 value 768.295845
#> iter 6 value 761.718590
#> iter 7 value 760.830100
#> iter 8 value 760.805715
#> iter 9 value 760.805620
#> iter 9 value 760.805616
#> iter 9 value 760.805614
#> final value 760.805614
#> converged
#> This is Run number 104
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.7235872 0.32353052 -5.0235872 -1.376469 2
#> 2 1 -1.35 -13.20 0.3105102 0.04119523 -1.0394898 -13.158805 1
#> 3 1 -2.05 -14.20 3.2758310 0.01598781 1.2258310 -14.184012 1
#> 4 1 -1.55 -3.10 0.8170753 0.97142781 -0.7329247 -2.128572 1
#> 5 1 -1.90 -3.60 -0.5043751 -0.89862662 -2.4043751 -4.498627 1
#> 6 1 -13.70 -1.85 -0.4633795 0.57576012 -14.1633795 -1.274240 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3140 -37300 10100
#> initial value 998.131940
#> iter 2 value 809.415547
#> iter 3 value 788.604168
#> iter 4 value 785.661840
#> iter 5 value 751.236208
#> iter 6 value 744.936701
#> iter 7 value 744.162026
#> iter 8 value 744.133384
#> iter 9 value 744.133331
#> iter 9 value 744.133323
#> iter 9 value 744.133319
#> final value 744.133319
#> converged
#> This is Run number 105
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.8062978 0.3964914 -2.49370224 -1.303509 2
#> 2 1 -1.35 -13.20 -0.4461023 -0.2911887 -1.79610225 -13.491189 1
#> 3 1 -2.05 -14.20 1.5341356 3.5501900 -0.51586441 -10.649810 1
#> 4 1 -1.55 -3.10 1.5997941 1.5644012 0.04979406 -1.535599 1
#> 5 1 -1.90 -3.60 -1.8419757 -0.6006330 -3.74197571 -4.200633 1
#> 6 1 -13.70 -1.85 1.5887604 0.7771503 -12.11123963 -1.072850 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2780 -36925 12150
#> initial value 998.131940
#> iter 2 value 796.865711
#> iter 3 value 768.527422
#> iter 4 value 767.241501
#> iter 5 value 734.867418
#> iter 6 value 730.002053
#> iter 7 value 729.510905
#> iter 8 value 729.484980
#> iter 9 value 729.484792
#> iter 10 value 729.484715
#> iter 11 value 729.484670
#> iter 12 value 729.484586
#> iter 12 value 729.484586
#> iter 12 value 729.484586
#> final value 729.484586
#> converged
#> This is Run number 106
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.03416017 -0.07068438 -4.265840 -1.770684 2
#> 2 1 -1.35 -13.20 -0.41787955 0.07340962 -1.767880 -13.126590 1
#> 3 1 -2.05 -14.20 0.85041145 1.28971893 -1.199589 -12.910281 1
#> 4 1 -1.55 -3.10 -0.41014449 1.42545306 -1.960144 -1.674547 2
#> 5 1 -1.90 -3.60 0.02931122 1.39018187 -1.870689 -2.209818 1
#> 6 1 -13.70 -1.85 -0.34608511 0.13042000 -14.046085 -1.719580 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3420 -38150 9600
#> initial value 998.131940
#> iter 2 value 801.136150
#> iter 3 value 782.020998
#> iter 4 value 778.463446
#> iter 5 value 745.119577
#> iter 6 value 738.418916
#> iter 7 value 737.537502
#> iter 8 value 737.503129
#> iter 9 value 737.503104
#> iter 9 value 737.503102
#> iter 9 value 737.503102
#> final value 737.503102
#> converged
#> This is Run number 107
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.3782793 0.14999452 -4.6782793 -1.5500055 2
#> 2 1 -1.35 -13.20 0.5049635 -0.30883437 -0.8450365 -13.5088344 1
#> 3 1 -2.05 -14.20 0.3211686 0.02983778 -1.7288314 -14.1701622 1
#> 4 1 -1.55 -3.10 -0.6695333 2.57322450 -2.2195333 -0.5267755 2
#> 5 1 -1.90 -3.60 -0.3611917 5.08741416 -2.2611917 1.4874142 2
#> 6 1 -13.70 -1.85 -0.6191117 -0.15027472 -14.3191117 -2.0002747 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4160 -36625 8575
#> initial value 998.131940
#> iter 2 value 830.522247
#> iter 3 value 816.414969
#> iter 4 value 815.061559
#> iter 5 value 780.246988
#> iter 6 value 773.320514
#> iter 7 value 772.257233
#> iter 8 value 772.228725
#> iter 9 value 772.228504
#> iter 10 value 772.228481
#> iter 11 value 772.228461
#> iter 12 value 772.228443
#> iter 12 value 772.228443
#> iter 12 value 772.228443
#> final value 772.228443
#> converged
#> This is Run number 108
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.1207366 2.6086464 -4.4207366 0.9086464 2
#> 2 1 -1.35 -13.20 -1.3910348 -0.5701621 -2.7410348 -13.7701621 1
#> 3 1 -2.05 -14.20 1.2853066 -0.7537960 -0.7646934 -14.9537960 1
#> 4 1 -1.55 -3.10 1.9324587 0.8133467 0.3824587 -2.2866533 1
#> 5 1 -1.90 -3.60 0.3384024 1.9125771 -1.5615976 -1.6874229 1
#> 6 1 -13.70 -1.85 0.8713042 1.6250914 -12.8286958 -0.2249086 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4140 -37675 9775
#> initial value 998.131940
#> iter 2 value 807.487788
#> iter 3 value 789.769824
#> iter 4 value 788.865357
#> iter 5 value 757.121217
#> iter 6 value 750.478281
#> iter 7 value 749.740899
#> iter 8 value 749.715566
#> iter 9 value 749.715407
#> iter 10 value 749.715336
#> iter 11 value 749.715279
#> iter 11 value 749.715276
#> iter 11 value 749.715276
#> final value 749.715276
#> converged
#> This is Run number 109
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 5.6043102 0.31911053 1.304310 -1.380889 1
#> 2 1 -1.35 -13.20 0.6959670 1.53992317 -0.654033 -11.660077 1
#> 3 1 -2.05 -14.20 0.7962013 3.96725473 -1.253799 -10.232745 1
#> 4 1 -1.55 -3.10 0.1600130 0.71963357 -1.389987 -2.380366 1
#> 5 1 -1.90 -3.60 -0.8381133 0.97268784 -2.738113 -2.627312 2
#> 6 1 -13.70 -1.85 1.7229619 0.02664864 -11.977038 -1.823351 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4520 -37275 8400
#> initial value 998.131940
#> iter 2 value 822.777985
#> iter 3 value 809.551230
#> iter 4 value 808.411821
#> iter 5 value 775.120926
#> iter 6 value 767.959781
#> iter 7 value 766.849845
#> iter 8 value 766.817545
#> iter 9 value 766.817271
#> iter 10 value 766.817242
#> iter 11 value 766.817216
#> iter 12 value 766.817191
#> iter 12 value 766.817191
#> iter 12 value 766.817191
#> final value 766.817191
#> converged
#> This is Run number 110
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.4533817 4.8579382 -4.753382 3.1579382 2
#> 2 1 -1.35 -13.20 0.2191321 0.1502756 -1.130868 -13.0497244 1
#> 3 1 -2.05 -14.20 0.3975937 -0.6543570 -1.652406 -14.8543570 1
#> 4 1 -1.55 -3.10 -0.1839718 0.5553151 -1.733972 -2.5446849 1
#> 5 1 -1.90 -3.60 0.1282435 -0.1046646 -1.771756 -3.7046646 1
#> 6 1 -13.70 -1.85 1.8252673 2.0243499 -11.874733 0.1743499 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4040 -36325 9300
#> initial value 998.131940
#> iter 2 value 829.638901
#> iter 3 value 813.526455
#> iter 4 value 812.735273
#> iter 5 value 778.239119
#> iter 6 value 771.666469
#> iter 7 value 770.834420
#> iter 8 value 770.812961
#> iter 9 value 770.812783
#> iter 9 value 770.812779
#> iter 9 value 770.812779
#> final value 770.812779
#> converged
#> This is Run number 111
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.68948187 0.7423855 -4.9894819 -0.9576145 2
#> 2 1 -1.35 -13.20 1.08399754 -0.3087154 -0.2660025 -13.5087154 1
#> 3 1 -2.05 -14.20 3.42355560 -0.7060914 1.3735556 -14.9060914 1
#> 4 1 -1.55 -3.10 0.04745525 2.4234988 -1.5025448 -0.6765012 2
#> 5 1 -1.90 -3.60 0.26440953 -0.8063989 -1.6355905 -4.4063989 1
#> 6 1 -13.70 -1.85 0.94626255 -0.2374354 -12.7537375 -2.0874354 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3960 -36300 8600
#> initial value 998.131940
#> iter 2 value 834.614572
#> iter 3 value 820.163648
#> iter 4 value 818.608777
#> iter 5 value 782.909274
#> iter 6 value 776.083697
#> iter 7 value 775.027958
#> iter 8 value 775.000874
#> iter 9 value 775.000680
#> iter 10 value 775.000662
#> iter 11 value 775.000648
#> iter 12 value 775.000635
#> iter 12 value 775.000635
#> iter 12 value 775.000635
#> final value 775.000635
#> converged
#> This is Run number 112
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.4610066 -0.9952982 -3.838993 -2.695298 2
#> 2 1 -1.35 -13.20 4.4131350 2.2909642 3.063135 -10.909036 1
#> 3 1 -2.05 -14.20 0.3573669 -0.6151567 -1.692633 -14.815157 1
#> 4 1 -1.55 -3.10 -0.1430535 -0.6636402 -1.693053 -3.763640 1
#> 5 1 -1.90 -3.60 -0.2154042 1.1082770 -2.115404 -2.491723 1
#> 6 1 -13.70 -1.85 0.8455314 0.0779099 -12.854469 -1.772090 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4600 -36975 9400
#> initial value 998.131940
#> iter 2 value 820.281956
#> iter 3 value 804.662099
#> iter 4 value 804.498386
#> iter 5 value 771.890225
#> iter 6 value 765.143362
#> iter 7 value 764.385767
#> iter 8 value 764.365307
#> iter 9 value 764.365138
#> iter 10 value 764.365114
#> iter 11 value 764.365031
#> iter 12 value 764.364957
#> iter 12 value 764.364957
#> iter 12 value 764.364957
#> final value 764.364957
#> converged
#> This is Run number 113
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.4258670 -0.3804583 -4.725867 -2.080458 2
#> 2 1 -1.35 -13.20 -0.7803972 0.8819973 -2.130397 -12.318003 1
#> 3 1 -2.05 -14.20 -0.1684043 0.2587996 -2.218404 -13.941200 1
#> 4 1 -1.55 -3.10 0.1499839 0.8530038 -1.400016 -2.246996 1
#> 5 1 -1.90 -3.60 0.8637982 0.9848530 -1.036202 -2.615147 1
#> 6 1 -13.70 -1.85 0.6396545 0.1019730 -13.060346 -1.748027 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4000 -37600 9775
#> initial value 998.131940
#> iter 2 value 808.482410
#> iter 3 value 790.507388
#> iter 4 value 789.332133
#> iter 5 value 757.209359
#> iter 6 value 750.593527
#> iter 7 value 749.840585
#> iter 8 value 749.814739
#> iter 9 value 749.814585
#> iter 10 value 749.814531
#> iter 11 value 749.814485
#> iter 11 value 749.814483
#> iter 11 value 749.814483
#> final value 749.814483
#> converged
#> This is Run number 114
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.1775681 -1.2338758 -3.122432 -2.933876 2
#> 2 1 -1.35 -13.20 4.3309259 -1.2384082 2.980926 -14.438408 1
#> 3 1 -2.05 -14.20 -0.1140705 0.4998849 -2.164070 -13.700115 1
#> 4 1 -1.55 -3.10 3.9556908 -0.5712152 2.405691 -3.671215 1
#> 5 1 -1.90 -3.60 -0.5638071 1.5735368 -2.463807 -2.026463 2
#> 6 1 -13.70 -1.85 -0.1304986 3.5758906 -13.830499 1.725891 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4160 -37550 8175
#> initial value 998.131940
#> iter 2 value 820.085571
#> iter 3 value 806.522302
#> iter 4 value 804.067082
#> iter 5 value 770.075394
#> iter 6 value 762.729123
#> iter 7 value 761.541440
#> iter 8 value 761.507627
#> iter 9 value 761.507444
#> iter 9 value 761.507436
#> iter 9 value 761.507432
#> final value 761.507432
#> converged
#> This is Run number 115
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.7613554 0.62854458 -5.0613554 -1.071455 2
#> 2 1 -1.35 -13.20 -1.0210270 1.01514980 -2.3710270 -12.184850 1
#> 3 1 -2.05 -14.20 -0.2932160 0.28544128 -2.3432160 -13.914559 1
#> 4 1 -1.55 -3.10 0.8818511 -0.18257794 -0.6681489 -3.282578 1
#> 5 1 -1.90 -3.60 0.2555133 -0.08382406 -1.6444867 -3.683824 1
#> 6 1 -13.70 -1.85 -0.3135815 -0.02595110 -14.0135815 -1.875951 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2680 -35400 9975
#> initial value 998.131940
#> iter 2 value 835.207322
#> iter 3 value 814.469187
#> iter 4 value 811.932058
#> iter 5 value 773.831154
#> iter 6 value 767.882492
#> iter 7 value 767.147568
#> iter 8 value 767.129044
#> iter 9 value 767.128978
#> iter 9 value 767.128974
#> iter 9 value 767.128972
#> final value 767.128972
#> converged
#> This is Run number 116
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.9414030 2.2082578 -5.241403 0.5082578 2
#> 2 1 -1.35 -13.20 -0.9460581 -0.5156047 -2.296058 -13.7156047 1
#> 3 1 -2.05 -14.20 -0.2164525 -0.7786590 -2.266453 -14.9786590 1
#> 4 1 -1.55 -3.10 -0.1419503 0.7988204 -1.691950 -2.3011796 1
#> 5 1 -1.90 -3.60 -0.3155997 0.5185360 -2.215600 -3.0814640 1
#> 6 1 -13.70 -1.85 -0.3801262 0.4713324 -14.080126 -1.3786676 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3400 -37500 10075
#> initial value 998.131940
#> iter 2 value 807.097819
#> iter 3 value 786.932600
#> iter 4 value 784.551888
#> iter 5 value 751.199324
#> iter 6 value 744.833503
#> iter 7 value 744.076072
#> iter 8 value 744.047685
#> iter 9 value 744.047605
#> iter 10 value 744.047582
#> iter 10 value 744.047581
#> iter 10 value 744.047581
#> final value 744.047581
#> converged
#> This is Run number 117
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.3599294 0.3072688 -4.659929 -1.392731 2
#> 2 1 -1.35 -13.20 -0.7407248 -1.3910520 -2.090725 -14.591052 1
#> 3 1 -2.05 -14.20 0.6091768 -0.5386860 -1.440823 -14.738686 1
#> 4 1 -1.55 -3.10 0.1938947 1.8976991 -1.356105 -1.202301 2
#> 5 1 -1.90 -3.60 0.4096292 -0.2258097 -1.490371 -3.825810 1
#> 6 1 -13.70 -1.85 2.5907023 -0.8466524 -11.109298 -2.696652 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3240 -37125 9850
#> initial value 998.131940
#> iter 2 value 813.904703
#> iter 3 value 794.146909
#> iter 4 value 791.376923
#> iter 5 value 756.667203
#> iter 6 value 750.235972
#> iter 7 value 749.429110
#> iter 8 value 749.402104
#> iter 9 value 749.402031
#> iter 9 value 749.402027
#> iter 9 value 749.402027
#> final value 749.402027
#> converged
#> This is Run number 118
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.7851639 -0.8148084 -5.085164 -2.514808 2
#> 2 1 -1.35 -13.20 -0.7342475 1.6341378 -2.084248 -11.565862 1
#> 3 1 -2.05 -14.20 0.1756557 -0.4083313 -1.874344 -14.608331 1
#> 4 1 -1.55 -3.10 -0.8394415 1.6268952 -2.389441 -1.473105 2
#> 5 1 -1.90 -3.60 0.7637515 -0.9228696 -1.136249 -4.522870 1
#> 6 1 -13.70 -1.85 0.6714249 3.2387025 -13.028575 1.388702 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3600 -37650 10175
#> initial value 998.131940
#> iter 2 value 804.398489
#> iter 3 value 784.357553
#> iter 4 value 782.550446
#> iter 5 value 750.102328
#> iter 6 value 743.754438
#> iter 7 value 743.036195
#> iter 8 value 743.008404
#> iter 9 value 743.008307
#> iter 10 value 743.008253
#> iter 10 value 743.008250
#> iter 10 value 743.008242
#> final value 743.008242
#> converged
#> This is Run number 119
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.7851529 -0.3318614 -3.514847 -2.0318614 2
#> 2 1 -1.35 -13.20 -0.1984820 0.6182880 -1.548482 -12.5817120 1
#> 3 1 -2.05 -14.20 -0.9917933 2.1546514 -3.041793 -12.0453486 1
#> 4 1 -1.55 -3.10 0.4079425 2.7226101 -1.142057 -0.3773899 2
#> 5 1 -1.90 -3.60 -0.6833507 2.0459343 -2.583351 -1.5540657 2
#> 6 1 -13.70 -1.85 0.4690580 0.2136791 -13.230942 -1.6363209 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3060 -37450 10475
#> initial value 998.131940
#> iter 2 value 804.250959
#> iter 3 value 782.052569
#> iter 4 value 779.174844
#> iter 5 value 745.299149
#> iter 6 value 739.226288
#> iter 7 value 738.505411
#> iter 8 value 738.475186
#> iter 9 value 738.475140
#> iter 10 value 738.475118
#> iter 10 value 738.475109
#> iter 10 value 738.475109
#> final value 738.475109
#> converged
#> This is Run number 120
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.4488488 -0.5735838 -2.851151 -2.2735838 2
#> 2 1 -1.35 -13.20 1.7928920 -0.9582536 0.442892 -14.1582536 1
#> 3 1 -2.05 -14.20 0.9722899 2.6751788 -1.077710 -11.5248212 1
#> 4 1 -1.55 -3.10 -0.1982997 0.4613534 -1.748300 -2.6386466 1
#> 5 1 -1.90 -3.60 -1.2419426 0.7656429 -3.141943 -2.8343571 2
#> 6 1 -13.70 -1.85 -0.4852802 2.5900449 -14.185280 0.7400449 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3620 -36200 9025
#> initial value 998.131940
#> iter 2 value 832.851229
#> iter 3 value 816.641541
#> iter 4 value 814.781778
#> iter 5 value 778.755988
#> iter 6 value 772.117427
#> iter 7 value 771.175286
#> iter 8 value 771.151340
#> iter 9 value 771.151184
#> iter 10 value 771.151171
#> iter 10 value 771.151163
#> iter 10 value 771.151159
#> final value 771.151159
#> converged
#> This is Run number 121
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.2274485 0.4604212 -4.5274485 -1.2395788 2
#> 2 1 -1.35 -13.20 0.8528264 -0.3188702 -0.4971736 -13.5188702 1
#> 3 1 -2.05 -14.20 -0.5250508 0.1191872 -2.5750508 -14.0808128 1
#> 4 1 -1.55 -3.10 0.6204561 2.4375192 -0.9295439 -0.6624808 2
#> 5 1 -1.90 -3.60 1.0356492 2.2304474 -0.8643508 -1.3695526 1
#> 6 1 -13.70 -1.85 2.7731812 0.2546138 -10.9268188 -1.5953862 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4440 -36100 7700
#> initial value 998.131940
#> iter 2 value 842.992051
#> iter 3 value 831.619348
#> iter 4 value 830.410530
#> iter 5 value 794.156042
#> iter 6 value 787.164797
#> iter 7 value 785.814077
#> iter 8 value 785.778646
#> iter 9 value 785.778403
#> iter 9 value 785.778397
#> iter 9 value 785.778397
#> final value 785.778397
#> converged
#> This is Run number 122
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.1332335 -0.48636879 -4.1667665 -2.186369 2
#> 2 1 -1.35 -13.20 1.5256529 -0.05772778 0.1756529 -13.257728 1
#> 3 1 -2.05 -14.20 0.9018603 -1.19489177 -1.1481397 -15.394892 1
#> 4 1 -1.55 -3.10 -0.1625421 2.05706569 -1.7125421 -1.042934 2
#> 5 1 -1.90 -3.60 1.4201339 0.52827307 -0.4798661 -3.071727 1
#> 6 1 -13.70 -1.85 -0.4927024 -0.59082749 -14.1927024 -2.440827 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3560 -37000 10225
#> initial value 998.131940
#> iter 2 value 813.206108
#> iter 3 value 793.186789
#> iter 4 value 791.809041
#> iter 5 value 758.523356
#> iter 6 value 752.288999
#> iter 7 value 751.606486
#> iter 8 value 751.583337
#> iter 9 value 751.583225
#> iter 10 value 751.583166
#> iter 11 value 751.583136
#> iter 11 value 751.583130
#> iter 11 value 751.583130
#> final value 751.583130
#> converged
#> This is Run number 123
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.05156922 -0.7346934 -4.2484308 -2.434693 2
#> 2 1 -1.35 -13.20 0.85406425 1.6521958 -0.4959357 -11.547804 1
#> 3 1 -2.05 -14.20 0.82255863 0.2304833 -1.2274414 -13.969517 1
#> 4 1 -1.55 -3.10 -0.77975829 -1.2147762 -2.3297583 -4.314776 1
#> 5 1 -1.90 -3.60 0.79666565 0.8414129 -1.1033343 -2.758587 1
#> 6 1 -13.70 -1.85 -0.10868914 3.3723032 -13.8086891 1.522303 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3680 -36825 9075
#> initial value 998.131940
#> iter 2 value 824.102121
#> iter 3 value 807.629925
#> iter 4 value 805.477044
#> iter 5 value 770.488186
#> iter 6 value 763.700137
#> iter 7 value 762.754244
#> iter 8 value 762.727959
#> iter 9 value 762.727804
#> iter 9 value 762.727794
#> iter 9 value 762.727789
#> final value 762.727789
#> converged
#> This is Run number 124
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -1.1932372 -1.8208992 -5.493237 -3.520899 2
#> 2 1 -1.35 -13.20 -0.7041835 -0.8238112 -2.054184 -14.023811 1
#> 3 1 -2.05 -14.20 -0.8477195 0.1575259 -2.897719 -14.042474 1
#> 4 1 -1.55 -3.10 -0.5442904 0.7606963 -2.094290 -2.339304 1
#> 5 1 -1.90 -3.60 0.7019333 -0.6192146 -1.198067 -4.219215 1
#> 6 1 -13.70 -1.85 2.0641656 -0.4421758 -11.635834 -2.292176 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3960 -37650 9750
#> initial value 998.131940
#> iter 2 value 807.917216
#> iter 3 value 789.910926
#> iter 4 value 788.579119
#> iter 5 value 756.416685
#> iter 6 value 749.786331
#> iter 7 value 749.020826
#> iter 8 value 748.994268
#> iter 9 value 748.994116
#> iter 10 value 748.994069
#> iter 11 value 748.994030
#> iter 11 value 748.994028
#> iter 11 value 748.994028
#> final value 748.994028
#> converged
#> This is Run number 125
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.5256338 -0.2491366 -1.7743662 -1.949137 1
#> 2 1 -1.35 -13.20 -0.1576947 -0.5885727 -1.5076947 -13.788573 1
#> 3 1 -2.05 -14.20 0.3207808 1.5135140 -1.7292192 -12.686486 1
#> 4 1 -1.55 -3.10 2.0276993 -0.7902918 0.4776993 -3.890292 1
#> 5 1 -1.90 -3.60 1.4833894 2.4616829 -0.4166106 -1.138317 1
#> 6 1 -13.70 -1.85 1.8924771 0.1159700 -11.8075229 -1.734030 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3220 -35000 9875
#> initial value 998.131940
#> iter 2 value 841.804831
#> iter 3 value 822.864318
#> iter 4 value 821.677898
#> iter 5 value 784.903674
#> iter 6 value 779.015469
#> iter 7 value 778.331829
#> iter 8 value 778.316536
#> iter 9 value 778.316432
#> iter 9 value 778.316422
#> iter 9 value 778.316422
#> final value 778.316422
#> converged
#> This is Run number 126
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.2881536 1.5758437 -4.5881536 -0.1241563 2
#> 2 1 -1.35 -13.20 0.3152431 -0.8307058 -1.0347569 -14.0307058 1
#> 3 1 -2.05 -14.20 2.1852156 -0.1726850 0.1352156 -14.3726850 1
#> 4 1 -1.55 -3.10 2.5687527 0.7499342 1.0187527 -2.3500658 1
#> 5 1 -1.90 -3.60 -0.4360062 1.8790101 -2.3360062 -1.7209899 2
#> 6 1 -13.70 -1.85 -0.4952410 0.1408448 -14.1952410 -1.7091552 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3540 -36425 8700
#> initial value 998.131940
#> iter 2 value 831.895742
#> iter 3 value 816.198115
#> iter 4 value 813.693907
#> iter 5 value 777.028559
#> iter 6 value 770.164089
#> iter 7 value 769.122859
#> iter 8 value 769.096874
#> iter 9 value 769.096751
#> iter 9 value 769.096745
#> iter 9 value 769.096743
#> final value 769.096743
#> converged
#> This is Run number 127
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.13596376 -0.4719210 -4.16403624 -2.1719210 2
#> 2 1 -1.35 -13.20 0.27648246 3.0538336 -1.07351754 -10.1461664 1
#> 3 1 -2.05 -14.20 2.04489463 -0.9924220 -0.00510537 -15.1924220 1
#> 4 1 -1.55 -3.10 0.61849647 1.3178078 -0.93150353 -1.7821922 1
#> 5 1 -1.90 -3.60 2.47022950 3.0187425 0.57022950 -0.5812575 1
#> 6 1 -13.70 -1.85 0.03285275 0.3180292 -13.66714725 -1.5319708 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3560 -37825 10450
#> initial value 998.131940
#> iter 2 value 799.666076
#> iter 3 value 778.631126
#> iter 4 value 776.899488
#> iter 5 value 744.948618
#> iter 6 value 738.760569
#> iter 7 value 738.080813
#> iter 8 value 738.051821
#> iter 9 value 738.051738
#> iter 10 value 738.051650
#> iter 10 value 738.051649
#> iter 10 value 738.051649
#> final value 738.051649
#> converged
#> This is Run number 128
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.0947047 4.7383838 -2.2052953 3.0383838 2
#> 2 1 -1.35 -13.20 2.2508037 0.8159859 0.9008037 -12.3840141 1
#> 3 1 -2.05 -14.20 3.6006529 0.2646778 1.5506529 -13.9353222 1
#> 4 1 -1.55 -3.10 0.2490108 0.5057610 -1.3009892 -2.5942390 1
#> 5 1 -1.90 -3.60 -0.5320864 2.0610620 -2.4320864 -1.5389380 2
#> 6 1 -13.70 -1.85 0.4772463 1.2633476 -13.2227537 -0.5866524 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3360 -38325 10275
#> initial value 998.131940
#> iter 2 value 793.393163
#> iter 3 value 772.160397
#> iter 4 value 769.112346
#> iter 5 value 736.916518
#> iter 6 value 730.640692
#> iter 7 value 729.874912
#> iter 8 value 729.838593
#> iter 9 value 729.838551
#> iter 10 value 729.838526
#> iter 11 value 729.838502
#> iter 11 value 729.838495
#> iter 11 value 729.838495
#> final value 729.838495
#> converged
#> This is Run number 129
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.9702036 -0.74517929 -3.3297964 -2.4451793 2
#> 2 1 -1.35 -13.20 -1.7511460 1.53635926 -3.1011460 -11.6636407 1
#> 3 1 -2.05 -14.20 -0.9405461 1.71047951 -2.9905461 -12.4895205 1
#> 4 1 -1.55 -3.10 1.7505074 3.24397808 0.2005074 0.1439781 1
#> 5 1 -1.90 -3.60 2.7687013 0.07759844 0.8687013 -3.5224016 1
#> 6 1 -13.70 -1.85 -0.6128380 -0.44654841 -14.3128380 -2.2965484 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3300 -38475 10200
#> initial value 998.131940
#> iter 2 value 791.629805
#> iter 3 value 770.378613
#> iter 4 value 766.855765
#> iter 5 value 734.486105
#> iter 6 value 728.176798
#> iter 7 value 727.380055
#> iter 8 value 727.341216
#> iter 9 value 727.341185
#> iter 9 value 727.341183
#> iter 9 value 727.341183
#> final value 727.341183
#> converged
#> This is Run number 130
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.82542771 -0.1429724 -3.474572 -1.8429724 2
#> 2 1 -1.35 -13.20 -1.09755539 0.6727157 -2.447555 -12.5272843 1
#> 3 1 -2.05 -14.20 0.51520401 -0.6404648 -1.534796 -14.8404648 1
#> 4 1 -1.55 -3.10 0.53447840 2.2466957 -1.015522 -0.8533043 2
#> 5 1 -1.90 -3.60 0.01341429 0.4600764 -1.886586 -3.1399236 1
#> 6 1 -13.70 -1.85 -0.51198140 -0.5154147 -14.211981 -2.3654147 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3560 -38125 10750
#> initial value 998.131940
#> iter 2 value 792.833957
#> iter 3 value 770.741388
#> iter 4 value 769.135753
#> iter 5 value 737.952760
#> iter 6 value 731.950833
#> iter 7 value 731.303862
#> iter 8 value 731.272579
#> iter 9 value 731.272495
#> iter 10 value 731.272358
#> iter 11 value 731.272303
#> iter 12 value 731.272277
#> iter 12 value 731.272277
#> iter 12 value 731.272277
#> final value 731.272277
#> converged
#> This is Run number 131
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.05893223 -0.2741527 -4.2410678 -1.974153 2
#> 2 1 -1.35 -13.20 -0.29562115 0.1692996 -1.6456212 -13.030700 1
#> 3 1 -2.05 -14.20 0.85765027 0.1886230 -1.1923497 -14.011377 1
#> 4 1 -1.55 -3.10 -0.80880070 2.1808430 -2.3588007 -0.919157 2
#> 5 1 -1.90 -3.60 2.25747467 1.4631019 0.3574747 -2.136898 1
#> 6 1 -13.70 -1.85 -0.39072468 -0.5778681 -14.0907247 -2.427868 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3740 -36750 8950
#> initial value 998.131940
#> iter 2 value 826.035605
#> iter 3 value 810.050687
#> iter 4 value 807.982231
#> iter 5 value 772.863370
#> iter 6 value 766.038506
#> iter 7 value 765.063694
#> iter 8 value 765.037155
#> iter 9 value 765.036990
#> iter 10 value 765.036978
#> iter 10 value 765.036973
#> iter 10 value 765.036973
#> final value 765.036973
#> converged
#> This is Run number 132
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.6141324 -0.009820376 -3.6858676 -1.709820 2
#> 2 1 -1.35 -13.20 0.4835557 2.667871399 -0.8664443 -10.532129 1
#> 3 1 -2.05 -14.20 -0.5042820 1.130919637 -2.5542820 -13.069080 1
#> 4 1 -1.55 -3.10 2.4702052 -0.056794905 0.9202052 -3.156795 1
#> 5 1 -1.90 -3.60 -1.1620774 0.329092513 -3.0620774 -3.270907 1
#> 6 1 -13.70 -1.85 2.9548775 -0.746531648 -10.7451225 -2.596532 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3540 -36525 9800
#> initial value 998.131940
#> iter 2 value 822.930154
#> iter 3 value 804.305468
#> iter 4 value 802.774700
#> iter 5 value 768.221406
#> iter 6 value 761.857761
#> iter 7 value 761.099239
#> iter 8 value 761.077305
#> iter 9 value 761.077167
#> iter 10 value 761.077149
#> iter 11 value 761.077124
#> iter 12 value 761.077107
#> iter 12 value 761.077107
#> iter 12 value 761.077107
#> final value 761.077107
#> converged
#> This is Run number 133
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.5818099 1.0217830 -3.718190 -0.678217 2
#> 2 1 -1.35 -13.20 -0.1761203 2.0801454 -1.526120 -11.119855 1
#> 3 1 -2.05 -14.20 0.3235554 1.2236242 -1.726445 -12.976376 1
#> 4 1 -1.55 -3.10 -0.8742666 0.8153782 -2.424267 -2.284622 2
#> 5 1 -1.90 -3.60 -0.4312298 1.0714880 -2.331230 -2.528512 1
#> 6 1 -13.70 -1.85 -1.2954380 0.2010259 -14.995438 -1.648974 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3400 -36125 8875
#> initial value 998.131940
#> iter 2 value 834.598933
#> iter 3 value 818.278851
#> iter 4 value 815.852670
#> iter 5 value 778.705436
#> iter 6 value 772.004114
#> iter 7 value 771.015205
#> iter 8 value 770.991161
#> iter 9 value 770.991045
#> iter 9 value 770.991039
#> iter 9 value 770.991037
#> final value 770.991037
#> converged
#> This is Run number 134
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.26457998 -0.02381743 -4.0354200 -1.7238174 2
#> 2 1 -1.35 -13.20 0.43953022 0.89250432 -0.9104698 -12.3074957 1
#> 3 1 -2.05 -14.20 1.04426149 1.12656013 -1.0057385 -13.0734399 1
#> 4 1 -1.55 -3.10 0.09107807 -0.84661728 -1.4589219 -3.9466173 1
#> 5 1 -1.90 -3.60 0.78104055 -0.24743751 -1.1189594 -3.8474375 1
#> 6 1 -13.70 -1.85 -0.69081525 2.25811327 -14.3908152 0.4081133 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4120 -37675 7900
#> initial value 998.131940
#> iter 2 value 819.897557
#> iter 3 value 806.768707
#> iter 4 value 803.863863
#> iter 5 value 769.401905
#> iter 6 value 761.884132
#> iter 7 value 760.633199
#> iter 8 value 760.599190
#> iter 9 value 760.599068
#> iter 9 value 760.599063
#> iter 9 value 760.599060
#> final value 760.599060
#> converged
#> This is Run number 135
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.31600682 1.39287668 -3.9839932 -0.3071233 2
#> 2 1 -1.35 -13.20 -0.05690912 2.46693840 -1.4069091 -10.7330616 1
#> 3 1 -2.05 -14.20 2.22499137 -0.85609057 0.1749914 -15.0560906 1
#> 4 1 -1.55 -3.10 -0.52823518 0.23218775 -2.0782352 -2.8678123 1
#> 5 1 -1.90 -3.60 -1.25508855 2.34782995 -3.1550886 -1.2521700 2
#> 6 1 -13.70 -1.85 -0.89576021 0.04160775 -14.5957602 -1.8083923 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4160 -38275 9525
#> initial value 998.131940
#> iter 2 value 800.505393
#> iter 3 value 783.313219
#> iter 4 value 781.800161
#> iter 5 value 750.755870
#> iter 6 value 743.921543
#> iter 7 value 743.111753
#> iter 8 value 743.081427
#> iter 9 value 743.081274
#> iter 10 value 743.081232
#> iter 11 value 743.081200
#> iter 11 value 743.081198
#> iter 11 value 743.081198
#> final value 743.081198
#> converged
#> This is Run number 136
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.26003675 0.8359438 -4.0399632 -0.8640562 2
#> 2 1 -1.35 -13.20 -0.36009908 0.9745960 -1.7100991 -12.2254040 1
#> 3 1 -2.05 -14.20 2.52328929 0.1892647 0.4732893 -14.0107353 1
#> 4 1 -1.55 -3.10 0.04749592 -0.6266316 -1.5025041 -3.7266316 1
#> 5 1 -1.90 -3.60 0.56957740 0.3309988 -1.3304226 -3.2690012 1
#> 6 1 -13.70 -1.85 1.48355178 0.9841863 -12.2164482 -0.8658137 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3080 -35925 11275
#> initial value 998.131940
#> iter 2 value 818.642389
#> iter 3 value 794.552903
#> iter 4 value 793.712832
#> iter 5 value 759.906129
#> iter 6 value 754.520371
#> iter 7 value 754.025167
#> iter 8 value 754.008428
#> iter 9 value 754.008368
#> iter 10 value 754.008213
#> iter 10 value 754.008213
#> iter 10 value 754.008207
#> final value 754.008207
#> converged
#> This is Run number 137
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 3.15315405 2.88984865 -1.1468460 1.189849 2
#> 2 1 -1.35 -13.20 0.88246588 -1.63999104 -0.4675341 -14.839991 1
#> 3 1 -2.05 -14.20 -0.70574667 -0.44488008 -2.7557467 -14.644880 1
#> 4 1 -1.55 -3.10 -0.62645054 -0.04522435 -2.1764505 -3.145224 1
#> 5 1 -1.90 -3.60 4.83543623 0.16359652 2.9354362 -3.436403 1
#> 6 1 -13.70 -1.85 -0.04243297 -1.44085339 -13.7424330 -3.290853 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4520 -38275 8525
#> initial value 998.131940
#> iter 2 value 807.467886
#> iter 3 value 793.574972
#> iter 4 value 791.863588
#> iter 5 value 760.482201
#> iter 6 value 753.154279
#> iter 7 value 752.102759
#> iter 8 value 752.068206
#> iter 9 value 752.067948
#> iter 10 value 752.067931
#> iter 10 value 752.067923
#> iter 10 value 752.067914
#> final value 752.067914
#> converged
#> This is Run number 138
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.8145190 0.7714905 -2.4854810 -0.9285095 2
#> 2 1 -1.35 -13.20 5.5233524 1.8146087 4.1733524 -11.3853913 1
#> 3 1 -2.05 -14.20 1.2783247 -0.2305247 -0.7716753 -14.4305247 1
#> 4 1 -1.55 -3.10 -1.1483929 -0.5061940 -2.6983929 -3.6061940 1
#> 5 1 -1.90 -3.60 -0.2174284 -0.3090436 -2.1174284 -3.9090436 1
#> 6 1 -13.70 -1.85 -0.6753649 -0.7203401 -14.3753649 -2.5703401 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4440 -35825 8250
#> initial value 998.131940
#> iter 2 value 843.321122
#> iter 3 value 830.792232
#> iter 4 value 830.149015
#> iter 5 value 794.168381
#> iter 6 value 787.408593
#> iter 7 value 786.284655
#> iter 8 value 786.257401
#> iter 9 value 786.257200
#> iter 9 value 786.257193
#> iter 9 value 786.257193
#> final value 786.257193
#> converged
#> This is Run number 139
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 3.2066934 0.5853592 -1.0933066 -1.114641 1
#> 2 1 -1.35 -13.20 2.3137942 -1.4124321 0.9637942 -14.612432 1
#> 3 1 -2.05 -14.20 -0.1772841 1.0083809 -2.2272841 -13.191619 1
#> 4 1 -1.55 -3.10 0.5063202 0.9105780 -1.0436798 -2.189422 1
#> 5 1 -1.90 -3.60 0.8376728 -0.3979626 -1.0623272 -3.997963 1
#> 6 1 -13.70 -1.85 3.9579343 -1.4385327 -9.7420657 -3.288533 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3820 -39025 9550
#> initial value 998.131940
#> iter 2 value 788.621843
#> iter 3 value 770.248714
#> iter 4 value 767.010795
#> iter 5 value 736.221550
#> iter 6 value 729.445201
#> iter 7 value 728.576955
#> iter 8 value 728.537549
#> iter 9 value 728.537514
#> iter 9 value 728.537504
#> iter 9 value 728.537504
#> final value 728.537504
#> converged
#> This is Run number 140
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.69492773 0.8479919 -2.60507227 -0.8520081 2
#> 2 1 -1.35 -13.20 0.41224651 0.8590345 -0.93775349 -12.3409655 1
#> 3 1 -2.05 -14.20 0.58496574 4.8719338 -1.46503426 -9.3280662 1
#> 4 1 -1.55 -3.10 1.47310326 0.9139084 -0.07689674 -2.1860916 1
#> 5 1 -1.90 -3.60 0.52027474 0.6740269 -1.37972526 -2.9259731 1
#> 6 1 -13.70 -1.85 -0.09909648 3.4354755 -13.79909648 1.5854755 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3400 -36600 10150
#> initial value 998.131940
#> iter 2 value 819.123944
#> iter 3 value 799.127452
#> iter 4 value 797.556480
#> iter 5 value 763.294724
#> iter 6 value 757.108366
#> iter 7 value 756.411039
#> iter 8 value 756.389233
#> iter 9 value 756.389120
#> iter 10 value 756.389084
#> iter 11 value 756.389054
#> iter 11 value 756.389053
#> iter 11 value 756.389053
#> final value 756.389053
#> converged
#> This is Run number 141
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.6760240 -0.1320905 -3.6239760 -1.832090 2
#> 2 1 -1.35 -13.20 -0.7668984 0.3168880 -2.1168984 -12.883112 1
#> 3 1 -2.05 -14.20 0.9649826 -0.2583584 -1.0850174 -14.458358 1
#> 4 1 -1.55 -3.10 0.9152255 1.3170561 -0.6347745 -1.782944 1
#> 5 1 -1.90 -3.60 0.6103952 1.4238708 -1.2896048 -2.176129 1
#> 6 1 -13.70 -1.85 -0.9672811 4.9228763 -14.6672811 3.072876 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3300 -37250 10150
#> initial value 998.131940
#> iter 2 value 809.964720
#> iter 3 value 789.445699
#> iter 4 value 787.084434
#> iter 5 value 753.254671
#> iter 6 value 746.973832
#> iter 7 value 746.231611
#> iter 8 value 746.204617
#> iter 9 value 746.204538
#> iter 10 value 746.204516
#> iter 10 value 746.204511
#> iter 10 value 746.204511
#> final value 746.204511
#> converged
#> This is Run number 142
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.31515424 0.1585482 -2.984846 -1.541452 2
#> 2 1 -1.35 -13.20 -0.85660808 -0.6340510 -2.206608 -13.834051 1
#> 3 1 -2.05 -14.20 -1.51528248 -0.2323008 -3.565282 -14.432301 1
#> 4 1 -1.55 -3.10 1.38347203 0.4855700 -0.166528 -2.614430 1
#> 5 1 -1.90 -3.60 -0.06423696 2.3838067 -1.964237 -1.216193 2
#> 6 1 -13.70 -1.85 3.25627853 -0.3490106 -10.443721 -2.199011 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3560 -36950 10875
#> initial value 998.131940
#> iter 2 value 808.705252
#> iter 3 value 786.645484
#> iter 4 value 785.901550
#> iter 5 value 753.490609
#> iter 6 value 747.638539
#> iter 7 value 747.076427
#> iter 8 value 747.055425
#> iter 9 value 747.055344
#> iter 10 value 747.055155
#> iter 10 value 747.055154
#> iter 10 value 747.055145
#> final value 747.055145
#> converged
#> This is Run number 143
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.5052383 -0.18971789 -3.7947617 -1.889718 2
#> 2 1 -1.35 -13.20 -0.1621842 0.07388539 -1.5121842 -13.126115 1
#> 3 1 -2.05 -14.20 0.1172284 -0.50168952 -1.9327716 -14.701690 1
#> 4 1 -1.55 -3.10 2.1150745 -0.44957511 0.5650745 -3.549575 1
#> 5 1 -1.90 -3.60 0.8943112 -1.34452195 -1.0056888 -4.944522 1
#> 6 1 -13.70 -1.85 2.1296324 -1.08489867 -11.5703676 -2.934899 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3600 -35450 9375
#> initial value 998.131940
#> iter 2 value 840.184929
#> iter 3 value 823.305697
#> iter 4 value 822.202379
#> iter 5 value 785.865764
#> iter 6 value 779.607084
#> iter 7 value 778.801010
#> iter 8 value 778.782416
#> iter 9 value 778.782278
#> iter 9 value 778.782277
#> iter 9 value 778.782277
#> final value 778.782277
#> converged
#> This is Run number 144
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.3890683 1.70874734 -4.68906830 0.008747338 2
#> 2 1 -1.35 -13.20 -0.4783302 -0.36308763 -1.82833020 -13.563087626 1
#> 3 1 -2.05 -14.20 1.2101575 -0.17191690 -0.83984253 -14.371916899 1
#> 4 1 -1.55 -3.10 1.5005253 0.08868745 -0.04947469 -3.011312552 1
#> 5 1 -1.90 -3.60 -0.1452812 -0.05654540 -2.04528119 -3.656545403 1
#> 6 1 -13.70 -1.85 -0.7406279 2.69592280 -14.44062794 0.845922797 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2840 -34975 8900
#> initial value 998.131940
#> iter 2 value 848.369046
#> iter 3 value 831.125142
#> iter 4 value 828.640332
#> iter 5 value 788.085259
#> iter 6 value 781.718310
#> iter 7 value 780.787712
#> iter 8 value 780.769206
#> iter 9 value 780.769148
#> iter 9 value 780.769145
#> iter 9 value 780.769144
#> final value 780.769144
#> converged
#> This is Run number 145
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.2875433 0.71720410 -4.5875433 -0.9827959 2
#> 2 1 -1.35 -13.20 0.3924399 6.50537438 -0.9575601 -6.6946256 1
#> 3 1 -2.05 -14.20 -1.0047290 -0.28967913 -3.0547290 -14.4896791 1
#> 4 1 -1.55 -3.10 0.8915355 -0.15011464 -0.6584645 -3.2501146 1
#> 5 1 -1.90 -3.60 1.7364414 4.51894972 -0.1635586 0.9189497 2
#> 6 1 -13.70 -1.85 -1.5838653 -0.08308132 -15.2838653 -1.9330813 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3920 -37500 9150
#> initial value 998.131940
#> iter 2 value 814.314702
#> iter 3 value 797.907174
#> iter 4 value 795.914202
#> iter 5 value 762.644604
#> iter 6 value 755.742301
#> iter 7 value 754.821321
#> iter 8 value 754.792643
#> iter 9 value 754.792470
#> iter 10 value 754.792458
#> iter 10 value 754.792450
#> iter 10 value 754.792449
#> final value 754.792449
#> converged
#> This is Run number 146
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.1479605 -1.70986892 -3.152039 -3.4098689 1
#> 2 1 -1.35 -13.20 0.1332082 0.11498071 -1.216792 -13.0850193 1
#> 3 1 -2.05 -14.20 -0.5800052 0.28731859 -2.630005 -13.9126814 1
#> 4 1 -1.55 -3.10 6.2246856 2.91946788 4.674686 -0.1805321 1
#> 5 1 -1.90 -3.60 0.2325390 -0.05205622 -1.667461 -3.6520562 1
#> 6 1 -13.70 -1.85 1.1449537 -0.98016695 -12.555046 -2.8301669 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3880 -38225 9800
#> initial value 998.131940
#> iter 2 value 799.044318
#> iter 3 value 780.492839
#> iter 4 value 778.563332
#> iter 5 value 747.121366
#> iter 6 value 740.477518
#> iter 7 value 739.695103
#> iter 8 value 739.663976
#> iter 9 value 739.663871
#> iter 10 value 739.663829
#> iter 10 value 739.663828
#> iter 10 value 739.663828
#> final value 739.663828
#> converged
#> This is Run number 147
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.4377999 -0.4837869 -4.7377999 -2.183787 2
#> 2 1 -1.35 -13.20 0.9691779 1.3424228 -0.3808221 -11.857577 1
#> 3 1 -2.05 -14.20 0.6427644 1.7791320 -1.4072356 -12.420868 1
#> 4 1 -1.55 -3.10 1.2229760 0.9526136 -0.3270240 -2.147386 1
#> 5 1 -1.90 -3.60 -0.5314730 0.4884015 -2.4314730 -3.111598 1
#> 6 1 -13.70 -1.85 0.4827494 0.3278487 -13.2172506 -1.522151 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3680 -37100 10425
#> initial value 998.131940
#> iter 2 value 810.361661
#> iter 3 value 789.951001
#> iter 4 value 788.983366
#> iter 5 value 756.369577
#> iter 6 value 750.215900
#> iter 7 value 749.582993
#> iter 8 value 749.560664
#> iter 9 value 749.560561
#> iter 10 value 749.560452
#> iter 10 value 749.560445
#> iter 10 value 749.560445
#> final value 749.560445
#> converged
#> This is Run number 148
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.2799292 0.61802165 -4.5799292 -1.081978 2
#> 2 1 -1.35 -13.20 4.6407093 2.13612594 3.2907093 -11.063874 1
#> 3 1 -2.05 -14.20 0.5127272 0.09543388 -1.5372728 -14.104566 1
#> 4 1 -1.55 -3.10 -0.1299024 0.89224845 -1.6799024 -2.207752 1
#> 5 1 -1.90 -3.60 1.2637205 0.67570528 -0.6362795 -2.924295 1
#> 6 1 -13.70 -1.85 2.4941101 -0.55816710 -11.2058899 -2.408167 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3940 -36550 9550
#> initial value 998.131940
#> iter 2 value 824.765812
#> iter 3 value 807.685530
#> iter 4 value 806.790264
#> iter 5 value 772.766783
#> iter 6 value 766.247302
#> iter 7 value 765.466248
#> iter 8 value 765.444860
#> iter 9 value 765.444691
#> iter 10 value 765.444672
#> iter 11 value 765.444627
#> iter 12 value 765.444586
#> iter 12 value 765.444586
#> iter 12 value 765.444586
#> final value 765.444586
#> converged
#> This is Run number 149
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.1154075 2.0080847 -4.1845925 0.3080847 2
#> 2 1 -1.35 -13.20 2.5127603 -0.2605134 1.1627603 -13.4605134 1
#> 3 1 -2.05 -14.20 1.6207538 -0.4739484 -0.4292462 -14.6739484 1
#> 4 1 -1.55 -3.10 -0.2670073 1.0974170 -1.8170073 -2.0025830 1
#> 5 1 -1.90 -3.60 0.9518495 -0.5469247 -0.9481505 -4.1469247 1
#> 6 1 -13.70 -1.85 -0.7756821 1.5232785 -14.4756821 -0.3267215 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3720 -37525 10325
#> initial value 998.131940
#> iter 2 value 805.153249
#> iter 3 value 784.981130
#> iter 4 value 783.747292
#> iter 5 value 751.626549
#> iter 6 value 745.360709
#> iter 7 value 744.693359
#> iter 8 value 744.667939
#> iter 9 value 744.667834
#> iter 10 value 744.667737
#> iter 10 value 744.667732
#> iter 10 value 744.667722
#> final value 744.667722
#> converged
#> This is Run number 150
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.2426891 1.528947 -3.0573109 -0.1710528 2
#> 2 1 -1.35 -13.20 1.9398021 1.531420 0.5898021 -11.6685798 1
#> 3 1 -2.05 -14.20 0.8035333 0.289794 -1.2464667 -13.9102060 1
#> 4 1 -1.55 -3.10 3.4419600 1.194090 1.8919600 -1.9059101 1
#> 5 1 -1.90 -3.60 0.9354322 1.648961 -0.9645678 -1.9510386 1
#> 6 1 -13.70 -1.85 1.5636524 0.519665 -12.1363476 -1.3303350 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3760 -36925 9300
#> initial value 998.131940
#> iter 2 value 821.246331
#> iter 3 value 804.328656
#> iter 4 value 802.534957
#> iter 5 value 768.265762
#> iter 6 value 761.558737
#> iter 7 value 760.677422
#> iter 8 value 760.651885
#> iter 9 value 760.651717
#> iter 10 value 760.651703
#> iter 11 value 760.651690
#> iter 12 value 760.651677
#> iter 12 value 760.651677
#> iter 12 value 760.651677
#> final value 760.651677
#> converged
#> This is Run number 151
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.4825715 0.5760702 -1.8174285 -1.123930 2
#> 2 1 -1.35 -13.20 1.6713433 0.4390183 0.3213433 -12.760982 1
#> 3 1 -2.05 -14.20 -1.2623802 2.4870319 -3.3123802 -11.712968 1
#> 4 1 -1.55 -3.10 -0.2006655 3.3956470 -1.7506655 0.295647 2
#> 5 1 -1.90 -3.60 -1.3572634 -0.9831301 -3.2572634 -4.583130 1
#> 6 1 -13.70 -1.85 3.5932755 -0.2817101 -10.1067245 -2.131710 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3640 -36550 9225
#> initial value 998.131940
#> iter 2 value 826.800218
#> iter 3 value 809.967847
#> iter 4 value 808.084391
#> iter 5 value 772.887045
#> iter 6 value 766.239484
#> iter 7 value 765.340402
#> iter 8 value 765.315995
#> iter 9 value 765.315837
#> iter 10 value 765.315823
#> iter 10 value 765.315814
#> iter 10 value 765.315809
#> final value 765.315809
#> converged
#> This is Run number 152
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.2515457 1.4443873 -4.551546e+00 -0.25561271 2
#> 2 1 -1.35 -13.20 1.3502718 -1.1364540 2.717807e-04 -14.33645400 1
#> 3 1 -2.05 -14.20 1.2178600 -0.9137894 -8.321400e-01 -15.11378943 1
#> 4 1 -1.55 -3.10 -0.8956418 1.5431577 -2.445642e+00 -1.55684229 2
#> 5 1 -1.90 -3.60 1.0674871 0.6280994 -8.325129e-01 -2.97190065 1
#> 6 1 -13.70 -1.85 -0.5007010 1.8185388 -1.420070e+01 -0.03146118 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4620 -38525 8875
#> initial value 998.131940
#> iter 2 value 801.449699
#> iter 3 value 786.806341
#> iter 4 value 785.570261
#> iter 5 value 755.178732
#> iter 6 value 747.961173
#> iter 7 value 747.032225
#> iter 8 value 746.999592
#> iter 9 value 746.999343
#> iter 9 value 746.999333
#> iter 9 value 746.999333
#> final value 746.999333
#> converged
#> This is Run number 153
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.2452389 4.18517472 -4.0547611 2.485175 2
#> 2 1 -1.35 -13.20 0.4926933 -0.08748082 -0.8573067 -13.287481 1
#> 3 1 -2.05 -14.20 -0.8151505 -0.51250267 -2.8651505 -14.712503 1
#> 4 1 -1.55 -3.10 -0.2237312 -0.36245816 -1.7737312 -3.462458 1
#> 5 1 -1.90 -3.60 1.1453638 0.14264471 -0.7546362 -3.457355 1
#> 6 1 -13.70 -1.85 0.2634047 -0.30573831 -13.4365953 -2.155738 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2720 -36300 9550
#> initial value 998.131940
#> iter 2 value 826.589614
#> iter 3 value 806.640315
#> iter 4 value 803.101125
#> iter 5 value 764.537908
#> iter 6 value 758.102245
#> iter 7 value 757.226234
#> iter 8 value 757.202577
#> iter 9 value 757.202554
#> iter 9 value 757.202552
#> iter 9 value 757.202552
#> final value 757.202552
#> converged
#> This is Run number 154
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.31478993 0.8025989 -4.6147899 -0.8974011 2
#> 2 1 -1.35 -13.20 0.47400840 0.5011896 -0.8759916 -12.6988104 1
#> 3 1 -2.05 -14.20 0.62794010 1.0878536 -1.4220599 -13.1121464 1
#> 4 1 -1.55 -3.10 -0.19832414 -0.7988612 -1.7483241 -3.8988612 1
#> 5 1 -1.90 -3.60 0.02691388 0.9020753 -1.8730861 -2.6979247 1
#> 6 1 -13.70 -1.85 0.95113290 2.3340635 -12.7488671 0.4840635 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4000 -36625 9150
#> initial value 998.131940
#> iter 2 value 826.602038
#> iter 3 value 810.710588
#> iter 4 value 809.541811
#> iter 5 value 775.189511
#> iter 6 value 768.480934
#> iter 7 value 767.588475
#> iter 8 value 767.564251
#> iter 9 value 767.564056
#> iter 10 value 767.564029
#> iter 11 value 767.564000
#> iter 12 value 767.563976
#> iter 12 value 767.563976
#> iter 12 value 767.563976
#> final value 767.563976
#> converged
#> This is Run number 155
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.5010295 0.02636611 -4.8010295 -1.673634 2
#> 2 1 -1.35 -13.20 1.9873249 0.24814885 0.6373249 -12.951851 1
#> 3 1 -2.05 -14.20 1.1358998 3.35260651 -0.9141002 -10.847393 1
#> 4 1 -1.55 -3.10 -1.0122922 0.52577769 -2.5622922 -2.574222 1
#> 5 1 -1.90 -3.60 -0.5941264 -0.05390263 -2.4941264 -3.653903 1
#> 6 1 -13.70 -1.85 0.8586786 3.36333094 -12.8413214 1.513331 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3620 -36325 10650
#> initial value 998.131940
#> iter 2 value 819.139671
#> iter 3 value 798.152391
#> iter 4 value 797.626663
#> iter 5 value 764.310878
#> iter 6 value 758.413921
#> iter 7 value 757.854098
#> iter 8 value 757.837025
#> iter 9 value 757.836943
#> iter 10 value 757.836811
#> iter 11 value 757.836792
#> iter 12 value 757.836761
#> iter 12 value 757.836761
#> iter 12 value 757.836761
#> final value 757.836761
#> converged
#> This is Run number 156
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.7233625 1.2269414 -5.0233625 -0.4730586 2
#> 2 1 -1.35 -13.20 2.4780943 0.2837880 1.1280943 -12.9162120 1
#> 3 1 -2.05 -14.20 0.7626506 -1.1235885 -1.2873494 -15.3235885 1
#> 4 1 -1.55 -3.10 1.3785904 2.0017211 -0.1714096 -1.0982789 1
#> 5 1 -1.90 -3.60 1.9358435 0.6926696 0.0358435 -2.9073304 1
#> 6 1 -13.70 -1.85 4.6474310 0.4858236 -9.0525690 -1.3641764 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3360 -36675 9775
#> initial value 998.131940
#> iter 2 value 820.861348
#> iter 3 value 801.823415
#> iter 4 value 799.697442
#> iter 5 value 764.770347
#> iter 6 value 758.373689
#> iter 7 value 757.583403
#> iter 8 value 757.559700
#> iter 9 value 757.559584
#> iter 9 value 757.559578
#> iter 9 value 757.559578
#> final value 757.559578
#> converged
#> This is Run number 157
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.69731313 0.1453200 -3.6026869 -1.5546800 2
#> 2 1 -1.35 -13.20 -0.34839644 -0.3178735 -1.6983964 -13.5178735 1
#> 3 1 -2.05 -14.20 -0.02629944 -0.9749526 -2.0762994 -15.1749526 1
#> 4 1 -1.55 -3.10 2.10097011 1.9458315 0.5509701 -1.1541685 1
#> 5 1 -1.90 -3.60 2.51028129 -0.4311503 0.6102813 -4.0311503 1
#> 6 1 -13.70 -1.85 0.43066873 1.4141366 -13.2693313 -0.4358634 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4540 -39325 8300
#> initial value 998.131940
#> iter 2 value 792.774512
#> iter 3 value 779.000011
#> iter 4 value 776.114997
#> iter 5 value 746.404096
#> iter 6 value 738.879279
#> iter 7 value 737.814098
#> iter 8 value 737.775320
#> iter 9 value 737.775226
#> iter 9 value 737.775225
#> iter 9 value 737.775223
#> final value 737.775223
#> converged
#> This is Run number 158
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.0553203 0.2603656 -4.2446797 -1.4396344 2
#> 2 1 -1.35 -13.20 2.0116635 4.1701970 0.6616635 -9.0298030 1
#> 3 1 -2.05 -14.20 0.7694727 -0.2225942 -1.2805273 -14.4225942 1
#> 4 1 -1.55 -3.10 -0.6604612 2.7943454 -2.2104612 -0.3056546 2
#> 5 1 -1.90 -3.60 0.8867634 -0.0272099 -1.0132366 -3.6272099 1
#> 6 1 -13.70 -1.85 2.6399206 -0.3580720 -11.0600794 -2.2080720 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3280 -35675 9450
#> initial value 998.131940
#> iter 2 value 836.410109
#> iter 3 value 818.522772
#> iter 4 value 816.662765
#> iter 5 value 779.842982
#> iter 6 value 773.549535
#> iter 7 value 772.724543
#> iter 8 value 772.704494
#> iter 9 value 772.704372
#> iter 10 value 772.704360
#> iter 10 value 772.704350
#> iter 10 value 772.704347
#> final value 772.704347
#> converged
#> This is Run number 159
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.4599228 1.5018793 -4.75992277 -0.1981207 2
#> 2 1 -1.35 -13.20 0.3847489 1.3363536 -0.96525113 -11.8636464 1
#> 3 1 -2.05 -14.20 1.9620029 1.8524080 -0.08799712 -12.3475920 1
#> 4 1 -1.55 -3.10 -0.6637215 0.8715254 -2.21372150 -2.2284746 1
#> 5 1 -1.90 -3.60 0.4392898 0.1623928 -1.46071021 -3.4376072 1
#> 6 1 -13.70 -1.85 0.2093196 0.2928178 -13.49068043 -1.5571822 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3700 -38100 10425
#> initial value 998.131940
#> iter 2 value 795.957653
#> iter 3 value 775.212210
#> iter 4 value 773.630675
#> iter 5 value 742.350584
#> iter 6 value 736.114236
#> iter 7 value 735.434738
#> iter 8 value 735.404563
#> iter 9 value 735.404476
#> iter 10 value 735.404364
#> iter 10 value 735.404354
#> iter 10 value 735.404354
#> final value 735.404354
#> converged
#> This is Run number 160
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.8101815 -0.2612309 -1.4898185 -1.96123086 1
#> 2 1 -1.35 -13.20 0.8986273 6.4327119 -0.4513727 -6.76728810 1
#> 3 1 -2.05 -14.20 3.6111272 -0.3402674 1.5611272 -14.54026740 1
#> 4 1 -1.55 -3.10 0.9111845 0.4327141 -0.6388155 -2.66728592 1
#> 5 1 -1.90 -3.60 -0.8424119 1.0609811 -2.7424119 -2.53901892 2
#> 6 1 -13.70 -1.85 0.3541161 1.8355555 -13.3458839 -0.01444446 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3720 -36250 9525
#> initial value 998.131940
#> iter 2 value 828.805831
#> iter 3 value 811.457318
#> iter 4 value 810.255932
#> iter 5 value 775.361601
#> iter 6 value 768.924238
#> iter 7 value 768.126646
#> iter 8 value 768.105586
#> iter 9 value 768.105427
#> iter 9 value 768.105419
#> iter 9 value 768.105419
#> final value 768.105419
#> converged
#> This is Run number 161
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.6782610 0.4590083 -4.9782610 -1.240992 2
#> 2 1 -1.35 -13.20 1.7480567 1.5479862 0.3980567 -11.652014 1
#> 3 1 -2.05 -14.20 0.9608081 -1.7006047 -1.0891919 -15.900605 1
#> 4 1 -1.55 -3.10 0.7866687 0.4081583 -0.7633313 -2.691842 1
#> 5 1 -1.90 -3.60 0.7029003 -0.1478572 -1.1970997 -3.747857 1
#> 6 1 -13.70 -1.85 4.4151872 -1.0652142 -9.2848128 -2.915214 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4320 -37275 9775
#> initial value 998.131940
#> iter 2 value 813.287987
#> iter 3 value 796.033561
#> iter 4 value 795.640251
#> iter 5 value 763.572074
#> iter 6 value 756.963629
#> iter 7 value 756.261554
#> iter 8 value 756.239983
#> iter 9 value 756.239830
#> iter 10 value 756.239746
#> iter 11 value 756.239665
#> iter 12 value 756.239651
#> iter 12 value 756.239651
#> iter 12 value 756.239651
#> final value 756.239651
#> converged
#> This is Run number 162
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.6983528 0.9995198 -4.9983528 -0.7004802 2
#> 2 1 -1.35 -13.20 1.7240478 2.0123870 0.3740478 -11.1876130 1
#> 3 1 -2.05 -14.20 -0.2697201 -0.5098891 -2.3197201 -14.7098891 1
#> 4 1 -1.55 -3.10 0.7084374 -0.9774902 -0.8415626 -4.0774902 1
#> 5 1 -1.90 -3.60 1.7934341 -0.4445189 -0.1065659 -4.0445189 1
#> 6 1 -13.70 -1.85 -0.6146527 0.2007947 -14.3146527 -1.6492053 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2780 -35525 8900
#> initial value 998.131940
#> iter 2 value 841.324385
#> iter 3 value 823.611301
#> iter 4 value 820.655249
#> iter 5 value 779.968683
#> iter 6 value 773.382421
#> iter 7 value 772.419850
#> iter 8 value 772.400085
#> iter 9 value 772.400054
#> iter 9 value 772.400051
#> iter 9 value 772.400051
#> final value 772.400051
#> converged
#> This is Run number 163
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 4.5708736 -0.8773256 0.2708736 -2.577326 1
#> 2 1 -1.35 -13.20 0.1614379 0.2238660 -1.1885621 -12.976134 1
#> 3 1 -2.05 -14.20 -0.4621242 1.0687827 -2.5121242 -13.131217 1
#> 4 1 -1.55 -3.10 0.6416030 -0.1141787 -0.9083970 -3.214179 1
#> 5 1 -1.90 -3.60 -1.1194462 0.3345166 -3.0194462 -3.265483 1
#> 6 1 -13.70 -1.85 -0.4108435 0.1619849 -14.1108435 -1.688015 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4040 -37375 9175
#> initial value 998.131940
#> iter 2 value 816.016351
#> iter 3 value 799.856410
#> iter 4 value 798.302702
#> iter 5 value 765.171617
#> iter 6 value 758.299341
#> iter 7 value 757.398560
#> iter 8 value 757.371017
#> iter 9 value 757.370818
#> iter 9 value 757.370818
#> iter 9 value 757.370818
#> final value 757.370818
#> converged
#> This is Run number 164
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.54390249 -0.565560611 -4.843902 -2.2655606 2
#> 2 1 -1.35 -13.20 0.04908881 3.820259418 -1.300911 -9.3797406 1
#> 3 1 -2.05 -14.20 0.52040843 -0.397035930 -1.529592 -14.5970359 1
#> 4 1 -1.55 -3.10 2.90350648 3.370612430 1.353506 0.2706124 1
#> 5 1 -1.90 -3.60 0.23727503 -0.009881966 -1.662725 -3.6098820 1
#> 6 1 -13.70 -1.85 -0.85867994 -0.497993298 -14.558680 -2.3479933 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3120 -34675 9600
#> initial value 998.131940
#> iter 2 value 847.669262
#> iter 3 value 829.428505
#> iter 4 value 828.031104
#> iter 5 value 790.179806
#> iter 6 value 784.284452
#> iter 7 value 783.551598
#> iter 8 value 783.536178
#> iter 9 value 783.536079
#> iter 9 value 783.536079
#> iter 9 value 783.536079
#> final value 783.536079
#> converged
#> This is Run number 165
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.70254417 0.6294400 -3.59745583 -1.070560 2
#> 2 1 -1.35 -13.20 -1.29549777 0.1376457 -2.64549777 -13.062354 1
#> 3 1 -2.05 -14.20 0.09472869 -0.1178696 -1.95527131 -14.317870 1
#> 4 1 -1.55 -3.10 4.09859345 -1.1345420 2.54859345 -4.234542 1
#> 5 1 -1.90 -3.60 1.96390871 0.9188891 0.06390871 -2.681111 1
#> 6 1 -13.70 -1.85 -1.00493876 -0.8327750 -14.70493876 -2.682775 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4340 -35200 8375
#> initial value 998.131940
#> iter 2 value 850.467432
#> iter 3 value 837.658207
#> iter 4 value 837.198937
#> iter 5 value 800.326803
#> iter 6 value 793.819389
#> iter 7 value 792.778752
#> iter 8 value 792.756017
#> iter 9 value 792.755862
#> iter 9 value 792.755855
#> iter 9 value 792.755855
#> final value 792.755855
#> converged
#> This is Run number 166
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.7517101 0.5850307 -5.05171008 -1.114969 2
#> 2 1 -1.35 -13.20 -0.7826001 -0.2627959 -2.13260013 -13.462796 1
#> 3 1 -2.05 -14.20 -0.5110655 -0.6066667 -2.56106551 -14.806667 1
#> 4 1 -1.55 -3.10 1.6008110 0.4971726 0.05081103 -2.602827 1
#> 5 1 -1.90 -3.60 -0.1822176 0.2137232 -2.08221758 -3.386277 1
#> 6 1 -13.70 -1.85 0.7623154 -0.4863584 -12.93768455 -2.336358 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3800 -37225 9700
#> initial value 998.131940
#> iter 2 value 814.225290
#> iter 3 value 796.180085
#> iter 4 value 794.691590
#> iter 5 value 761.508039
#> iter 6 value 754.932547
#> iter 7 value 754.149609
#> iter 8 value 754.124514
#> iter 9 value 754.124360
#> iter 10 value 754.124333
#> iter 11 value 754.124303
#> iter 11 value 754.124293
#> iter 11 value 754.124293
#> final value 754.124293
#> converged
#> This is Run number 167
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.687125589 -0.54884190 -4.9871256 -2.248842 2
#> 2 1 -1.35 -13.20 1.644439722 1.57048508 0.2944397 -11.629515 1
#> 3 1 -2.05 -14.20 0.007314424 2.58595129 -2.0426856 -11.614049 1
#> 4 1 -1.55 -3.10 -0.924010326 0.06701443 -2.4740103 -3.032986 1
#> 5 1 -1.90 -3.60 1.239361257 0.44815801 -0.6606387 -3.151842 1
#> 6 1 -13.70 -1.85 0.350409610 -0.52891062 -13.3495904 -2.378911 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2820 -36075 10625
#> initial value 998.131940
#> iter 2 value 821.651197
#> iter 3 value 799.014671
#> iter 4 value 796.854291
#> iter 5 value 761.223135
#> iter 6 value 755.467193
#> iter 7 value 754.830024
#> iter 8 value 754.809308
#> iter 9 value 754.809241
#> iter 10 value 754.809216
#> iter 10 value 754.809207
#> iter 10 value 754.809207
#> final value 754.809207
#> converged
#> This is Run number 168
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.1860476 2.0838273 -4.11395242 0.3838273 2
#> 2 1 -1.35 -13.20 0.1308181 0.4258730 -1.21918191 -12.7741270 1
#> 3 1 -2.05 -14.20 2.0543668 0.1551497 0.00436680 -14.0448503 1
#> 4 1 -1.55 -3.10 1.6470476 0.3887544 0.09704755 -2.7112456 1
#> 5 1 -1.90 -3.60 -0.6499454 -0.1549246 -2.54994541 -3.7549246 1
#> 6 1 -13.70 -1.85 -0.7261210 -0.2285042 -14.42612099 -2.0785042 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3880 -39275 10650
#> initial value 998.131940
#> iter 2 value 776.339027
#> iter 3 value 754.846960
#> iter 4 value 753.144926
#> iter 5 value 724.167608
#> iter 6 value 718.123039
#> iter 7 value 717.435381
#> iter 8 value 717.395035
#> iter 9 value 717.394909
#> iter 10 value 717.394841
#> iter 11 value 717.394726
#> iter 12 value 717.394566
#> iter 12 value 717.394566
#> iter 12 value 717.394566
#> final value 717.394566
#> converged
#> This is Run number 169
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.3218137 -1.47060485 -1.978186 -3.1706049 1
#> 2 1 -1.35 -13.20 -0.4240442 0.29122417 -1.774044 -12.9087758 1
#> 3 1 -2.05 -14.20 0.4566131 0.06074565 -1.593387 -14.1392543 1
#> 4 1 -1.55 -3.10 -1.1913050 -0.37725120 -2.741305 -3.4772512 1
#> 5 1 -1.90 -3.60 -0.3905193 -0.94006397 -2.290519 -4.5400640 1
#> 6 1 -13.70 -1.85 0.4084648 2.01004693 -13.291535 0.1600469 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3700 -35300 10375
#> initial value 998.131940
#> iter 2 value 834.733017
#> iter 3 value 815.103841
#> iter 4 value 814.866648
#> iter 5 value 780.177622
#> iter 6 value 774.367355
#> iter 7 value 773.816040
#> iter 8 value 773.803713
#> iter 9 value 773.803640
#> iter 10 value 773.803590
#> iter 11 value 773.803528
#> iter 12 value 773.803502
#> iter 12 value 773.803502
#> iter 12 value 773.803502
#> final value 773.803502
#> converged
#> This is Run number 170
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.6883640 0.1986114 -3.6116360 -1.501389 2
#> 2 1 -1.35 -13.20 0.3794280 0.4964047 -0.9705720 -12.703595 1
#> 3 1 -2.05 -14.20 0.8451013 -0.1349292 -1.2048987 -14.334929 1
#> 4 1 -1.55 -3.10 0.9385732 1.3855590 -0.6114268 -1.714441 1
#> 5 1 -1.90 -3.60 -0.0462070 1.7496606 -1.9462070 -1.850339 2
#> 6 1 -13.70 -1.85 2.2360499 -0.5093341 -11.4639501 -2.359334 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3200 -37325 10150
#> initial value 998.131940
#> iter 2 value 808.765017
#> iter 3 value 787.955403
#> iter 4 value 785.229017
#> iter 5 value 751.142955
#> iter 6 value 744.864185
#> iter 7 value 744.105735
#> iter 8 value 744.077401
#> iter 9 value 744.077340
#> iter 10 value 744.077326
#> iter 10 value 744.077325
#> iter 10 value 744.077322
#> final value 744.077322
#> converged
#> This is Run number 171
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.7551436 0.5702066 -1.5448564 -1.129793 2
#> 2 1 -1.35 -13.20 -0.5380813 -0.5517408 -1.8880813 -13.751741 1
#> 3 1 -2.05 -14.20 0.8903767 1.4311234 -1.1596233 -12.768877 1
#> 4 1 -1.55 -3.10 0.2804007 1.1265537 -1.2695993 -1.973446 1
#> 5 1 -1.90 -3.60 1.3776705 1.7571482 -0.5223295 -1.842852 1
#> 6 1 -13.70 -1.85 -0.2537020 0.8067950 -13.9537020 -1.043205 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4080 -36750 9175
#> initial value 998.131940
#> iter 2 value 824.772859
#> iter 3 value 808.928835
#> iter 4 value 807.879286
#> iter 5 value 773.896742
#> iter 6 value 767.162017
#> iter 7 value 766.280762
#> iter 8 value 766.256446
#> iter 9 value 766.256245
#> iter 10 value 766.256216
#> iter 11 value 766.256182
#> iter 12 value 766.256155
#> iter 12 value 766.256155
#> iter 12 value 766.256155
#> final value 766.256155
#> converged
#> This is Run number 172
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.5675754 -0.5549022 -4.8675754 -2.2549022 2
#> 2 1 -1.35 -13.20 1.2723816 -0.1133845 -0.0776184 -13.3133845 1
#> 3 1 -2.05 -14.20 0.4230666 0.5626142 -1.6269334 -13.6373858 1
#> 4 1 -1.55 -3.10 -0.2925090 2.3590748 -1.8425090 -0.7409252 2
#> 5 1 -1.90 -3.60 -1.6211338 0.5334014 -3.5211338 -3.0665986 2
#> 6 1 -13.70 -1.85 -0.8336904 1.8854298 -14.5336904 0.0354298 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4000 -36675 9775
#> initial value 998.131940
#> iter 2 value 821.463080
#> iter 3 value 803.809408
#> iter 4 value 803.145993
#> iter 5 value 769.702963
#> iter 6 value 763.248088
#> iter 7 value 762.527971
#> iter 8 value 762.507619
#> iter 9 value 762.507465
#> iter 10 value 762.507421
#> iter 11 value 762.507360
#> iter 12 value 762.507334
#> iter 12 value 762.507334
#> iter 12 value 762.507334
#> final value 762.507334
#> converged
#> This is Run number 173
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.9167209 2.3815461 -5.216721 0.6815461 2
#> 2 1 -1.35 -13.20 -0.7473570 0.4171020 -2.097357 -12.7828980 1
#> 3 1 -2.05 -14.20 -0.7828672 0.9482268 -2.832867 -13.2517732 1
#> 4 1 -1.55 -3.10 -0.2258321 0.5302622 -1.775832 -2.5697378 1
#> 5 1 -1.90 -3.60 -0.1730882 0.2377881 -2.073088 -3.3622119 1
#> 6 1 -13.70 -1.85 0.6180101 -1.3245748 -13.081990 -3.1745748 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3420 -36700 9550
#> initial value 998.131940
#> iter 2 value 822.223068
#> iter 3 value 803.940151
#> iter 4 value 801.713176
#> iter 5 value 766.599998
#> iter 6 value 760.078000
#> iter 7 value 759.238531
#> iter 8 value 759.214184
#> iter 9 value 759.214061
#> iter 9 value 759.214053
#> iter 9 value 759.214049
#> final value 759.214049
#> converged
#> This is Run number 174
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.3024534 -0.7487084 -4.602453 -2.4487084 2
#> 2 1 -1.35 -13.20 -0.7292158 -0.5891232 -2.079216 -13.7891232 1
#> 3 1 -2.05 -14.20 0.1707288 2.3578953 -1.879271 -11.8421047 1
#> 4 1 -1.55 -3.10 0.2785784 2.5656753 -1.271422 -0.5343247 2
#> 5 1 -1.90 -3.60 1.2195860 2.6216117 -0.680414 -0.9783883 1
#> 6 1 -13.70 -1.85 0.1203971 -0.1773623 -13.579603 -2.0273623 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3500 -37700 9600
#> initial value 998.131940
#> iter 2 value 807.846767
#> iter 3 value 789.162471
#> iter 4 value 786.314642
#> iter 5 value 752.740536
#> iter 6 value 746.068331
#> iter 7 value 745.211996
#> iter 8 value 745.181836
#> iter 9 value 745.181762
#> iter 9 value 745.181758
#> iter 9 value 745.181758
#> final value 745.181758
#> converged
#> This is Run number 175
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.33448886 1.2715648 -4.6344889 -0.4284352 2
#> 2 1 -1.35 -13.20 -0.01739318 -1.0246145 -1.3673932 -14.2246145 1
#> 3 1 -2.05 -14.20 -0.26991324 1.0523884 -2.3199132 -13.1476116 1
#> 4 1 -1.55 -3.10 0.46090811 1.7260727 -1.0890919 -1.3739273 1
#> 5 1 -1.90 -3.60 2.59324147 -1.2307922 0.6932415 -4.8307922 1
#> 6 1 -13.70 -1.85 0.20883102 -0.6690217 -13.4911690 -2.5190217 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2940 -35800 9000
#> initial value 998.131940
#> iter 2 value 837.379734
#> iter 3 value 819.720891
#> iter 4 value 816.767593
#> iter 5 value 777.513415
#> iter 6 value 770.919960
#> iter 7 value 769.965606
#> iter 8 value 769.944298
#> iter 9 value 769.944248
#> iter 9 value 769.944245
#> iter 9 value 769.944244
#> final value 769.944244
#> converged
#> This is Run number 176
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -1.1560258 1.0077056 -5.45602584 -0.6922944 2
#> 2 1 -1.35 -13.20 -0.3342144 1.6419885 -1.68421443 -11.5580115 1
#> 3 1 -2.05 -14.20 1.6853173 -1.3910995 -0.36468270 -15.5910995 1
#> 4 1 -1.55 -3.10 -0.3232407 -0.4310688 -1.87324074 -3.5310688 1
#> 5 1 -1.90 -3.60 1.8261887 0.6257140 -0.07381127 -2.9742860 1
#> 6 1 -13.70 -1.85 2.2261287 0.7514136 -11.47387133 -1.0985864 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4240 -37825 8425
#> initial value 998.131940
#> iter 2 value 814.611095
#> iter 3 value 800.543587
#> iter 4 value 798.326608
#> iter 5 value 765.385340
#> iter 6 value 758.091837
#> iter 7 value 756.984369
#> iter 8 value 756.950782
#> iter 9 value 756.950574
#> iter 9 value 756.950563
#> iter 9 value 756.950557
#> final value 756.950557
#> converged
#> This is Run number 177
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 5.9091410 1.9862591 1.6091410 0.2862591 1
#> 2 1 -1.35 -13.20 2.1670669 -1.2576889 0.8170669 -14.4576889 1
#> 3 1 -2.05 -14.20 -0.8553610 -0.1320855 -2.9053610 -14.3320855 1
#> 4 1 -1.55 -3.10 1.0255556 -1.6160599 -0.5244444 -4.7160599 1
#> 5 1 -1.90 -3.60 -0.1216492 -0.8195609 -2.0216492 -4.4195609 1
#> 6 1 -13.70 -1.85 2.6218348 0.8499871 -11.0781652 -1.0000129 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3800 -37500 10025
#> initial value 998.131940
#> iter 2 value 807.893345
#> iter 3 value 788.805231
#> iter 4 value 787.470507
#> iter 5 value 755.100136
#> iter 6 value 748.655698
#> iter 7 value 747.938085
#> iter 8 value 747.912502
#> iter 9 value 747.912375
#> iter 10 value 747.912313
#> iter 11 value 747.912282
#> iter 11 value 747.912274
#> iter 11 value 747.912274
#> final value 747.912274
#> converged
#> This is Run number 178
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.41305013 1.30212408 -4.7130501 -0.3978759 2
#> 2 1 -1.35 -13.20 0.37988287 -0.02686327 -0.9701171 -13.2268633 1
#> 3 1 -2.05 -14.20 -0.10181085 -0.32887555 -2.1518108 -14.5288755 1
#> 4 1 -1.55 -3.10 0.03609279 2.38421541 -1.5139072 -0.7157846 2
#> 5 1 -1.90 -3.60 0.39277118 1.33919515 -1.5072288 -2.2608048 1
#> 6 1 -13.70 -1.85 2.10515657 0.33799726 -11.5948434 -1.5120027 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3880 -35500 9025
#> initial value 998.131940
#> iter 2 value 842.200972
#> iter 3 value 826.810349
#> iter 4 value 825.930728
#> iter 5 value 789.662331
#> iter 6 value 783.249001
#> iter 7 value 782.362153
#> iter 8 value 782.341875
#> iter 9 value 782.341722
#> iter 10 value 782.341692
#> iter 11 value 782.341654
#> iter 12 value 782.341630
#> iter 12 value 782.341630
#> iter 12 value 782.341630
#> final value 782.341630
#> converged
#> This is Run number 179
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.6203905 4.794670e-01 -4.9203905 -1.2205330 2
#> 2 1 -1.35 -13.20 1.9507350 -5.464110e-02 0.6007350 -13.2546411 1
#> 3 1 -2.05 -14.20 1.1882732 2.982391e+00 -0.8617268 -11.2176095 1
#> 4 1 -1.55 -3.10 0.7507229 -6.081534e-05 -0.7992771 -3.1000608 1
#> 5 1 -1.90 -3.60 1.7788164 1.705734e+00 -0.1211836 -1.8942662 1
#> 6 1 -13.70 -1.85 2.0366154 1.075935e+00 -11.6633846 -0.7740652 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4100 -35875 9125
#> initial value 998.131940
#> iter 2 value 836.829191
#> iter 3 value 821.454010
#> iter 4 value 820.846985
#> iter 5 value 785.588816
#> iter 6 value 779.078218
#> iter 7 value 778.220518
#> iter 8 value 778.200187
#> iter 9 value 778.200022
#> iter 10 value 778.199986
#> iter 11 value 778.199935
#> iter 12 value 778.199904
#> iter 12 value 778.199904
#> iter 12 value 778.199904
#> final value 778.199904
#> converged
#> This is Run number 180
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.2750944 -0.2011122 -3.0249056 -1.901112 2
#> 2 1 -1.35 -13.20 3.2433217 -1.2690831 1.8933217 -14.469083 1
#> 3 1 -2.05 -14.20 3.7303434 -1.1568889 1.6803434 -15.356889 1
#> 4 1 -1.55 -3.10 0.9281034 -1.2203946 -0.6218966 -4.320395 1
#> 5 1 -1.90 -3.60 0.9003070 -0.2313566 -0.9996930 -3.831357 1
#> 6 1 -13.70 -1.85 -0.2875892 3.7942561 -13.9875892 1.944256 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3660 -37750 8775
#> initial value 998.131940
#> iter 2 value 812.972594
#> iter 3 value 796.745998
#> iter 4 value 793.400357
#> iter 5 value 758.931927
#> iter 6 value 751.790611
#> iter 7 value 750.757318
#> iter 8 value 750.726428
#> iter 9 value 750.726372
#> iter 9 value 750.726372
#> iter 9 value 750.726372
#> final value 750.726372
#> converged
#> This is Run number 181
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.05180097 -0.597179920 -4.24819903 -2.297180 2
#> 2 1 -1.35 -13.20 1.75636947 4.323805255 0.40636947 -8.876195 1
#> 3 1 -2.05 -14.20 2.08267653 -0.008626623 0.03267653 -14.208627 1
#> 4 1 -1.55 -3.10 -0.64107554 0.096048610 -2.19107554 -3.003951 1
#> 5 1 -1.90 -3.60 0.55710323 0.096010421 -1.34289677 -3.503990 1
#> 6 1 -13.70 -1.85 0.33381672 -1.071087269 -13.36618328 -2.921087 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4720 -36100 8550
#> initial value 998.131940
#> iter 2 value 837.881389
#> iter 3 value 824.970518
#> iter 4 value 824.773721
#> iter 5 value 789.907653
#> iter 6 value 783.116293
#> iter 7 value 782.119585
#> iter 8 value 782.095984
#> iter 9 value 782.095802
#> iter 10 value 782.095755
#> iter 11 value 782.095685
#> iter 12 value 782.095645
#> iter 12 value 782.095645
#> iter 12 value 782.095645
#> final value 782.095645
#> converged
#> This is Run number 182
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.7081670 0.1229209 -5.0081670 -1.5770791 2
#> 2 1 -1.35 -13.20 0.1986898 -0.3736209 -1.1513102 -13.5736209 1
#> 3 1 -2.05 -14.20 1.1498814 -0.4211925 -0.9001186 -14.6211925 1
#> 4 1 -1.55 -3.10 2.2118599 3.7871190 0.6618599 0.6871190 2
#> 5 1 -1.90 -3.60 0.2495999 0.9666152 -1.6504001 -2.6333848 1
#> 6 1 -13.70 -1.85 -1.0634148 1.0455493 -14.7634148 -0.8044507 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4000 -38325 8875
#> initial value 998.131940
#> iter 2 value 804.144987
#> iter 3 value 788.245081
#> iter 4 value 785.412770
#> iter 5 value 753.196640
#> iter 6 value 746.034328
#> iter 7 value 745.045788
#> iter 8 value 745.012190
#> iter 9 value 745.012089
#> iter 9 value 745.012086
#> iter 9 value 745.012085
#> final value 745.012085
#> converged
#> This is Run number 183
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.6786124 1.0952084 -2.6213876 -0.6047916 2
#> 2 1 -1.35 -13.20 1.4825373 -0.4378220 0.1325373 -13.6378220 1
#> 3 1 -2.05 -14.20 -0.4695484 -0.6036841 -2.5195484 -14.8036841 1
#> 4 1 -1.55 -3.10 0.6961639 -0.4794538 -0.8538361 -3.5794538 1
#> 5 1 -1.90 -3.60 2.6250005 0.4891226 0.7250005 -3.1108774 1
#> 6 1 -13.70 -1.85 -0.3813021 -1.0028558 -14.0813021 -2.8528558 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3480 -34350 9350
#> initial value 998.131940
#> iter 2 value 853.776654
#> iter 3 value 837.129536
#> iter 4 value 836.357016
#> iter 5 value 798.638299
#> iter 6 value 792.756748
#> iter 7 value 792.012406
#> iter 8 value 791.998110
#> iter 9 value 791.998013
#> iter 9 value 791.998013
#> iter 9 value 791.998013
#> final value 791.998013
#> converged
#> This is Run number 184
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 3.1407123 0.4640146 -1.159288 -1.2359854 1
#> 2 1 -1.35 -13.20 -1.2726190 0.4662695 -2.622619 -12.7337305 1
#> 3 1 -2.05 -14.20 0.3264553 0.3680698 -1.723545 -13.8319302 1
#> 4 1 -1.55 -3.10 0.3364961 0.3373544 -1.213504 -2.7626456 1
#> 5 1 -1.90 -3.60 -0.3338210 1.1613846 -2.233821 -2.4386154 1
#> 6 1 -13.70 -1.85 -0.1988117 1.7433209 -13.898812 -0.1066791 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3160 -36125 9275
#> initial value 998.131940
#> iter 2 value 831.575299
#> iter 3 value 813.643333
#> iter 4 value 811.006545
#> iter 5 value 773.793573
#> iter 6 value 767.273635
#> iter 7 value 766.373921
#> iter 8 value 766.351253
#> iter 9 value 766.351162
#> iter 9 value 766.351157
#> iter 9 value 766.351155
#> final value 766.351155
#> converged
#> This is Run number 185
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.6093211 0.17051051 -4.909321 -1.5294895 2
#> 2 1 -1.35 -13.20 -1.0247440 -0.87585833 -2.374744 -14.0758583 1
#> 3 1 -2.05 -14.20 -0.1207013 1.23401130 -2.170701 -12.9659887 1
#> 4 1 -1.55 -3.10 0.3946978 -0.82252641 -1.155302 -3.9225264 1
#> 5 1 -1.90 -3.60 0.9873590 -0.02472111 -0.912641 -3.6247211 1
#> 6 1 -13.70 -1.85 -1.0253997 1.39791222 -14.725400 -0.4520878 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3780 -36200 8925
#> initial value 998.131940
#> iter 2 value 833.674668
#> iter 3 value 818.073852
#> iter 4 value 816.485358
#> iter 5 value 780.724106
#> iter 6 value 774.048599
#> iter 7 value 773.087242
#> iter 8 value 773.062810
#> iter 9 value 773.062636
#> iter 10 value 773.062618
#> iter 11 value 773.062604
#> iter 12 value 773.062591
#> iter 12 value 773.062591
#> iter 12 value 773.062591
#> final value 773.062591
#> converged
#> This is Run number 186
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 3.59899037 0.09841625 -0.7010096 -1.6015838 1
#> 2 1 -1.35 -13.20 0.35889509 1.77188836 -0.9911049 -11.4281116 1
#> 3 1 -2.05 -14.20 -0.79238620 1.43786638 -2.8423862 -12.7621336 1
#> 4 1 -1.55 -3.10 2.30875323 2.26190276 0.7587532 -0.8380972 1
#> 5 1 -1.90 -3.60 -0.38213279 0.95117891 -2.2821328 -2.6488211 1
#> 6 1 -13.70 -1.85 0.07142748 5.46219756 -13.6285725 3.6121976 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3440 -37450 9725
#> initial value 998.131940
#> iter 2 value 810.470765
#> iter 3 value 791.414090
#> iter 4 value 788.775453
#> iter 5 value 754.909216
#> iter 6 value 748.343943
#> iter 7 value 747.517883
#> iter 8 value 747.489426
#> iter 9 value 747.489342
#> iter 9 value 747.489335
#> iter 9 value 747.489335
#> final value 747.489335
#> converged
#> This is Run number 187
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -1.30726852 2.7439550 -5.6072685 1.043955 2
#> 2 1 -1.35 -13.20 2.79732421 0.8612413 1.4473242 -12.338759 1
#> 3 1 -2.05 -14.20 -0.07355559 -1.0981094 -2.1235556 -15.298109 1
#> 4 1 -1.55 -3.10 2.02199609 0.5251783 0.4719961 -2.574822 1
#> 5 1 -1.90 -3.60 0.79742189 1.1033913 -1.1025781 -2.496609 1
#> 6 1 -13.70 -1.85 3.03844165 0.4346536 -10.6615584 -1.415346 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3980 -38250 10000
#> initial value 998.131940
#> iter 2 value 797.251196
#> iter 3 value 778.340303
#> iter 4 value 776.913460
#> iter 5 value 745.978570
#> iter 6 value 739.434960
#> iter 7 value 738.707180
#> iter 8 value 738.677283
#> iter 9 value 738.677172
#> iter 10 value 738.677086
#> iter 10 value 738.677085
#> iter 11 value 738.677074
#> iter 12 value 738.677053
#> iter 12 value 738.677053
#> iter 12 value 738.677051
#> final value 738.677051
#> converged
#> This is Run number 188
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.6129259 0.7336342 -2.6870741 -0.9663658 2
#> 2 1 -1.35 -13.20 0.4348537 1.1964967 -0.9151463 -12.0035033 1
#> 3 1 -2.05 -14.20 0.7571323 -0.2164358 -1.2928677 -14.4164358 1
#> 4 1 -1.55 -3.10 -0.8274327 1.9482812 -2.3774327 -1.1517188 2
#> 5 1 -1.90 -3.60 -0.5047487 2.6222057 -2.4047487 -0.9777943 2
#> 6 1 -13.70 -1.85 0.3936458 -1.0548469 -13.3063542 -2.9048469 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4360 -37200 9550
#> initial value 998.131940
#> iter 2 value 816.007002
#> iter 3 value 799.498965
#> iter 4 value 799.047470
#> iter 5 value 766.663452
#> iter 6 value 759.959985
#> iter 7 value 759.206662
#> iter 8 value 759.184378
#> iter 9 value 759.184200
#> iter 10 value 759.184151
#> iter 11 value 759.184078
#> iter 12 value 759.184040
#> iter 12 value 759.184040
#> iter 12 value 759.184040
#> final value 759.184040
#> converged
#> This is Run number 189
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.2199693 -0.3121518 -4.0800307 -2.0121518 2
#> 2 1 -1.35 -13.20 -0.6080093 -0.8955600 -1.9580093 -14.0955600 1
#> 3 1 -2.05 -14.20 1.8253322 -0.5177120 -0.2246678 -14.7177120 1
#> 4 1 -1.55 -3.10 2.1693733 1.5314840 0.6193733 -1.5685160 1
#> 5 1 -1.90 -3.60 2.4540024 1.7316114 0.5540024 -1.8683886 1
#> 6 1 -13.70 -1.85 1.8091803 1.2261274 -11.8908197 -0.6238726 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3920 -36850 9325
#> initial value 998.131940
#> iter 2 value 822.243440
#> iter 3 value 805.634707
#> iter 4 value 804.309539
#> iter 5 value 770.352032
#> iter 6 value 763.665870
#> iter 7 value 762.809118
#> iter 8 value 762.784664
#> iter 9 value 762.784478
#> iter 9 value 762.784474
#> iter 9 value 762.784474
#> final value 762.784474
#> converged
#> This is Run number 190
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -1.05671021 0.7887981 -5.35671021 -0.9112019 2
#> 2 1 -1.35 -13.20 1.40840175 0.2952238 0.05840175 -12.9047762 1
#> 3 1 -2.05 -14.20 -0.45006073 -0.2033161 -2.50006073 -14.4033161 1
#> 4 1 -1.55 -3.10 0.24451886 0.4081298 -1.30548114 -2.6918702 1
#> 5 1 -1.90 -3.60 -0.00451944 1.0132895 -1.90451944 -2.5867105 1
#> 6 1 -13.70 -1.85 -0.43544900 0.3372493 -14.13544900 -1.5127507 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4480 -37850 8975
#> initial value 998.131940
#> iter 2 value 810.762551
#> iter 3 value 795.831734
#> iter 4 value 794.805716
#> iter 5 value 763.065311
#> iter 6 value 755.991584
#> iter 7 value 755.072736
#> iter 8 value 755.043376
#> iter 9 value 755.043126
#> iter 9 value 755.043122
#> iter 9 value 755.043122
#> final value 755.043122
#> converged
#> This is Run number 191
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -1.1069447 -0.861687483 -5.4069447 -2.561687 2
#> 2 1 -1.35 -13.20 0.2553841 -0.707188296 -1.0946159 -13.907188 1
#> 3 1 -2.05 -14.20 -0.2121117 2.075910375 -2.2621117 -12.124090 1
#> 4 1 -1.55 -3.10 3.7337367 0.001262785 2.1837367 -3.098737 1
#> 5 1 -1.90 -3.60 1.0879589 0.940551295 -0.8120411 -2.659449 1
#> 6 1 -13.70 -1.85 -0.3692787 0.100683897 -14.0692787 -1.749316 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3740 -36100 9250
#> initial value 998.131940
#> iter 2 value 832.754483
#> iter 3 value 816.258740
#> iter 4 value 814.945567
#> iter 5 value 779.481933
#> iter 6 value 772.968803
#> iter 7 value 772.103953
#> iter 8 value 772.082009
#> iter 9 value 772.081844
#> iter 10 value 772.081821
#> iter 11 value 772.081797
#> iter 12 value 772.081779
#> iter 12 value 772.081779
#> iter 12 value 772.081779
#> final value 772.081779
#> converged
#> This is Run number 192
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.889643 0.9384426 -2.4103572 -0.7615574 2
#> 2 1 -1.35 -13.20 -0.949384 0.2556187 -2.2993840 -12.9443813 1
#> 3 1 -2.05 -14.20 2.854072 -1.2586145 0.8040723 -15.4586145 1
#> 4 1 -1.55 -3.10 2.437909 0.6618152 0.8879086 -2.4381848 1
#> 5 1 -1.90 -3.60 3.340676 0.5870149 1.4406755 -3.0129851 1
#> 6 1 -13.70 -1.85 -0.640695 1.3391416 -14.3406950 -0.5108584 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3900 -36000 8450
#> initial value 998.131940
#> iter 2 value 839.497235
#> iter 3 value 825.401179
#> iter 4 value 823.789590
#> iter 5 value 787.293903
#> iter 6 value 780.508610
#> iter 7 value 779.414525
#> iter 8 value 779.387493
#> iter 9 value 779.387312
#> iter 10 value 779.387297
#> iter 11 value 779.387285
#> iter 11 value 779.387274
#> iter 11 value 779.387274
#> final value 779.387274
#> converged
#> This is Run number 193
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.1296655 0.6655227 -4.170334 -1.0344773 2
#> 2 1 -1.35 -13.20 -1.4871635 4.6415182 -2.837164 -8.5584818 1
#> 3 1 -2.05 -14.20 -0.5602957 0.5461292 -2.610296 -13.6538708 1
#> 4 1 -1.55 -3.10 -0.8780385 1.2543267 -2.428038 -1.8456733 2
#> 5 1 -1.90 -3.60 -0.1904855 0.6535269 -2.090486 -2.9464731 1
#> 6 1 -13.70 -1.85 -0.5289239 1.2634729 -14.228924 -0.5865271 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4040 -39025 10500
#> initial value 998.131940
#> iter 2 value 781.584093
#> iter 3 value 761.011107
#> iter 4 value 759.769513
#> iter 5 value 730.643490
#> iter 6 value 724.433244
#> iter 7 value 723.762928
#> iter 8 value 723.727403
#> iter 9 value 723.727290
#> iter 10 value 723.727141
#> iter 11 value 723.727036
#> iter 12 value 723.726936
#> iter 12 value 723.726936
#> iter 12 value 723.726936
#> final value 723.726936
#> converged
#> This is Run number 194
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -1.23919641 0.60915743 -5.5391964 -1.0908426 2
#> 2 1 -1.35 -13.20 0.43757217 2.23971977 -0.9124278 -10.9602802 1
#> 3 1 -2.05 -14.20 0.08422347 0.06815142 -1.9657765 -14.1318486 1
#> 4 1 -1.55 -3.10 1.76689821 -1.20261414 0.2168982 -4.3026141 1
#> 5 1 -1.90 -3.60 -0.45387017 -0.32362583 -2.3538702 -3.9236258 1
#> 6 1 -13.70 -1.85 2.25799764 1.36106535 -11.4420024 -0.4889346 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3460 -37250 9825
#> initial value 998.131940
#> iter 2 value 812.606380
#> iter 3 value 793.413501
#> iter 4 value 791.130548
#> iter 5 value 757.259102
#> iter 6 value 750.776992
#> iter 7 value 749.983704
#> iter 8 value 749.956989
#> iter 9 value 749.956886
#> iter 10 value 749.956873
#> iter 11 value 749.956861
#> iter 11 value 749.956859
#> iter 11 value 749.956859
#> final value 749.956859
#> converged
#> This is Run number 195
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.1640563 0.4698106 -3.1359437 -1.230189 2
#> 2 1 -1.35 -13.20 0.3050833 0.5720567 -1.0449167 -12.627943 1
#> 3 1 -2.05 -14.20 1.9473024 0.6651328 -0.1026976 -13.534867 1
#> 4 1 -1.55 -3.10 -0.7709440 0.4254145 -2.3209440 -2.674585 1
#> 5 1 -1.90 -3.60 2.6084016 -0.2851632 0.7084016 -3.885163 1
#> 6 1 -13.70 -1.85 0.2317721 -0.9962865 -13.4682279 -2.846286 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3320 -35725 9175
#> initial value 998.131940
#> iter 2 value 837.726141
#> iter 3 value 820.641548
#> iter 4 value 818.597218
#> iter 5 value 781.400045
#> iter 6 value 774.964076
#> iter 7 value 774.068382
#> iter 8 value 774.047010
#> iter 9 value 774.046888
#> iter 9 value 774.046878
#> iter 9 value 774.046874
#> final value 774.046874
#> converged
#> This is Run number 196
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.59075958 0.6728028 -4.8907596 -1.027197 2
#> 2 1 -1.35 -13.20 -0.11832924 -0.4226595 -1.4683292 -13.622659 1
#> 3 1 -2.05 -14.20 1.94149976 0.1506505 -0.1085002 -14.049349 1
#> 4 1 -1.55 -3.10 0.70123885 0.8262083 -0.8487611 -2.273792 1
#> 5 1 -1.90 -3.60 0.77790346 1.7306000 -1.1220965 -1.869400 1
#> 6 1 -13.70 -1.85 -0.05011674 0.2597037 -13.7501167 -1.590296 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3540 -35725 9525
#> initial value 998.131940
#> iter 2 value 835.532202
#> iter 3 value 818.004039
#> iter 4 value 816.742454
#> iter 5 value 780.823187
#> iter 6 value 774.543344
#> iter 7 value 773.756076
#> iter 8 value 773.736869
#> iter 9 value 773.736729
#> iter 9 value 773.736726
#> iter 9 value 773.736726
#> final value 773.736726
#> converged
#> This is Run number 197
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.4112906 0.1414411 -3.888709380 -1.558559 2
#> 2 1 -1.35 -13.20 1.7645593 0.6163383 0.414559328 -12.583662 1
#> 3 1 -2.05 -14.20 -0.1358423 0.6371863 -2.185842271 -13.562814 1
#> 4 1 -1.55 -3.10 3.3842107 -0.7890904 1.834210730 -3.889090 1
#> 5 1 -1.90 -3.60 1.9037510 -0.3234435 0.003751003 -3.923443 1
#> 6 1 -13.70 -1.85 -0.5284044 -0.1326573 -14.228404420 -1.982657 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3560 -38650 10350
#> initial value 998.131940
#> iter 2 value 788.125143
#> iter 3 value 767.035810
#> iter 4 value 764.443993
#> iter 5 value 733.411191
#> iter 6 value 727.159537
#> iter 7 value 726.418306
#> iter 8 value 726.380807
#> iter 9 value 726.380747
#> iter 10 value 726.380698
#> iter 11 value 726.380650
#> iter 12 value 726.380632
#> iter 12 value 726.380632
#> iter 12 value 726.380632
#> final value 726.380632
#> converged
#> This is Run number 198
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.30103959 -0.3168884 -3.99896041 -2.016888 2
#> 2 1 -1.35 -13.20 1.30331404 1.1350711 -0.04668596 -12.064929 1
#> 3 1 -2.05 -14.20 -0.88678508 -0.3365831 -2.93678508 -14.536583 1
#> 4 1 -1.55 -3.10 -0.09690847 0.5947993 -1.64690847 -2.505201 1
#> 5 1 -1.90 -3.60 0.41753533 -0.4545796 -1.48246467 -4.054580 1
#> 6 1 -13.70 -1.85 0.42528055 0.7382519 -13.27471945 -1.111748 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3820 -35975 8925
#> initial value 998.131940
#> iter 2 value 836.681547
#> iter 3 value 821.255252
#> iter 4 value 819.903485
#> iter 5 value 783.951575
#> iter 6 value 777.347392
#> iter 7 value 776.398890
#> iter 8 value 776.375485
#> iter 9 value 776.375312
#> iter 10 value 776.375291
#> iter 11 value 776.375270
#> iter 12 value 776.375253
#> iter 12 value 776.375253
#> iter 12 value 776.375253
#> final value 776.375253
#> converged
#> This is Run number 199
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.99682657 0.4409783 -2.3031734 -1.259022 2
#> 2 1 -1.35 -13.20 2.19257267 1.2190909 0.8425727 -11.980909 1
#> 3 1 -2.05 -14.20 0.02250784 0.3611862 -2.0274922 -13.838814 1
#> 4 1 -1.55 -3.10 -0.38788523 5.1885497 -1.9378852 2.088550 2
#> 5 1 -1.90 -3.60 0.32270111 -0.1474153 -1.5772989 -3.747415 1
#> 6 1 -13.70 -1.85 -0.16394863 0.4029355 -13.8639486 -1.447064 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3400 -36000 10075
#> initial value 998.131940
#> iter 2 value 827.737808
#> iter 3 value 808.206384
#> iter 4 value 806.962259
#> iter 5 value 771.931953
#> iter 6 value 765.839274
#> iter 7 value 765.157376
#> iter 8 value 765.138795
#> iter 9 value 765.138676
#> iter 10 value 765.138646
#> iter 11 value 765.138610
#> iter 12 value 765.138598
#> iter 12 value 765.138598
#> iter 12 value 765.138598
#> final value 765.138598
#> converged
#> This is Run number 200
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.14583210 -0.6488895 -4.44583210 -2.348889 2
#> 2 1 -1.35 -13.20 1.32112762 0.3753014 -0.02887238 -12.824699 1
#> 3 1 -2.05 -14.20 0.84925061 -0.1032309 -1.20074939 -14.303231 1
#> 4 1 -1.55 -3.10 1.65096109 -0.1975839 0.10096109 -3.297584 1
#> 5 1 -1.90 -3.60 0.36575507 -0.2223931 -1.53424493 -3.822393 1
#> 6 1 -13.70 -1.85 -0.09903494 -0.1497176 -13.79903494 -1.999718 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3780 -38050 8375
#> initial value 998.131940
#> iter 2 value 811.252800
#> iter 3 value 796.085579
#> iter 4 value 792.409926
#> iter 5 value 757.947912
#> iter 6 value 750.544233
#> iter 7 value 749.429719
#> iter 8 value 749.397696
#> iter 9 value 749.397673
#> iter 9 value 749.397665
#> iter 9 value 749.397664
#> final value 749.397664
#> converged
#> This is Run number 201
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.6533260 0.6452891 -4.9533260 -1.0547109 2
#> 2 1 -1.35 -13.20 2.7881885 -1.0209463 1.4381885 -14.2209463 1
#> 3 1 -2.05 -14.20 1.3812093 0.9460280 -0.6687907 -13.2539720 1
#> 4 1 -1.55 -3.10 0.2285581 2.4001456 -1.3214419 -0.6998544 2
#> 5 1 -1.90 -3.60 -0.6076161 -0.6550816 -2.5076161 -4.2550816 1
#> 6 1 -13.70 -1.85 -0.2827257 0.2134240 -13.9827257 -1.6365760 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3920 -36100 8750
#> initial value 998.131940
#> iter 2 value 836.271203
#> iter 3 value 821.446526
#> iter 4 value 820.072587
#> iter 5 value 784.239522
#> iter 6 value 777.531959
#> iter 7 value 776.529810
#> iter 8 value 776.504697
#> iter 9 value 776.504512
#> iter 10 value 776.504491
#> iter 11 value 776.504471
#> iter 12 value 776.504454
#> iter 12 value 776.504454
#> iter 12 value 776.504454
#> final value 776.504454
#> converged
#> This is Run number 202
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.5646966 1.579859 -2.7353034 -0.120141204 2
#> 2 1 -1.35 -13.20 -1.2765367 -0.458419 -2.6265367 -13.658419004 1
#> 3 1 -2.05 -14.20 -0.8204197 3.942049 -2.8704197 -10.257951172 1
#> 4 1 -1.55 -3.10 1.0276787 3.097936 -0.5223213 -0.002064339 2
#> 5 1 -1.90 -3.60 0.3627660 3.259284 -1.5372340 -0.340716411 2
#> 6 1 -13.70 -1.85 0.3475239 1.479565 -13.3524761 -0.370435097 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3420 -36775 9200
#> initial value 998.131940
#> iter 2 value 823.647216
#> iter 3 value 806.251432
#> iter 4 value 803.605374
#> iter 5 value 767.909157
#> iter 6 value 761.188727
#> iter 7 value 760.260245
#> iter 8 value 760.234500
#> iter 9 value 760.234393
#> iter 9 value 760.234388
#> iter 9 value 760.234386
#> final value 760.234386
#> converged
#> This is Run number 203
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.66183800 7.37159108 -4.9618380 5.671591 2
#> 2 1 -1.35 -13.20 0.08693553 0.37182639 -1.2630645 -12.828174 1
#> 3 1 -2.05 -14.20 0.64161445 -0.36128472 -1.4083856 -14.561285 1
#> 4 1 -1.55 -3.10 0.04400015 -0.20457514 -1.5059998 -3.304575 1
#> 5 1 -1.90 -3.60 1.50554365 2.52569099 -0.3944564 -1.074309 1
#> 6 1 -13.70 -1.85 0.59155072 0.07954644 -13.1084493 -1.770454 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4000 -36525 9700
#> initial value 998.131940
#> iter 2 value 824.055657
#> iter 3 value 806.669893
#> iter 4 value 806.019091
#> iter 5 value 772.270787
#> iter 6 value 765.815912
#> iter 7 value 765.082586
#> iter 8 value 765.062599
#> iter 9 value 765.062443
#> iter 10 value 765.062409
#> iter 11 value 765.062351
#> iter 12 value 765.062315
#> iter 12 value 765.062315
#> iter 12 value 765.062315
#> final value 765.062315
#> converged
#> This is Run number 204
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.5252422 -1.05338328 -4.8252422 -2.753383 2
#> 2 1 -1.35 -13.20 1.8106731 2.79849118 0.4606731 -10.401509 1
#> 3 1 -2.05 -14.20 0.2018736 -0.06624084 -1.8481264 -14.266241 1
#> 4 1 -1.55 -3.10 1.8042200 -0.13020604 0.2542200 -3.230206 1
#> 5 1 -1.90 -3.60 1.0637271 1.65209518 -0.8362729 -1.947905 1
#> 6 1 -13.70 -1.85 -0.6483979 3.09616050 -14.3483979 1.246161 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3100 -35125 9900
#> initial value 998.131940
#> iter 2 value 839.903628
#> iter 3 value 820.566677
#> iter 4 value 819.082398
#> iter 5 value 782.134583
#> iter 6 value 776.224171
#> iter 7 value 775.527625
#> iter 8 value 775.511444
#> iter 9 value 775.511342
#> iter 9 value 775.511335
#> iter 9 value 775.511335
#> final value 775.511335
#> converged
#> This is Run number 205
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 3.6933331 -0.3994896 -0.6066669 -2.0994896 1
#> 2 1 -1.35 -13.20 -0.1588746 2.9637742 -1.5088746 -10.2362258 1
#> 3 1 -2.05 -14.20 0.9859338 1.0474805 -1.0640662 -13.1525195 1
#> 4 1 -1.55 -3.10 2.4348921 -0.9991915 0.8848921 -4.0991915 1
#> 5 1 -1.90 -3.60 -1.1317975 -0.2797519 -3.0317975 -3.8797519 1
#> 6 1 -13.70 -1.85 0.7794065 2.4509156 -12.9205935 0.6009156 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3360 -37300 9725
#> initial value 998.131940
#> iter 2 value 812.509348
#> iter 3 value 793.321108
#> iter 4 value 790.589627
#> iter 5 value 756.271838
#> iter 6 value 749.733949
#> iter 7 value 748.905035
#> iter 8 value 748.877210
#> iter 9 value 748.877130
#> iter 9 value 748.877126
#> iter 9 value 748.877126
#> final value 748.877126
#> converged
#> This is Run number 206
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.2684508 3.614909444 -4.0315492 1.9149094 2
#> 2 1 -1.35 -13.20 -0.6533222 1.571643861 -2.0033222 -11.6283561 1
#> 3 1 -2.05 -14.20 2.8940629 0.409543203 0.8440629 -13.7904568 1
#> 4 1 -1.55 -3.10 -0.6746242 2.524116891 -2.2246242 -0.5758831 2
#> 5 1 -1.90 -3.60 0.8233985 -1.035685320 -1.0766015 -4.6356853 1
#> 6 1 -13.70 -1.85 -0.6388348 0.002127276 -14.3388348 -1.8478727 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3860 -36875 8700
#> initial value 998.131940
#> iter 2 value 826.069019
#> iter 3 value 810.917637
#> iter 4 value 808.796637
#> iter 5 value 773.778670
#> iter 6 value 766.814086
#> iter 7 value 765.771001
#> iter 8 value 765.742622
#> iter 9 value 765.742446
#> iter 9 value 765.742434
#> iter 9 value 765.742430
#> final value 765.742430
#> converged
#> This is Run number 207
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.7501617 -0.83923012 -5.05016172 -2.539230 2
#> 2 1 -1.35 -13.20 1.5763107 0.56840691 0.22631071 -12.631593 1
#> 3 1 -2.05 -14.20 0.3925555 -1.24018686 -1.65744455 -15.440187 1
#> 4 1 -1.55 -3.10 3.9200700 -0.42710596 2.37007005 -3.527106 1
#> 5 1 -1.90 -3.60 1.8955329 -0.03922801 -0.00446708 -3.639228 1
#> 6 1 -13.70 -1.85 0.6924011 -0.69204902 -13.00759892 -2.542049 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3620 -38550 10050
#> initial value 998.131940
#> iter 2 value 792.028878
#> iter 3 value 772.006290
#> iter 4 value 769.292164
#> iter 5 value 737.904569
#> iter 6 value 731.446058
#> iter 7 value 730.665095
#> iter 8 value 730.629031
#> iter 9 value 730.628977
#> iter 10 value 730.628941
#> iter 11 value 730.628916
#> iter 11 value 730.628913
#> iter 11 value 730.628913
#> final value 730.628913
#> converged
#> This is Run number 208
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.7402572 1.2882237 -5.0402572 -0.4117763 2
#> 2 1 -1.35 -13.20 0.9961523 0.1958080 -0.3538477 -13.0041920 1
#> 3 1 -2.05 -14.20 0.9238502 2.2370581 -1.1261498 -11.9629419 1
#> 4 1 -1.55 -3.10 -0.6080313 1.8197996 -2.1580313 -1.2802004 2
#> 5 1 -1.90 -3.60 -0.6585402 -1.3645289 -2.5585402 -4.9645289 1
#> 6 1 -13.70 -1.85 -0.2225789 0.3202181 -13.9225789 -1.5297819 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2760 -36225 10700
#> initial value 998.131940
#> iter 2 value 818.949819
#> iter 3 value 795.850434
#> iter 4 value 793.483467
#> iter 5 value 757.902959
#> iter 6 value 752.169003
#> iter 7 value 751.528788
#> iter 8 value 751.506735
#> iter 9 value 751.506676
#> iter 10 value 751.506653
#> iter 10 value 751.506652
#> iter 10 value 751.506652
#> final value 751.506652
#> converged
#> This is Run number 209
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.12574737 4.3638525 -4.4257474 2.6638525 2
#> 2 1 -1.35 -13.20 0.63409184 0.2590826 -0.7159082 -12.9409174 1
#> 3 1 -2.05 -14.20 4.20181099 1.0736009 2.1518110 -13.1263991 1
#> 4 1 -1.55 -3.10 0.71116766 0.5195269 -0.8388323 -2.5804731 1
#> 5 1 -1.90 -3.60 -0.34076178 0.4027422 -2.2407618 -3.1972578 1
#> 6 1 -13.70 -1.85 -0.08476072 1.9454632 -13.7847607 0.0954632 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3620 -36375 10375
#> initial value 998.131940
#> iter 2 value 820.658901
#> iter 3 value 800.536262
#> iter 4 value 799.788070
#> iter 5 value 766.117832
#> iter 6 value 760.065883
#> iter 7 value 759.451991
#> iter 8 value 759.433722
#> iter 9 value 759.433618
#> iter 10 value 759.433532
#> iter 11 value 759.433482
#> iter 11 value 759.433477
#> iter 11 value 759.433477
#> final value 759.433477
#> converged
#> This is Run number 210
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.8062792 0.2643496 -3.4937208 -1.435650 2
#> 2 1 -1.35 -13.20 0.7612458 2.3567243 -0.5887542 -10.843276 1
#> 3 1 -2.05 -14.20 -0.7898726 2.1652429 -2.8398726 -12.034757 1
#> 4 1 -1.55 -3.10 -0.1487708 -0.5922700 -1.6987708 -3.692270 1
#> 5 1 -1.90 -3.60 1.1566839 0.7340265 -0.7433161 -2.865974 1
#> 6 1 -13.70 -1.85 0.5781394 0.1573897 -13.1218606 -1.692610 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2580 -35950 11175
#> initial value 998.131940
#> iter 2 value 818.369282
#> iter 3 value 793.385821
#> iter 4 value 791.264847
#> iter 5 value 755.846774
#> iter 6 value 750.472345
#> iter 7 value 749.909478
#> iter 8 value 749.888845
#> iter 9 value 749.888794
#> iter 10 value 749.888750
#> iter 10 value 749.888749
#> iter 10 value 749.888739
#> final value 749.888739
#> converged
#> This is Run number 211
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.0640870 0.05862392 -3.2359130 -1.641376 2
#> 2 1 -1.35 -13.20 0.6266215 -0.60112828 -0.7233785 -13.801128 1
#> 3 1 -2.05 -14.20 -0.9333785 -0.55901653 -2.9833785 -14.759017 1
#> 4 1 -1.55 -3.10 -0.2449084 0.27457547 -1.7949084 -2.825425 1
#> 5 1 -1.90 -3.60 1.2389147 3.72261199 -0.6610853 0.122612 2
#> 6 1 -13.70 -1.85 1.1278029 -0.14813332 -12.5721971 -1.998133 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4240 -36675 9075
#> initial value 998.131940
#> iter 2 value 826.572081
#> iter 3 value 811.326189
#> iter 4 value 810.551122
#> iter 5 value 776.607241
#> iter 6 value 769.842737
#> iter 7 value 768.949526
#> iter 8 value 768.925522
#> iter 9 value 768.925315
#> iter 10 value 768.925279
#> iter 11 value 768.925234
#> iter 12 value 768.925202
#> iter 12 value 768.925202
#> iter 12 value 768.925202
#> final value 768.925202
#> converged
#> This is Run number 212
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.6066032 0.7354589 -4.906603 -0.9645411 2
#> 2 1 -1.35 -13.20 -0.6526036 0.1543255 -2.002604 -13.0456745 1
#> 3 1 -2.05 -14.20 0.7780677 0.4104661 -1.271932 -13.7895339 1
#> 4 1 -1.55 -3.10 5.9456248 -0.5643607 4.395625 -3.6643607 1
#> 5 1 -1.90 -3.60 -0.4517407 0.5099507 -2.351741 -3.0900493 1
#> 6 1 -13.70 -1.85 2.0092158 -0.3911551 -11.690784 -2.2411551 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2940 -36575 11125
#> initial value 998.131940
#> iter 2 value 811.008555
#> iter 3 value 786.840056
#> iter 4 value 785.135336
#> iter 5 value 751.223882
#> iter 6 value 745.671112
#> iter 7 value 745.099681
#> iter 8 value 745.077007
#> iter 9 value 745.076945
#> iter 10 value 745.076856
#> iter 10 value 745.076854
#> iter 10 value 745.076854
#> final value 745.076854
#> converged
#> This is Run number 213
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.8812187 0.39053711 -3.4187813 -1.3094629 2
#> 2 1 -1.35 -13.20 0.2072932 0.88448990 -1.1427068 -12.3155101 1
#> 3 1 -2.05 -14.20 -0.6412890 -0.95879738 -2.6912890 -15.1587974 1
#> 4 1 -1.55 -3.10 0.8749405 -0.08967638 -0.6750595 -3.1896764 1
#> 5 1 -1.90 -3.60 1.4788592 0.38670701 -0.4211408 -3.2132930 1
#> 6 1 -13.70 -1.85 1.9726908 2.22999142 -11.7273092 0.3799914 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2540 -34575 9475
#> initial value 998.131940
#> iter 2 value 848.822256
#> iter 3 value 829.508671
#> iter 4 value 827.089213
#> iter 5 value 786.539742
#> iter 6 value 780.585492
#> iter 7 value 779.797380
#> iter 8 value 779.781485
#> iter 9 value 779.781432
#> iter 9 value 779.781428
#> iter 9 value 779.781427
#> final value 779.781427
#> converged
#> This is Run number 214
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.08219672 0.1162563 -4.21780328 -1.583744 2
#> 2 1 -1.35 -13.20 1.26503219 0.9592513 -0.08496781 -12.240749 1
#> 3 1 -2.05 -14.20 1.24194081 0.5569182 -0.80805919 -13.643082 1
#> 4 1 -1.55 -3.10 -0.81669457 -1.1971667 -2.36669457 -4.297167 1
#> 5 1 -1.90 -3.60 4.06984019 0.5601332 2.16984019 -3.039867 1
#> 6 1 -13.70 -1.85 1.90666615 -0.1915622 -11.79333385 -2.041562 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3620 -35775 9475
#> initial value 998.131940
#> iter 2 value 835.320709
#> iter 3 value 818.082538
#> iter 4 value 816.913536
#> iter 5 value 781.151446
#> iter 6 value 774.831853
#> iter 7 value 774.035634
#> iter 8 value 774.016198
#> iter 9 value 774.016052
#> iter 9 value 774.016049
#> iter 9 value 774.016049
#> final value 774.016049
#> converged
#> This is Run number 215
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.72209815 0.2520467 -5.0220982 -1.447953 2
#> 2 1 -1.35 -13.20 2.20509505 -0.6725345 0.8550951 -13.872534 1
#> 3 1 -2.05 -14.20 0.06349949 -0.7869451 -1.9865005 -14.986945 1
#> 4 1 -1.55 -3.10 0.25845775 -0.6780321 -1.2915423 -3.778032 1
#> 5 1 -1.90 -3.60 -1.11263590 -0.5274145 -3.0126359 -4.127414 1
#> 6 1 -13.70 -1.85 -1.43949917 6.6154654 -15.1394992 4.765465 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3560 -35875 10150
#> initial value 998.131940
#> iter 2 value 828.974939
#> iter 3 value 809.602660
#> iter 4 value 808.813073
#> iter 5 value 774.122479
#> iter 6 value 768.079052
#> iter 7 value 767.437206
#> iter 8 value 767.420451
#> iter 9 value 767.420338
#> iter 10 value 767.420292
#> iter 11 value 767.420240
#> iter 12 value 767.420227
#> iter 12 value 767.420227
#> iter 12 value 767.420227
#> final value 767.420227
#> converged
#> This is Run number 216
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.0584796 0.2380571 -2.241520 -1.461943 2
#> 2 1 -1.35 -13.20 -0.6799215 -0.8472607 -2.029921 -14.047261 1
#> 3 1 -2.05 -14.20 -0.7797568 0.1315187 -2.829757 -14.068481 1
#> 4 1 -1.55 -3.10 0.7064970 -0.0826091 -0.843503 -3.182609 1
#> 5 1 -1.90 -3.60 -0.4496470 2.3966881 -2.349647 -1.203312 2
#> 6 1 -13.70 -1.85 -0.1920478 0.5378940 -13.892048 -1.312106 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4540 -36275 8000
#> initial value 998.131940
#> iter 2 value 838.950418
#> iter 3 value 827.033458
#> iter 4 value 826.158812
#> iter 5 value 790.738825
#> iter 6 value 783.767987
#> iter 7 value 782.529761
#> iter 8 value 782.497275
#> iter 9 value 782.497031
#> iter 9 value 782.497025
#> iter 9 value 782.497025
#> final value 782.497025
#> converged
#> This is Run number 217
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.3309666 3.1614429 -3.9690334 1.461443 2
#> 2 1 -1.35 -13.20 -0.2058103 0.4614235 -1.5558103 -12.738577 1
#> 3 1 -2.05 -14.20 1.8897949 2.1891063 -0.1602051 -12.010894 1
#> 4 1 -1.55 -3.10 0.5685065 1.7185234 -0.9814935 -1.381477 1
#> 5 1 -1.90 -3.60 1.3611684 -0.8248428 -0.5388316 -4.424843 1
#> 6 1 -13.70 -1.85 -0.6745246 0.7714318 -14.3745246 -1.078568 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4020 -35700 9125
#> initial value 998.131940
#> iter 2 value 839.050901
#> iter 3 value 823.587152
#> iter 4 value 822.926568
#> iter 5 value 787.306719
#> iter 6 value 780.855852
#> iter 7 value 779.999925
#> iter 8 value 779.980065
#> iter 9 value 779.979907
#> iter 10 value 779.979873
#> iter 11 value 779.979825
#> iter 12 value 779.979797
#> iter 12 value 779.979797
#> iter 12 value 779.979797
#> final value 779.979797
#> converged
#> This is Run number 218
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.92738352 -0.3739636 -5.227384 -2.073964 2
#> 2 1 -1.35 -13.20 0.08804087 1.3153167 -1.261959 -11.884683 1
#> 3 1 -2.05 -14.20 0.45566109 0.3450519 -1.594339 -13.854948 1
#> 4 1 -1.55 -3.10 -0.18452078 0.7062062 -1.734521 -2.393794 1
#> 5 1 -1.90 -3.60 0.42772031 -0.6712709 -1.472280 -4.271271 1
#> 6 1 -13.70 -1.85 0.17492103 0.1470032 -13.525079 -1.702997 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3640 -35925 9800
#> initial value 998.131940
#> iter 2 value 831.029661
#> iter 3 value 812.850342
#> iter 4 value 811.908864
#> iter 5 value 776.882484
#> iter 6 value 770.658252
#> iter 7 value 769.939985
#> iter 8 value 769.921719
#> iter 9 value 769.921584
#> iter 10 value 769.921562
#> iter 11 value 769.921520
#> iter 12 value 769.921489
#> iter 12 value 769.921489
#> iter 12 value 769.921489
#> final value 769.921489
#> converged
#> This is Run number 219
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.1135305 0.3719639 -2.1864695 -1.328036 2
#> 2 1 -1.35 -13.20 0.3443602 0.4960190 -1.0056398 -12.703981 1
#> 3 1 -2.05 -14.20 0.4388315 2.0680731 -1.6111685 -12.131927 1
#> 4 1 -1.55 -3.10 0.2042597 -0.1496830 -1.3457403 -3.249683 1
#> 5 1 -1.90 -3.60 2.5499673 0.4994260 0.6499673 -3.100574 1
#> 6 1 -13.70 -1.85 -0.7092704 2.9803116 -14.4092704 1.130312 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3400 -38075 10950
#> initial value 998.131940
#> iter 2 value 791.747133
#> iter 3 value 768.652305
#> iter 4 value 766.868469
#> iter 5 value 735.470316
#> iter 6 value 729.631311
#> iter 7 value 728.995682
#> iter 8 value 728.963417
#> iter 9 value 728.963337
#> iter 10 value 728.963224
#> iter 11 value 728.963151
#> iter 12 value 728.963113
#> iter 12 value 728.963113
#> iter 12 value 728.963113
#> final value 728.963113
#> converged
#> This is Run number 220
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.4471571 1.02015682 -4.7471571 -0.6798432 2
#> 2 1 -1.35 -13.20 1.8409583 -0.94737652 0.4909583 -14.1473765 1
#> 3 1 -2.05 -14.20 0.1186642 1.82735592 -1.9313358 -12.3726441 1
#> 4 1 -1.55 -3.10 -0.6682765 -0.90161060 -2.2182765 -4.0016106 1
#> 5 1 -1.90 -3.60 1.5300389 0.07489096 -0.3699611 -3.5251090 1
#> 6 1 -13.70 -1.85 3.8939284 0.77324876 -9.8060716 -1.0767512 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3640 -38050 9600
#> initial value 998.131940
#> iter 2 value 802.877292
#> iter 3 value 784.379510
#> iter 4 value 781.620233
#> iter 5 value 748.967216
#> iter 6 value 742.249197
#> iter 7 value 741.397853
#> iter 8 value 741.365884
#> iter 9 value 741.365811
#> iter 9 value 741.365803
#> iter 9 value 741.365802
#> final value 741.365802
#> converged
#> This is Run number 221
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.6269404 0.83958799 -2.6730596 -0.860412 2
#> 2 1 -1.35 -13.20 0.8044372 1.28190338 -0.5455628 -11.918097 1
#> 3 1 -2.05 -14.20 -0.2891683 2.06494947 -2.3391683 -12.135051 1
#> 4 1 -1.55 -3.10 1.8067369 -0.08900203 0.2567369 -3.189002 1
#> 5 1 -1.90 -3.60 -0.7227498 -0.19878400 -2.6227498 -3.798784 1
#> 6 1 -13.70 -1.85 -0.7853681 1.10916796 -14.4853681 -0.740832 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2140 -33175 10525
#> initial value 998.131940
#> iter 2 value 856.461371
#> iter 3 value 833.741089
#> iter 4 value 832.165864
#> iter 5 value 792.628913
#> iter 6 value 787.701084
#> iter 7 value 787.197866
#> iter 8 value 787.188423
#> iter 9 value 787.188382
#> iter 9 value 787.188375
#> iter 9 value 787.188375
#> final value 787.188375
#> converged
#> This is Run number 222
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.77719981 1.9765787 -3.5228002 0.2765787 2
#> 2 1 -1.35 -13.20 1.13025418 -0.5660023 -0.2197458 -13.7660023 1
#> 3 1 -2.05 -14.20 -0.83915119 -0.2010743 -2.8891512 -14.4010743 1
#> 4 1 -1.55 -3.10 -1.43720760 1.1220985 -2.9872076 -1.9779015 2
#> 5 1 -1.90 -3.60 -0.02329635 0.9339090 -1.9232964 -2.6660910 1
#> 6 1 -13.70 -1.85 -0.70750733 1.4247621 -14.4075073 -0.4252379 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4520 -37875 9150
#> initial value 998.131940
#> iter 2 value 809.212419
#> iter 3 value 793.887741
#> iter 4 value 793.096514
#> iter 5 value 761.640703
#> iter 6 value 754.632576
#> iter 7 value 753.772062
#> iter 8 value 753.744226
#> iter 9 value 753.743991
#> iter 10 value 753.743967
#> iter 11 value 753.743917
#> iter 12 value 753.743869
#> iter 12 value 753.743869
#> iter 12 value 753.743869
#> final value 753.743869
#> converged
#> This is Run number 223
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 3.3231134 2.02390345 -0.9768866 0.3239034 2
#> 2 1 -1.35 -13.20 0.4247412 1.04850697 -0.9252588 -12.1514930 1
#> 3 1 -2.05 -14.20 -0.7487330 0.06029126 -2.7987330 -14.1397087 1
#> 4 1 -1.55 -3.10 -0.6201272 1.86549894 -2.1701272 -1.2345011 2
#> 5 1 -1.90 -3.60 -0.1691942 1.03665437 -2.0691942 -2.5633456 1
#> 6 1 -13.70 -1.85 0.8411649 -0.03021697 -12.8588351 -1.8802170 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3600 -37400 9750
#> initial value 998.131940
#> iter 2 value 811.183801
#> iter 3 value 792.470932
#> iter 4 value 790.367922
#> iter 5 value 756.976960
#> iter 6 value 750.418846
#> iter 7 value 749.618522
#> iter 8 value 749.591373
#> iter 9 value 749.591255
#> iter 10 value 749.591239
#> iter 11 value 749.591224
#> iter 11 value 749.591221
#> iter 11 value 749.591221
#> final value 749.591221
#> converged
#> This is Run number 224
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.006959831 -0.08693069 -4.2930402 -1.786931 2
#> 2 1 -1.35 -13.20 -1.321261378 1.60796045 -2.6712614 -11.592040 1
#> 3 1 -2.05 -14.20 3.287725389 1.28557196 1.2377254 -12.914428 1
#> 4 1 -1.55 -3.10 1.772767734 -0.50379072 0.2227677 -3.603791 1
#> 5 1 -1.90 -3.60 0.591352322 -0.13205167 -1.3086477 -3.732052 1
#> 6 1 -13.70 -1.85 1.009752348 -0.12906061 -12.6902477 -1.979061 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3880 -33975 7675
#> initial value 998.131940
#> iter 2 value 869.125642
#> iter 3 value 857.540078
#> iter 4 value 856.533504
#> iter 5 value 816.279435
#> iter 6 value 810.067715
#> iter 7 value 808.896827
#> iter 8 value 808.873050
#> iter 9 value 808.872922
#> iter 10 value 808.872900
#> iter 11 value 808.872869
#> iter 11 value 808.872858
#> iter 11 value 808.872858
#> final value 808.872858
#> converged
#> This is Run number 225
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.8582556 -1.1285466 -5.158256 -2.828547 2
#> 2 1 -1.35 -13.20 0.2487588 4.6673744 -1.101241 -8.532626 1
#> 3 1 -2.05 -14.20 0.4263128 -0.1830761 -1.623687 -14.383076 1
#> 4 1 -1.55 -3.10 -1.1720298 1.2227553 -2.722030 -1.877245 2
#> 5 1 -1.90 -3.60 -1.4226251 -1.1842498 -3.322625 -4.784250 1
#> 6 1 -13.70 -1.85 1.9961816 0.3189068 -11.703818 -1.531093 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3300 -37050 9825
#> initial value 998.131940
#> iter 2 value 815.222526
#> iter 3 value 795.723886
#> iter 4 value 793.165496
#> iter 5 value 758.542943
#> iter 6 value 752.105610
#> iter 7 value 751.303231
#> iter 8 value 751.277015
#> iter 9 value 751.276928
#> iter 9 value 751.276922
#> iter 9 value 751.276922
#> final value 751.276922
#> converged
#> This is Run number 226
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.0297101 0.5368554 -3.2702899 -1.1631446 2
#> 2 1 -1.35 -13.20 -0.2190544 4.1216410 -1.5690544 -9.0783590 1
#> 3 1 -2.05 -14.20 1.4039477 3.9288783 -0.6460523 -10.2711217 1
#> 4 1 -1.55 -3.10 0.1532120 3.8024450 -1.3967880 0.7024450 2
#> 5 1 -1.90 -3.60 1.2618339 0.8505382 -0.6381661 -2.7494618 1
#> 6 1 -13.70 -1.85 3.9528531 0.9330101 -9.7471469 -0.9169899 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4340 -36950 8300
#> initial value 998.131940
#> iter 2 value 827.882947
#> iter 3 value 814.664549
#> iter 4 value 813.236663
#> iter 5 value 778.940424
#> iter 6 value 771.831007
#> iter 7 value 770.676662
#> iter 8 value 770.644395
#> iter 9 value 770.644146
#> iter 10 value 770.644124
#> iter 11 value 770.644108
#> iter 12 value 770.644092
#> iter 12 value 770.644092
#> iter 12 value 770.644092
#> final value 770.644092
#> converged
#> This is Run number 227
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.4982232 3.0024690 -3.8017768 1.302469 2
#> 2 1 -1.35 -13.20 -1.0840001 -0.3366742 -2.4340001 -13.536674 1
#> 3 1 -2.05 -14.20 1.0442539 -0.5833355 -1.0057461 -14.783336 1
#> 4 1 -1.55 -3.10 0.7068723 -0.7463479 -0.8431277 -3.846348 1
#> 5 1 -1.90 -3.60 2.1959358 2.0778660 0.2959358 -1.522134 1
#> 6 1 -13.70 -1.85 0.9885571 -0.8092862 -12.7114429 -2.659286 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3560 -38075 8925
#> initial value 998.131940
#> iter 2 value 807.099308
#> iter 3 value 790.087562
#> iter 4 value 786.286117
#> iter 5 value 752.069117
#> iter 6 value 744.967911
#> iter 7 value 743.960018
#> iter 8 value 743.927201
#> iter 9 value 743.927185
#> iter 9 value 743.927183
#> iter 9 value 743.927183
#> final value 743.927183
#> converged
#> This is Run number 228
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.04480736 4.50124361 -4.344807 2.801244 2
#> 2 1 -1.35 -13.20 -0.28323979 0.12815000 -1.633240 -13.071850 1
#> 3 1 -2.05 -14.20 3.24468921 1.75798482 1.194689 -12.442015 1
#> 4 1 -1.55 -3.10 0.18843890 0.04074503 -1.361561 -3.059255 1
#> 5 1 -1.90 -3.60 -0.30417322 -0.11281512 -2.204173 -3.712815 1
#> 6 1 -13.70 -1.85 2.13011800 -0.58467611 -11.569882 -2.434676 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3120 -34725 9725
#> initial value 998.131940
#> iter 2 value 846.157430
#> iter 3 value 827.540547
#> iter 4 value 826.206948
#> iter 5 value 788.651367
#> iter 6 value 782.792520
#> iter 7 value 782.085341
#> iter 8 value 782.070261
#> iter 9 value 782.070163
#> iter 9 value 782.070159
#> iter 9 value 782.070159
#> final value 782.070159
#> converged
#> This is Run number 229
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.9131333 1.31109277 -3.386867 -0.3889072 2
#> 2 1 -1.35 -13.20 0.3339201 -0.26549377 -1.016080 -13.4654938 1
#> 3 1 -2.05 -14.20 0.3532671 0.23378126 -1.696733 -13.9662187 1
#> 4 1 -1.55 -3.10 0.4605435 0.05954281 -1.089456 -3.0404572 1
#> 5 1 -1.90 -3.60 0.2479603 -0.47561525 -1.652040 -4.0756153 1
#> 6 1 -13.70 -1.85 -0.2651950 -0.15458834 -13.965195 -2.0045883 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4000 -37700 9325
#> initial value 998.131940
#> iter 2 value 810.280164
#> iter 3 value 793.509081
#> iter 4 value 791.772564
#> iter 5 value 759.236591
#> iter 6 value 752.380850
#> iter 7 value 751.511500
#> iter 8 value 751.482895
#> iter 9 value 751.482720
#> iter 9 value 751.482710
#> iter 9 value 751.482710
#> final value 751.482710
#> converged
#> This is Run number 230
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.1121013 0.16120275 -4.18789871 -1.5387973 2
#> 2 1 -1.35 -13.20 1.4335628 -0.09499696 0.08356282 -13.2949970 1
#> 3 1 -2.05 -14.20 0.5526031 1.12635251 -1.49739690 -13.0736475 1
#> 4 1 -1.55 -3.10 3.5720875 0.36540717 2.02208753 -2.7345928 1
#> 5 1 -1.90 -3.60 3.2172344 -0.69510757 1.31723441 -4.2951076 1
#> 6 1 -13.70 -1.85 0.4688138 2.20062654 -13.23118622 0.3506265 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4100 -37250 9225
#> initial value 998.131940
#> iter 2 value 817.480467
#> iter 3 value 801.360771
#> iter 4 value 800.091991
#> iter 5 value 766.961959
#> iter 6 value 760.133236
#> iter 7 value 759.255446
#> iter 8 value 759.229094
#> iter 9 value 759.228888
#> iter 9 value 759.228883
#> iter 9 value 759.228883
#> final value 759.228883
#> converged
#> This is Run number 231
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.4687830 1.08987219 -3.8312170 -0.6101278 2
#> 2 1 -1.35 -13.20 0.4320087 -0.50414223 -0.9179913 -13.7041422 1
#> 3 1 -2.05 -14.20 2.3665782 0.02666835 0.3165782 -14.1733317 1
#> 4 1 -1.55 -3.10 2.5777596 1.78675702 1.0277596 -1.3132430 1
#> 5 1 -1.90 -3.60 -0.2593736 -0.23937763 -2.1593736 -3.8393776 1
#> 6 1 -13.70 -1.85 1.9984363 0.35418251 -11.7015637 -1.4958175 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3660 -36850 8550
#> initial value 998.131940
#> iter 2 value 827.185396
#> iter 3 value 811.928586
#> iter 4 value 809.214537
#> iter 5 value 773.187501
#> iter 6 value 766.137335
#> iter 7 value 765.051035
#> iter 8 value 765.022943
#> iter 9 value 765.022826
#> iter 9 value 765.022821
#> iter 9 value 765.022819
#> final value 765.022819
#> converged
#> This is Run number 232
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.17247965 0.351410742 -4.4724797 -1.3485893 2
#> 2 1 -1.35 -13.20 0.35134294 1.360352142 -0.9986571 -11.8396479 1
#> 3 1 -2.05 -14.20 -0.50428883 -1.056772035 -2.5542888 -15.2567720 1
#> 4 1 -1.55 -3.10 2.19647312 0.003837607 0.6464731 -3.0961624 1
#> 5 1 -1.90 -3.60 2.31686637 -0.428734586 0.4168664 -4.0287346 1
#> 6 1 -13.70 -1.85 -0.01352833 1.692842565 -13.7135283 -0.1571574 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3260 -35475 9825
#> initial value 998.131940
#> iter 2 value 836.247062
#> iter 3 value 817.348674
#> iter 4 value 815.911822
#> iter 5 value 779.565683
#> iter 6 value 773.506941
#> iter 7 value 772.784377
#> iter 8 value 772.766813
#> iter 9 value 772.766698
#> iter 9 value 772.766689
#> iter 9 value 772.766689
#> final value 772.766689
#> converged
#> This is Run number 233
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.08087521 1.2194355 -4.3808752 -0.4805645 2
#> 2 1 -1.35 -13.20 0.19299095 0.3881210 -1.1570091 -12.8118790 1
#> 3 1 -2.05 -14.20 2.78200112 2.8878955 0.7320011 -11.3121045 1
#> 4 1 -1.55 -3.10 -0.45808664 0.7929966 -2.0080866 -2.3070034 1
#> 5 1 -1.90 -3.60 -0.54008342 2.1543740 -2.4400834 -1.4456260 2
#> 6 1 -13.70 -1.85 -1.50481092 2.7065981 -15.2048109 0.8565981 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3240 -37025 10825
#> initial value 998.131940
#> iter 2 value 807.705886
#> iter 3 value 785.063829
#> iter 4 value 783.492702
#> iter 5 value 750.339884
#> iter 6 value 744.499703
#> iter 7 value 743.888444
#> iter 8 value 743.864148
#> iter 9 value 743.864073
#> iter 10 value 743.863978
#> iter 10 value 743.863975
#> iter 10 value 743.863965
#> final value 743.863965
#> converged
#> This is Run number 234
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.1735762 -0.5138445 -4.4735762 -2.213845 2
#> 2 1 -1.35 -13.20 -1.1158602 2.1276896 -2.4658602 -11.072310 1
#> 3 1 -2.05 -14.20 1.0908666 -1.4146554 -0.9591334 -15.614655 1
#> 4 1 -1.55 -3.10 0.5557082 -0.1588118 -0.9942918 -3.258812 1
#> 5 1 -1.90 -3.60 -0.3045088 2.4085439 -2.2045088 -1.191456 2
#> 6 1 -13.70 -1.85 0.1352422 0.9036780 -13.5647578 -0.946322 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3760 -37425 10200
#> initial value 998.131940
#> iter 2 value 807.592477
#> iter 3 value 787.924562
#> iter 4 value 786.723896
#> iter 5 value 754.394622
#> iter 6 value 748.061843
#> iter 7 value 747.379294
#> iter 8 value 747.354547
#> iter 9 value 747.354432
#> iter 10 value 747.354349
#> iter 11 value 747.354334
#> iter 12 value 747.354307
#> iter 12 value 747.354307
#> iter 12 value 747.354307
#> final value 747.354307
#> converged
#> This is Run number 235
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.004241737 2.1712047 -4.295758 0.4712047 2
#> 2 1 -1.35 -13.20 -0.694588031 -0.9186759 -2.044588 -14.1186759 1
#> 3 1 -2.05 -14.20 0.050876389 -0.1081317 -1.999124 -14.3081317 1
#> 4 1 -1.55 -3.10 -0.565280389 -0.1637593 -2.115280 -3.2637593 1
#> 5 1 -1.90 -3.60 2.484087009 -0.3568139 0.584087 -3.9568139 1
#> 6 1 -13.70 -1.85 1.152301712 3.1758346 -12.547698 1.3258346 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3420 -35775 9175
#> initial value 998.131940
#> iter 2 value 837.199926
#> iter 3 value 820.328688
#> iter 4 value 818.465754
#> iter 5 value 781.644339
#> iter 6 value 775.197112
#> iter 7 value 774.304517
#> iter 8 value 774.282976
#> iter 9 value 774.282842
#> iter 10 value 774.282829
#> iter 10 value 774.282821
#> iter 10 value 774.282818
#> final value 774.282818
#> converged
#> This is Run number 236
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.99399914 -0.8008573 -2.306001 -2.500857 1
#> 2 1 -1.35 -13.20 -0.00933581 2.5763965 -1.359336 -10.623603 1
#> 3 1 -2.05 -14.20 -1.04698186 -0.3080019 -3.096982 -14.508002 1
#> 4 1 -1.55 -3.10 0.19064958 -0.3233341 -1.359350 -3.423334 1
#> 5 1 -1.90 -3.60 -0.82580636 0.4054827 -2.725806 -3.194517 1
#> 6 1 -13.70 -1.85 0.11361529 -0.7107327 -13.586385 -2.560733 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4000 -38375 10600
#> initial value 998.131940
#> iter 2 value 790.696329
#> iter 3 value 769.955287
#> iter 4 value 769.126915
#> iter 5 value 739.072822
#> iter 6 value 732.899999
#> iter 7 value 732.273581
#> iter 8 value 732.244285
#> iter 9 value 732.244180
#> iter 10 value 732.243941
#> iter 11 value 732.243898
#> iter 12 value 732.243835
#> iter 12 value 732.243835
#> iter 12 value 732.243835
#> final value 732.243835
#> converged
#> This is Run number 237
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.02958438 -0.6943235 -4.2704156 -2.394323 2
#> 2 1 -1.35 -13.20 0.59241874 -1.1655627 -0.7575813 -14.365563 1
#> 3 1 -2.05 -14.20 0.43197122 0.7567525 -1.6180288 -13.443247 1
#> 4 1 -1.55 -3.10 0.31171179 1.1141402 -1.2382882 -1.985860 1
#> 5 1 -1.90 -3.60 0.79242928 0.4613491 -1.1075707 -3.138651 1
#> 6 1 -13.70 -1.85 -0.52289140 -0.3334888 -14.2228914 -2.183489 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4440 -38150 8975
#> initial value 998.131940
#> iter 2 value 806.338622
#> iter 3 value 791.223934
#> iter 4 value 789.907189
#> iter 5 value 758.619481
#> iter 6 value 751.503707
#> iter 7 value 750.580756
#> iter 8 value 750.549754
#> iter 9 value 750.549518
#> iter 9 value 750.549511
#> iter 9 value 750.549511
#> final value 750.549511
#> converged
#> This is Run number 238
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.1839688 0.4404636 -4.1160312 -1.259536 2
#> 2 1 -1.35 -13.20 1.6990073 -0.7583831 0.3490073 -13.958383 1
#> 3 1 -2.05 -14.20 -0.6894821 -0.9231838 -2.7394821 -15.123184 1
#> 4 1 -1.55 -3.10 0.4690162 1.3361886 -1.0809838 -1.763811 1
#> 5 1 -1.90 -3.60 0.5274761 0.1457626 -1.3725239 -3.454237 1
#> 6 1 -13.70 -1.85 -0.4376664 0.4825851 -14.1376664 -1.367415 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3360 -34800 9050
#> initial value 998.131940
#> iter 2 value 850.275810
#> iter 3 value 834.013459
#> iter 4 value 832.583764
#> iter 5 value 794.398241
#> iter 6 value 788.237190
#> iter 7 value 787.370949
#> iter 8 value 787.352689
#> iter 9 value 787.352574
#> iter 10 value 787.352559
#> iter 11 value 787.352542
#> iter 11 value 787.352530
#> iter 11 value 787.352530
#> final value 787.352530
#> converged
#> This is Run number 239
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -1.7334344 3.0057288 -6.0334344 1.3057288 2
#> 2 1 -1.35 -13.20 1.0992552 -0.3568061 -0.2507448 -13.5568061 1
#> 3 1 -2.05 -14.20 0.9990038 1.0960987 -1.0509962 -13.1039013 1
#> 4 1 -1.55 -3.10 1.2601422 1.6245389 -0.2898578 -1.4754611 1
#> 5 1 -1.90 -3.60 -1.1886331 -0.3351199 -3.0886331 -3.9351199 1
#> 6 1 -13.70 -1.85 -0.2649073 1.4053364 -13.9649073 -0.4446636 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3380 -36675 9650
#> initial value 998.131940
#> iter 2 value 821.797205
#> iter 3 value 803.155157
#> iter 4 value 800.949399
#> iter 5 value 765.861210
#> iter 6 value 759.398035
#> iter 7 value 758.580111
#> iter 8 value 758.556092
#> iter 9 value 758.555974
#> iter 9 value 758.555972
#> iter 9 value 758.555972
#> final value 758.555972
#> converged
#> This is Run number 240
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.1249134 0.64787835 -4.4249134 -1.052122 2
#> 2 1 -1.35 -13.20 0.8068039 1.05512584 -0.5431961 -12.144874 1
#> 3 1 -2.05 -14.20 -1.0103325 2.77195909 -3.0603325 -11.428041 1
#> 4 1 -1.55 -3.10 -0.3732338 0.08864506 -1.9232338 -3.011355 1
#> 5 1 -1.90 -3.60 0.9092550 0.04956485 -0.9907450 -3.550435 1
#> 6 1 -13.70 -1.85 -0.9894156 -0.31961533 -14.6894156 -2.169615 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2900 -35275 9775
#> initial value 998.131940
#> iter 2 value 838.640369
#> iter 3 value 819.107320
#> iter 4 value 816.987762
#> iter 5 value 779.222124
#> iter 6 value 773.207398
#> iter 7 value 772.455960
#> iter 8 value 772.438111
#> iter 9 value 772.438022
#> iter 9 value 772.438014
#> iter 9 value 772.438011
#> final value 772.438011
#> converged
#> This is Run number 241
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.3394305 0.1685359 -4.639430 -1.5314641 2
#> 2 1 -1.35 -13.20 -1.5843940 0.3379982 -2.934394 -12.8620018 1
#> 3 1 -2.05 -14.20 -0.1923123 -0.5019945 -2.242312 -14.7019945 1
#> 4 1 -1.55 -3.10 -0.5904350 1.8367133 -2.140435 -1.2632867 2
#> 5 1 -1.90 -3.60 0.2265561 4.2604807 -1.673444 0.6604807 2
#> 6 1 -13.70 -1.85 1.8477353 0.5459878 -11.852265 -1.3040122 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3840 -37025 9325
#> initial value 998.131940
#> iter 2 value 819.750529
#> iter 3 value 802.902143
#> iter 4 value 801.261514
#> iter 5 value 767.366094
#> iter 6 value 760.645121
#> iter 7 value 759.775091
#> iter 8 value 759.749443
#> iter 9 value 759.749267
#> iter 9 value 759.749265
#> iter 9 value 759.749265
#> final value 759.749265
#> converged
#> This is Run number 242
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.28198102 -0.5336063 -4.5819810 -2.233606 2
#> 2 1 -1.35 -13.20 1.73562649 1.0519105 0.3856265 -12.148090 1
#> 3 1 -2.05 -14.20 0.03786915 0.3275577 -2.0121309 -13.872442 1
#> 4 1 -1.55 -3.10 0.27573642 -0.5208604 -1.2742636 -3.620860 1
#> 5 1 -1.90 -3.60 -1.01588577 0.1429407 -2.9158858 -3.457059 1
#> 6 1 -13.70 -1.85 2.71158198 0.2159814 -10.9884180 -1.634019 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3600 -36525 9225
#> initial value 998.131940
#> iter 2 value 827.098391
#> iter 3 value 810.185119
#> iter 4 value 808.222906
#> iter 5 value 772.880298
#> iter 6 value 766.239335
#> iter 7 value 765.338158
#> iter 8 value 765.313799
#> iter 9 value 765.313646
#> iter 10 value 765.313634
#> iter 10 value 765.313626
#> iter 10 value 765.313622
#> final value 765.313622
#> converged
#> This is Run number 243
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.1313995 0.09545582 -2.1686005 -1.604544 2
#> 2 1 -1.35 -13.20 -0.9407602 -0.03007458 -2.2907602 -13.230075 1
#> 3 1 -2.05 -14.20 1.1426776 -0.32627021 -0.9073224 -14.526270 1
#> 4 1 -1.55 -3.10 0.3484099 -0.43854140 -1.2015901 -3.538541 1
#> 5 1 -1.90 -3.60 0.1721021 1.52871782 -1.7278979 -2.071282 1
#> 6 1 -13.70 -1.85 1.5703597 0.20242649 -12.1296403 -1.647574 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2520 -36350 10350
#> initial value 998.131940
#> iter 2 value 819.594020
#> iter 3 value 796.817358
#> iter 4 value 793.338992
#> iter 5 value 755.973251
#> iter 6 value 750.022170
#> iter 7 value 749.281019
#> iter 8 value 749.256022
#> iter 9 value 749.255997
#> iter 9 value 749.255996
#> iter 9 value 749.255996
#> final value 749.255996
#> converged
#> This is Run number 244
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.2463578 0.1846839 -2.053642 -1.515316 2
#> 2 1 -1.35 -13.20 5.3291780 1.6175311 3.979178 -11.582469 1
#> 3 1 -2.05 -14.20 -0.3187964 1.1626001 -2.368796 -13.037400 1
#> 4 1 -1.55 -3.10 3.2916178 1.2438257 1.741618 -1.856174 1
#> 5 1 -1.90 -3.60 -1.4472849 0.7413328 -3.347285 -2.858667 2
#> 6 1 -13.70 -1.85 1.1334578 -0.6874939 -12.566542 -2.537494 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2780 -37400 10450
#> initial value 998.131940
#> iter 2 value 804.703341
#> iter 3 value 781.822770
#> iter 4 value 778.083686
#> iter 5 value 742.941097
#> iter 6 value 736.893553
#> iter 7 value 736.133862
#> iter 8 value 736.101346
#> iter 9 value 736.101327
#> iter 9 value 736.101324
#> iter 9 value 736.101324
#> final value 736.101324
#> converged
#> This is Run number 245
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.13494370 0.49853023 -4.4349437 -1.201470 2
#> 2 1 -1.35 -13.20 0.01726581 -0.33621562 -1.3327342 -13.536216 1
#> 3 1 -2.05 -14.20 -1.10018447 1.59980868 -3.1501845 -12.600191 1
#> 4 1 -1.55 -3.10 -0.91825531 -0.56935331 -2.4682553 -3.669353 1
#> 5 1 -1.90 -3.60 2.26620115 0.09007582 0.3662011 -3.509924 1
#> 6 1 -13.70 -1.85 1.18077644 0.21544360 -12.5192236 -1.634556 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2900 -36850 10800
#> initial value 998.131940
#> iter 2 value 809.854811
#> iter 3 value 786.515589
#> iter 4 value 784.108885
#> iter 5 value 749.713249
#> iter 6 value 743.927939
#> iter 7 value 743.281530
#> iter 8 value 743.255728
#> iter 9 value 743.255673
#> iter 10 value 743.255635
#> iter 10 value 743.255634
#> iter 10 value 743.255634
#> final value 743.255634
#> converged
#> This is Run number 246
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.39415295 -0.1727293 -4.694153 -1.872729 2
#> 2 1 -1.35 -13.20 -1.16397161 -0.3276055 -2.513972 -13.527606 1
#> 3 1 -2.05 -14.20 -0.28453034 1.0043047 -2.334530 -13.195695 1
#> 4 1 -1.55 -3.10 0.09396077 -0.5853078 -1.456039 -3.685308 1
#> 5 1 -1.90 -3.60 0.14068175 -0.9492962 -1.759318 -4.549296 1
#> 6 1 -13.70 -1.85 2.48850574 0.8264288 -11.211494 -1.023571 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3960 -38625 9800
#> initial value 998.131940
#> iter 2 value 793.078740
#> iter 3 value 774.544468
#> iter 4 value 772.512737
#> iter 5 value 741.865250
#> iter 6 value 735.200714
#> iter 7 value 734.416271
#> iter 8 value 734.382469
#> iter 9 value 734.382380
#> iter 10 value 734.382329
#> iter 10 value 734.382326
#> iter 10 value 734.382325
#> final value 734.382325
#> converged
#> This is Run number 247
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.6897874 0.4767041 -4.989787 -1.223296 2
#> 2 1 -1.35 -13.20 -0.8362536 -1.5218636 -2.186254 -14.721864 1
#> 3 1 -2.05 -14.20 -0.4506002 1.2226825 -2.500600 -12.977318 1
#> 4 1 -1.55 -3.10 -0.5057535 1.7955707 -2.055754 -1.304429 2
#> 5 1 -1.90 -3.60 -0.4821819 2.5062102 -2.382182 -1.093790 2
#> 6 1 -13.70 -1.85 -0.9251196 3.7922056 -14.625120 1.942206 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4280 -36350 9200
#> initial value 998.131940
#> iter 2 value 830.123223
#> iter 3 value 814.713141
#> iter 4 value 814.241562
#> iter 5 value 780.024739
#> iter 6 value 773.387954
#> iter 7 value 772.550551
#> iter 8 value 772.529465
#> iter 9 value 772.529286
#> iter 10 value 772.529245
#> iter 11 value 772.529186
#> iter 12 value 772.529149
#> iter 12 value 772.529149
#> iter 12 value 772.529149
#> final value 772.529149
#> converged
#> This is Run number 248
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.2377085 0.2508240 -4.5377085 -1.449176 2
#> 2 1 -1.35 -13.20 0.1177092 -0.7269030 -1.2322908 -13.926903 1
#> 3 1 -2.05 -14.20 2.6072624 1.2078884 0.5572624 -12.992112 1
#> 4 1 -1.55 -3.10 0.5502035 1.6110506 -0.9997965 -1.488949 1
#> 5 1 -1.90 -3.60 -0.3011752 -0.3466126 -2.2011752 -3.946613 1
#> 6 1 -13.70 -1.85 1.8805880 1.1094470 -11.8194120 -0.740553 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2760 -35775 11100
#> initial value 998.131940
#> iter 2 value 821.607092
#> iter 3 value 797.417761
#> iter 4 value 795.809795
#> iter 5 value 760.722152
#> iter 6 value 755.310210
#> iter 7 value 754.766988
#> iter 8 value 754.748760
#> iter 9 value 754.748701
#> iter 10 value 754.748637
#> iter 10 value 754.748636
#> iter 11 value 754.748622
#> iter 11 value 754.748620
#> iter 11 value 754.748620
#> final value 754.748620
#> converged
#> This is Run number 249
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.3862907 2.0266840 -4.6862907 0.3266840 2
#> 2 1 -1.35 -13.20 1.5906176 -0.4960826 0.2406176 -13.6960826 1
#> 3 1 -2.05 -14.20 -0.3553603 -1.2782284 -2.4053603 -15.4782284 1
#> 4 1 -1.55 -3.10 0.3935494 0.4187684 -1.1564506 -2.6812316 1
#> 5 1 -1.90 -3.60 -1.4258724 0.5596787 -3.3258724 -3.0403213 2
#> 6 1 -13.70 -1.85 0.9749176 2.4800225 -12.7250824 0.6300225 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4260 -36825 8050
#> initial value 998.131940
#> iter 2 value 831.093868
#> iter 3 value 818.330067
#> iter 4 value 816.569098
#> iter 5 value 781.548026
#> iter 6 value 774.383576
#> iter 7 value 773.142128
#> iter 8 value 773.108158
#> iter 9 value 773.107926
#> iter 10 value 773.107912
#> iter 10 value 773.107906
#> iter 10 value 773.107904
#> final value 773.107904
#> converged
#> This is Run number 250
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.1815262 1.344020198 -4.4815262 -0.3559798 2
#> 2 1 -1.35 -13.20 1.9930681 -1.169096607 0.6430681 -14.3690966 1
#> 3 1 -2.05 -14.20 0.4366477 3.358321604 -1.6133523 -10.8416784 1
#> 4 1 -1.55 -3.10 0.0834799 -0.196733962 -1.4665201 -3.2967340 1
#> 5 1 -1.90 -3.60 -1.0378923 -0.003332934 -2.9378923 -3.6033329 1
#> 6 1 -13.70 -1.85 0.5877365 -1.401877385 -13.1122635 -3.2518774 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3520 -38225 9275
#> initial value 998.131940
#> iter 2 value 802.441286
#> iter 3 value 784.390741
#> iter 4 value 780.677642
#> iter 5 value 747.206931
#> iter 6 value 740.300327
#> iter 7 value 739.360045
#> iter 8 value 739.325697
#> iter 9 value 739.325677
#> iter 9 value 739.325677
#> iter 9 value 739.325677
#> final value 739.325677
#> converged
#> This is Run number 251
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.97338306 -1.4672064 -2.3266169 -3.167206 1
#> 2 1 -1.35 -13.20 2.87807618 -0.1008022 1.5280762 -13.300802 1
#> 3 1 -2.05 -14.20 0.08054695 -0.6854168 -1.9694530 -14.885417 1
#> 4 1 -1.55 -3.10 1.69892966 0.3116053 0.1489297 -2.788395 1
#> 5 1 -1.90 -3.60 0.29843494 1.0725617 -1.6015651 -2.527438 1
#> 6 1 -13.70 -1.85 -0.48950792 3.4369769 -14.1895079 1.586977 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2840 -37000 10675
#> initial value 998.131940
#> iter 2 value 808.678885
#> iter 3 value 785.496268
#> iter 4 value 782.623539
#> iter 5 value 747.892293
#> iter 6 value 742.018625
#> iter 7 value 741.333182
#> iter 8 value 741.305353
#> iter 9 value 741.305309
#> iter 10 value 741.305289
#> iter 10 value 741.305284
#> iter 10 value 741.305284
#> final value 741.305284
#> converged
#> This is Run number 252
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.3055620 0.2384299 -2.9944380 -1.461570 2
#> 2 1 -1.35 -13.20 -0.8865154 -0.5897689 -2.2365154 -13.789769 1
#> 3 1 -2.05 -14.20 1.0158514 -1.1611752 -1.0341486 -15.361175 1
#> 4 1 -1.55 -3.10 -0.6006120 1.4525281 -2.1506120 -1.647472 2
#> 5 1 -1.90 -3.60 2.0329091 -0.2877525 0.1329091 -3.887752 1
#> 6 1 -13.70 -1.85 -0.2138498 4.5082922 -13.9138498 2.658292 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3260 -36225 9850
#> initial value 998.131940
#> iter 2 value 826.268387
#> iter 3 value 806.977155
#> iter 4 value 805.031432
#> iter 5 value 769.457517
#> iter 6 value 763.207944
#> iter 7 value 762.447775
#> iter 8 value 762.426469
#> iter 9 value 762.426354
#> iter 9 value 762.426347
#> iter 9 value 762.426347
#> final value 762.426347
#> converged
#> This is Run number 253
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.4715224 3.9734018 -3.8284776 2.273402 2
#> 2 1 -1.35 -13.20 0.6105136 1.2373147 -0.7394864 -11.962685 1
#> 3 1 -2.05 -14.20 1.0879601 -0.5010234 -0.9620399 -14.701023 1
#> 4 1 -1.55 -3.10 -0.8726059 -0.9867879 -2.4226059 -4.086788 1
#> 5 1 -1.90 -3.60 0.6105635 2.4380167 -1.2894365 -1.161983 2
#> 6 1 -13.70 -1.85 -0.5392580 0.3816202 -14.2392580 -1.468380 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3900 -37725 9550
#> initial value 998.131940
#> iter 2 value 808.241639
#> iter 3 value 790.633303
#> iter 4 value 788.865446
#> iter 5 value 756.422148
#> iter 6 value 749.684867
#> iter 7 value 748.861288
#> iter 8 value 748.833018
#> iter 9 value 748.832868
#> iter 10 value 748.832847
#> iter 11 value 748.832824
#> iter 11 value 748.832818
#> iter 11 value 748.832818
#> final value 748.832818
#> converged
#> This is Run number 254
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 4.0833673 0.7389626 -0.21663271 -0.9610374 1
#> 2 1 -1.35 -13.20 0.3000728 -0.4393752 -1.04992720 -13.6393752 1
#> 3 1 -2.05 -14.20 0.5124246 -0.8275286 -1.53757537 -15.0275286 1
#> 4 1 -1.55 -3.10 0.6973376 -0.4534594 -0.85266240 -3.5534594 1
#> 5 1 -1.90 -3.60 1.9849338 0.1663076 0.08493378 -3.4336924 1
#> 6 1 -13.70 -1.85 1.3805601 -0.7015005 -12.31943993 -2.5515005 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3100 -35900 9150
#> initial value 998.131940
#> iter 2 value 835.312897
#> iter 3 value 817.657651
#> iter 4 value 814.989290
#> iter 5 value 777.024029
#> iter 6 value 770.501435
#> iter 7 value 769.580255
#> iter 8 value 769.558319
#> iter 9 value 769.558236
#> iter 9 value 769.558232
#> iter 9 value 769.558230
#> final value 769.558230
#> converged
#> This is Run number 255
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.7423750 -1.0740710 -1.557625 -2.774071 1
#> 2 1 -1.35 -13.20 -1.9459656 2.4169310 -3.295966 -10.783069 1
#> 3 1 -2.05 -14.20 -0.1034626 -0.5639606 -2.153463 -14.763961 1
#> 4 1 -1.55 -3.10 -0.3149306 -0.2281008 -1.864931 -3.328101 1
#> 5 1 -1.90 -3.60 -0.1649116 0.4226628 -2.064912 -3.177337 1
#> 6 1 -13.70 -1.85 1.8864729 0.2257545 -11.813527 -1.624246 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3660 -37300 10375
#> initial value 998.131940
#> iter 2 value 807.916536
#> iter 3 value 787.544640
#> iter 4 value 786.363134
#> iter 5 value 753.888167
#> iter 6 value 747.684033
#> iter 7 value 747.029432
#> iter 8 value 747.005363
#> iter 9 value 747.005259
#> iter 10 value 747.005164
#> iter 10 value 747.005162
#> iter 10 value 747.005162
#> final value 747.005162
#> converged
#> This is Run number 256
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.49167207 0.39393625 -4.7916721 -1.3060637 2
#> 2 1 -1.35 -13.20 0.29573065 0.26621695 -1.0542694 -12.9337830 1
#> 3 1 -2.05 -14.20 0.97313741 3.34512217 -1.0768626 -10.8548778 1
#> 4 1 -1.55 -3.10 0.83020668 0.09631145 -0.7197933 -3.0036885 1
#> 5 1 -1.90 -3.60 -0.09866729 -0.71172842 -1.9986673 -4.3117284 1
#> 6 1 -13.70 -1.85 -1.00659603 2.29951017 -14.7065960 0.4495102 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3580 -37025 9600
#> initial value 998.131940
#> iter 2 value 817.547086
#> iter 3 value 799.364920
#> iter 4 value 797.347192
#> iter 5 value 763.189022
#> iter 6 value 756.616993
#> iter 7 value 755.792488
#> iter 8 value 755.767074
#> iter 9 value 755.766939
#> iter 9 value 755.766933
#> iter 9 value 755.766933
#> final value 755.766933
#> converged
#> This is Run number 257
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.2387716 0.1810649 -4.538772 -1.518935 2
#> 2 1 -1.35 -13.20 -1.0365281 -0.5247331 -2.386528 -13.724733 1
#> 3 1 -2.05 -14.20 -0.3254837 2.8859326 -2.375484 -11.314067 1
#> 4 1 -1.55 -3.10 2.7031438 1.3209452 1.153144 -1.779055 1
#> 5 1 -1.90 -3.60 0.6985578 0.3048380 -1.201442 -3.295162 1
#> 6 1 -13.70 -1.85 -0.5198106 0.1902654 -14.219811 -1.659735 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3520 -37550 10200
#> initial value 998.131940
#> iter 2 value 805.563013
#> iter 3 value 785.301775
#> iter 4 value 783.379076
#> iter 5 value 750.628433
#> iter 6 value 744.315550
#> iter 7 value 743.596643
#> iter 8 value 743.569068
#> iter 9 value 743.568976
#> iter 10 value 743.568929
#> iter 10 value 743.568926
#> iter 10 value 743.568918
#> final value 743.568918
#> converged
#> This is Run number 258
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.37523787 -0.38332332 -4.6752379 -2.083323 2
#> 2 1 -1.35 -13.20 -0.02727386 1.69490902 -1.3772739 -11.505091 1
#> 3 1 -2.05 -14.20 0.73003435 0.35290345 -1.3199656 -13.847097 1
#> 4 1 -1.55 -3.10 1.84047377 0.40984423 0.2904738 -2.690156 1
#> 5 1 -1.90 -3.60 -0.68779686 -0.33947113 -2.5877969 -3.939471 1
#> 6 1 -13.70 -1.85 1.12025267 -0.01334172 -12.5797473 -1.863342 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3860 -37350 9350
#> initial value 998.131940
#> iter 2 value 815.015885
#> iter 3 value 798.012285
#> iter 4 value 796.203578
#> iter 5 value 762.849010
#> iter 6 value 756.073606
#> iter 7 value 755.203628
#> iter 8 value 755.176478
#> iter 9 value 755.176310
#> iter 9 value 755.176305
#> iter 9 value 755.176305
#> final value 755.176305
#> converged
#> This is Run number 259
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.3390430 0.3990975 -3.9609570 -1.300903 2
#> 2 1 -1.35 -13.20 3.1981186 1.1705276 1.8481186 -12.029472 1
#> 3 1 -2.05 -14.20 0.1439583 -0.6423602 -1.9060417 -14.842360 1
#> 4 1 -1.55 -3.10 1.3548803 1.7522419 -0.1951197 -1.347758 1
#> 5 1 -1.90 -3.60 0.8157943 2.5252173 -1.0842057 -1.074783 2
#> 6 1 -13.70 -1.85 0.8322464 -0.4277404 -12.8677536 -2.277740 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3600 -36100 10100
#> initial value 998.131940
#> iter 2 value 826.437457
#> iter 3 value 807.219756
#> iter 4 value 806.352574
#> iter 5 value 771.912144
#> iter 6 value 765.785777
#> iter 7 value 765.125204
#> iter 8 value 765.107262
#> iter 9 value 765.107141
#> iter 10 value 765.107095
#> iter 11 value 765.107044
#> iter 12 value 765.107032
#> iter 12 value 765.107032
#> iter 12 value 765.107032
#> final value 765.107032
#> converged
#> This is Run number 260
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.26415975 -1.9215034 -2.0358402 -3.621503 1
#> 2 1 -1.35 -13.20 0.03193381 0.1920354 -1.3180662 -13.007965 1
#> 3 1 -2.05 -14.20 -0.36250406 -1.1713350 -2.4125041 -15.371335 1
#> 4 1 -1.55 -3.10 0.69369064 -0.8089267 -0.8563094 -3.908927 1
#> 5 1 -1.90 -3.60 2.47392399 0.8485470 0.5739240 -2.751453 1
#> 6 1 -13.70 -1.85 0.46028688 0.2436300 -13.2397131 -1.606370 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4160 -37250 9150
#> initial value 998.131940
#> iter 2 value 818.034634
#> iter 3 value 802.235245
#> iter 4 value 801.030967
#> iter 5 value 767.925326
#> iter 6 value 761.060429
#> iter 7 value 760.166860
#> iter 8 value 760.140252
#> iter 9 value 760.140037
#> iter 9 value 760.140035
#> iter 9 value 760.140035
#> final value 760.140035
#> converged
#> This is Run number 261
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.8280682 -1.1481770 -5.1280682 -2.848177 2
#> 2 1 -1.35 -13.20 0.5736273 0.4873293 -0.7763727 -12.712671 1
#> 3 1 -2.05 -14.20 0.3509629 -0.3495557 -1.6990371 -14.549556 1
#> 4 1 -1.55 -3.10 -0.2802599 -0.5390009 -1.8302599 -3.639001 1
#> 5 1 -1.90 -3.60 0.0371885 1.6414498 -1.8628115 -1.958550 1
#> 6 1 -13.70 -1.85 0.2838448 0.2564929 -13.4161552 -1.593507 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3560 -35150 9075
#> initial value 998.131940
#> iter 2 value 845.998661
#> iter 3 value 829.960661
#> iter 4 value 828.715501
#> iter 5 value 791.443483
#> iter 6 value 785.171047
#> iter 7 value 784.298220
#> iter 8 value 784.278961
#> iter 9 value 784.278828
#> iter 10 value 784.278808
#> iter 11 value 784.278784
#> iter 12 value 784.278768
#> iter 12 value 784.278768
#> iter 12 value 784.278768
#> final value 784.278768
#> converged
#> This is Run number 262
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.3449520 1.3607817 -4.6449520 -0.3392183 2
#> 2 1 -1.35 -13.20 1.2403946 5.0068095 -0.1096054 -8.1931905 1
#> 3 1 -2.05 -14.20 3.7361379 0.8115122 1.6861379 -13.3884878 1
#> 4 1 -1.55 -3.10 0.5447718 0.4378975 -1.0052282 -2.6621025 1
#> 5 1 -1.90 -3.60 1.4625875 -0.4697207 -0.4374125 -4.0697207 1
#> 6 1 -13.70 -1.85 1.1771646 0.1678368 -12.5228354 -1.6821632 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3440 -35650 10150
#> initial value 998.131940
#> iter 2 value 831.771447
#> iter 3 value 812.231902
#> iter 4 value 811.331859
#> iter 5 value 776.159773
#> iter 6 value 770.187731
#> iter 7 value 769.546178
#> iter 8 value 769.529944
#> iter 9 value 769.529836
#> iter 10 value 769.529798
#> iter 11 value 769.529753
#> iter 12 value 769.529737
#> iter 12 value 769.529737
#> iter 12 value 769.529737
#> final value 769.529737
#> converged
#> This is Run number 263
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.02773291 -0.85662533 -4.2722671 -2.556625 2
#> 2 1 -1.35 -13.20 1.82243232 1.80897747 0.4724323 -11.391023 1
#> 3 1 -2.05 -14.20 0.48172660 2.76861413 -1.5682734 -11.431386 1
#> 4 1 -1.55 -3.10 -0.70319068 5.46126606 -2.2531907 2.361266 2
#> 5 1 -1.90 -3.60 0.08534689 -0.06307753 -1.8146531 -3.663078 1
#> 6 1 -13.70 -1.85 0.39479141 -0.73122158 -13.3052086 -2.581222 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4040 -38875 9800
#> initial value 998.131940
#> iter 2 value 789.304516
#> iter 3 value 770.849614
#> iter 4 value 768.846063
#> iter 5 value 738.778965
#> iter 6 value 732.107177
#> iter 7 value 731.325842
#> iter 8 value 731.290536
#> iter 9 value 731.290451
#> iter 10 value 731.290389
#> iter 10 value 731.290380
#> iter 10 value 731.290380
#> final value 731.290380
#> converged
#> This is Run number 264
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.5731511 1.2641881 -1.7268489 -0.4358119 2
#> 2 1 -1.35 -13.20 0.4350641 3.6733788 -0.9149359 -9.5266212 1
#> 3 1 -2.05 -14.20 -0.2369047 -0.1394810 -2.2869047 -14.3394810 1
#> 4 1 -1.55 -3.10 5.3569479 -1.5406788 3.8069479 -4.6406788 1
#> 5 1 -1.90 -3.60 1.3997442 1.9697933 -0.5002558 -1.6302067 1
#> 6 1 -13.70 -1.85 0.6154450 -0.4725836 -13.0845550 -2.3225836 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3380 -37475 9475
#> initial value 998.131940
#> iter 2 value 811.837774
#> iter 3 value 793.285626
#> iter 4 value 790.160233
#> iter 5 value 755.639669
#> iter 6 value 748.932730
#> iter 7 value 748.043526
#> iter 8 value 748.014218
#> iter 9 value 748.014157
#> iter 9 value 748.014157
#> iter 9 value 748.014156
#> final value 748.014156
#> converged
#> This is Run number 265
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.1122133 -1.4232204 -4.41221327 -3.123220 2
#> 2 1 -1.35 -13.20 -0.8345244 0.3043974 -2.18452441 -12.895603 1
#> 3 1 -2.05 -14.20 0.7901846 -0.1546112 -1.25981544 -14.354611 1
#> 4 1 -1.55 -3.10 1.5852949 1.4286989 0.03529486 -1.671301 1
#> 5 1 -1.90 -3.60 0.1970897 1.3575359 -1.70291029 -2.242464 1
#> 6 1 -13.70 -1.85 0.6955554 0.2187514 -13.00444462 -1.631249 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3860 -36325 8325
#> initial value 998.131940
#> iter 2 value 835.932236
#> iter 3 value 821.902674
#> iter 4 value 819.867696
#> iter 5 value 783.460522
#> iter 6 value 776.508123
#> iter 7 value 775.364194
#> iter 8 value 775.335398
#> iter 9 value 775.335228
#> iter 9 value 775.335218
#> iter 9 value 775.335215
#> final value 775.335215
#> converged
#> This is Run number 266
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 3.1878672 2.5938490 -1.1121328 0.893849 2
#> 2 1 -1.35 -13.20 0.7934344 0.2175272 -0.5565656 -12.982473 1
#> 3 1 -2.05 -14.20 1.9408182 0.5670413 -0.1091818 -13.632959 1
#> 4 1 -1.55 -3.10 1.7567313 -0.2719157 0.2067313 -3.371916 1
#> 5 1 -1.90 -3.60 -0.1847201 -1.2531899 -2.0847201 -4.853190 1
#> 6 1 -13.70 -1.85 0.3572718 -0.3193907 -13.3427282 -2.169391 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3520 -36850 9825
#> initial value 998.131940
#> iter 2 value 818.271092
#> iter 3 value 799.395013
#> iter 4 value 797.602130
#> iter 5 value 763.423753
#> iter 6 value 757.006269
#> iter 7 value 756.236794
#> iter 8 value 756.212970
#> iter 9 value 756.212840
#> iter 10 value 756.212823
#> iter 11 value 756.212802
#> iter 11 value 756.212793
#> iter 11 value 756.212793
#> final value 756.212793
#> converged
#> This is Run number 267
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.0058256 -0.3347861 -3.294174 -2.034786 2
#> 2 1 -1.35 -13.20 -0.1250784 1.9944657 -1.475078 -11.205534 1
#> 3 1 -2.05 -14.20 -0.2384357 1.9452786 -2.288436 -12.254721 1
#> 4 1 -1.55 -3.10 -1.7118747 -0.1083421 -3.261875 -3.208342 2
#> 5 1 -1.90 -3.60 -0.5013480 -0.9063159 -2.401348 -4.506316 1
#> 6 1 -13.70 -1.85 -0.4493311 0.6727690 -14.149331 -1.177231 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4000 -36450 9175
#> initial value 998.131940
#> iter 2 value 828.802030
#> iter 3 value 812.907663
#> iter 4 value 811.865886
#> iter 5 value 777.300505
#> iter 6 value 770.648269
#> iter 7 value 769.769789
#> iter 8 value 769.746593
#> iter 9 value 769.746404
#> iter 10 value 769.746375
#> iter 11 value 769.746341
#> iter 12 value 769.746316
#> iter 12 value 769.746316
#> iter 12 value 769.746316
#> final value 769.746316
#> converged
#> This is Run number 268
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.297260077 1.7655411 -4.5972601 0.06554109 2
#> 2 1 -1.35 -13.20 1.886584173 0.6433205 0.5365842 -12.55667953 1
#> 3 1 -2.05 -14.20 -0.575100566 -0.9327199 -2.6251006 -15.13271993 1
#> 4 1 -1.55 -3.10 0.477838122 0.7849259 -1.0721619 -2.31507407 1
#> 5 1 -1.90 -3.60 0.794806490 0.7921832 -1.1051935 -2.80781683 1
#> 6 1 -13.70 -1.85 -0.005801978 0.7017618 -13.7058020 -1.14823819 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3420 -38100 10300
#> initial value 998.131940
#> iter 2 value 796.634066
#> iter 3 value 775.588873
#> iter 4 value 772.999922
#> iter 5 value 740.775643
#> iter 6 value 734.506125
#> iter 7 value 733.765630
#> iter 8 value 733.732386
#> iter 9 value 733.732329
#> iter 10 value 733.732289
#> iter 11 value 733.732268
#> iter 11 value 733.732263
#> iter 11 value 733.732263
#> final value 733.732263
#> converged
#> This is Run number 269
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.0685172 -0.2302717 -3.2314828 -1.930272 2
#> 2 1 -1.35 -13.20 -0.8358627 0.2397564 -2.1858627 -12.960244 1
#> 3 1 -2.05 -14.20 1.0900767 1.8845133 -0.9599233 -12.315487 1
#> 4 1 -1.55 -3.10 0.8808273 0.3465636 -0.6691727 -2.753436 1
#> 5 1 -1.90 -3.60 -0.3753934 0.7879678 -2.2753934 -2.812032 1
#> 6 1 -13.70 -1.85 0.2922388 0.4079445 -13.4077612 -1.442055 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2860 -34225 10075
#> initial value 998.131940
#> iter 2 value 849.196963
#> iter 3 value 829.165939
#> iter 4 value 827.899229
#> iter 5 value 790.022455
#> iter 6 value 784.497057
#> iter 7 value 783.883152
#> iter 8 value 783.870700
#> iter 9 value 783.870624
#> iter 9 value 783.870614
#> iter 9 value 783.870614
#> final value 783.870614
#> converged
#> This is Run number 270
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.44085250 3.1928036 -3.859148 1.4928036 2
#> 2 1 -1.35 -13.20 2.35796719 -0.7394440 1.007967 -13.9394440 1
#> 3 1 -2.05 -14.20 0.07595028 -0.3426388 -1.974050 -14.5426388 1
#> 4 1 -1.55 -3.10 0.51481514 -0.7591116 -1.035185 -3.8591116 1
#> 5 1 -1.90 -3.60 -0.68009648 -0.5414027 -2.580096 -4.1414027 1
#> 6 1 -13.70 -1.85 -0.49041152 2.1003527 -14.190412 0.2503527 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3380 -35825 10000
#> initial value 998.131940
#> iter 2 value 830.574085
#> iter 3 value 811.290708
#> iter 4 value 810.044201
#> iter 5 value 774.658234
#> iter 6 value 768.575565
#> iter 7 value 767.884410
#> iter 8 value 767.866350
#> iter 9 value 767.866231
#> iter 10 value 767.866208
#> iter 11 value 767.866175
#> iter 12 value 767.866158
#> iter 12 value 767.866158
#> iter 12 value 767.866158
#> final value 767.866158
#> converged
#> This is Run number 271
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.8846903 -1.0580322 -5.1846903 -2.758032 2
#> 2 1 -1.35 -13.20 0.6054915 -0.4612674 -0.7445085 -13.661267 1
#> 3 1 -2.05 -14.20 -0.5557992 4.1188871 -2.6057992 -10.081113 1
#> 4 1 -1.55 -3.10 0.4862993 -0.7415978 -1.0637007 -3.841598 1
#> 5 1 -1.90 -3.60 0.4978455 -0.6208918 -1.4021545 -4.220892 1
#> 6 1 -13.70 -1.85 2.8014712 1.0755000 -10.8985288 -0.774500 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4060 -36750 7700
#> initial value 998.131940
#> iter 2 value 834.039056
#> iter 3 value 821.615138
#> iter 4 value 819.203464
#> iter 5 value 782.827982
#> iter 6 value 775.501522
#> iter 7 value 774.166949
#> iter 8 value 774.133012
#> iter 9 value 774.132855
#> iter 9 value 774.132850
#> iter 9 value 774.132848
#> final value 774.132848
#> converged
#> This is Run number 272
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.5864532 0.9584641 -1.7135468 -0.74153592 2
#> 2 1 -1.35 -13.20 -0.9967737 -0.9418503 -2.3467737 -14.14185034 1
#> 3 1 -2.05 -14.20 1.5928536 2.1784868 -0.4571464 -12.02151324 1
#> 4 1 -1.55 -3.10 1.2668928 0.7333432 -0.2831072 -2.36665676 1
#> 5 1 -1.90 -3.60 -0.2485816 1.1668427 -2.1485816 -2.43315729 1
#> 6 1 -13.70 -1.85 1.5619365 1.8344049 -12.1380635 -0.01559512 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3800 -37075 10475
#> initial value 998.131940
#> iter 2 value 810.418164
#> iter 3 value 790.105847
#> iter 4 value 789.434654
#> iter 5 value 757.093241
#> iter 6 value 750.953292
#> iter 7 value 750.345181
#> iter 8 value 750.324085
#> iter 9 value 750.323986
#> iter 10 value 750.323843
#> iter 10 value 750.323840
#> iter 10 value 750.323840
#> final value 750.323840
#> converged
#> This is Run number 273
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 3.4296232 1.1657927 -0.87037680 -0.5342073 2
#> 2 1 -1.35 -13.20 0.3785797 -0.6716367 -0.97142028 -13.8716367 1
#> 3 1 -2.05 -14.20 3.1503358 2.7629793 1.10033584 -11.4370207 1
#> 4 1 -1.55 -3.10 1.5144860 0.9781115 -0.03551396 -2.1218885 1
#> 5 1 -1.90 -3.60 0.2148252 2.0128309 -1.68517485 -1.5871691 2
#> 6 1 -13.70 -1.85 -1.2091939 0.9565019 -14.90919388 -0.8934981 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2900 -35025 9975
#> initial value 998.131940
#> iter 2 value 840.298471
#> iter 3 value 820.308755
#> iter 4 value 818.534164
#> iter 5 value 781.048119
#> iter 6 value 775.211181
#> iter 7 value 774.521135
#> iter 8 value 774.505037
#> iter 9 value 774.504947
#> iter 9 value 774.504943
#> iter 9 value 774.504943
#> final value 774.504943
#> converged
#> This is Run number 274
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.8692426 -0.08853041 -3.4307574 -1.788530 2
#> 2 1 -1.35 -13.20 1.5950548 0.82455526 0.2450548 -12.375445 1
#> 3 1 -2.05 -14.20 -0.1156399 0.88150737 -2.1656399 -13.318493 1
#> 4 1 -1.55 -3.10 1.1909921 3.57613795 -0.3590079 0.476138 2
#> 5 1 -1.90 -3.60 0.3810135 0.34992742 -1.5189865 -3.250073 1
#> 6 1 -13.70 -1.85 4.1452179 -1.19407757 -9.5547821 -3.044078 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3960 -37275 9250
#> initial value 998.131940
#> iter 2 value 816.857727
#> iter 3 value 800.368886
#> iter 4 value 798.766754
#> iter 5 value 765.405659
#> iter 6 value 758.591693
#> iter 7 value 757.706204
#> iter 8 value 757.679307
#> iter 9 value 757.679118
#> iter 9 value 757.679116
#> iter 9 value 757.679116
#> final value 757.679116
#> converged
#> This is Run number 275
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.9939241 1.7756187 -5.293924 0.07561875 2
#> 2 1 -1.35 -13.20 -0.1807795 -0.1500516 -1.530779 -13.35005160 1
#> 3 1 -2.05 -14.20 4.8516757 1.4889315 2.801676 -12.71106854 1
#> 4 1 -1.55 -3.10 -0.5514148 2.6633440 -2.101415 -0.43665598 2
#> 5 1 -1.90 -3.60 0.2104319 -0.3821815 -1.689568 -3.98218152 1
#> 6 1 -13.70 -1.85 -0.3826189 1.3914857 -14.082619 -0.45851432 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2720 -35875 9600
#> initial value 998.131940
#> iter 2 value 831.875381
#> iter 3 value 812.030810
#> iter 4 value 808.908767
#> iter 5 value 770.260601
#> iter 6 value 763.965406
#> iter 7 value 763.124279
#> iter 8 value 763.102984
#> iter 9 value 763.102940
#> iter 9 value 763.102938
#> iter 9 value 763.102937
#> final value 763.102937
#> converged
#> This is Run number 276
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.2149605 1.16000011 -4.5149605 -0.5399999 2
#> 2 1 -1.35 -13.20 0.3652940 -0.48930531 -0.9847060 -13.6893053 1
#> 3 1 -2.05 -14.20 0.8535364 0.06935600 -1.1964636 -14.1306440 1
#> 4 1 -1.55 -3.10 0.5979875 -1.05587689 -0.9520125 -4.1558769 1
#> 5 1 -1.90 -3.60 0.3546107 1.07190840 -1.5453893 -2.5280916 1
#> 6 1 -13.70 -1.85 1.4883728 -0.09927243 -12.2116272 -1.9492724 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2880 -35950 9800
#> initial value 998.131940
#> iter 2 value 829.720410
#> iter 3 value 809.734030
#> iter 4 value 807.039095
#> iter 5 value 769.734097
#> iter 6 value 763.537164
#> iter 7 value 762.746450
#> iter 8 value 762.725268
#> iter 9 value 762.725196
#> iter 9 value 762.725193
#> iter 9 value 762.725192
#> final value 762.725192
#> converged
#> This is Run number 277
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.65924784 0.8502692 -3.6407522 -0.8497308 2
#> 2 1 -1.35 -13.20 1.00967078 -0.1803763 -0.3403292 -13.3803763 1
#> 3 1 -2.05 -14.20 1.82346536 -0.1708252 -0.2265346 -14.3708252 1
#> 4 1 -1.55 -3.10 1.86236167 1.3832776 0.3123617 -1.7167224 1
#> 5 1 -1.90 -3.60 -0.05956054 1.0287386 -1.9595605 -2.5712614 1
#> 6 1 -13.70 -1.85 -0.57228174 -0.6286713 -14.2722817 -2.4786713 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3580 -36275 10625
#> initial value 998.131940
#> iter 2 value 819.973966
#> iter 3 value 799.004994
#> iter 4 value 798.417446
#> iter 5 value 764.934940
#> iter 6 value 759.039878
#> iter 7 value 758.474044
#> iter 8 value 758.456933
#> iter 9 value 758.456848
#> iter 10 value 758.456728
#> iter 11 value 758.456703
#> iter 12 value 758.456678
#> iter 12 value 758.456678
#> iter 12 value 758.456678
#> final value 758.456678
#> converged
#> This is Run number 278
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.5955690 0.6898540 -4.895569 -1.010146 2
#> 2 1 -1.35 -13.20 -0.4644962 1.1489700 -1.814496 -12.051030 1
#> 3 1 -2.05 -14.20 0.5786765 -0.1760435 -1.471324 -14.376044 1
#> 4 1 -1.55 -3.10 -0.0638652 -0.7688789 -1.613865 -3.868879 1
#> 5 1 -1.90 -3.60 -0.3626010 -0.5565446 -2.262601 -4.156545 1
#> 6 1 -13.70 -1.85 1.7420639 0.8386699 -11.957936 -1.011330 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4600 -38150 9425
#> initial value 998.131940
#> iter 2 value 803.252507
#> iter 3 value 787.234788
#> iter 4 value 786.688435
#> iter 5 value 756.096247
#> iter 6 value 749.168712
#> iter 7 value 748.394136
#> iter 8 value 748.367338
#> iter 9 value 748.367141
#> iter 10 value 748.367064
#> iter 11 value 748.366989
#> iter 12 value 748.366975
#> iter 12 value 748.366975
#> iter 12 value 748.366975
#> final value 748.366975
#> converged
#> This is Run number 279
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.9495852 0.04085807 -3.3504148 -1.659142 2
#> 2 1 -1.35 -13.20 1.6351978 0.21844616 0.2851978 -12.981554 1
#> 3 1 -2.05 -14.20 -0.1492538 1.04551914 -2.1992538 -13.154481 1
#> 4 1 -1.55 -3.10 -1.1868328 1.94466654 -2.7368328 -1.155333 2
#> 5 1 -1.90 -3.60 -1.1316174 1.91541746 -3.0316174 -1.684583 2
#> 6 1 -13.70 -1.85 -0.5901538 4.81269775 -14.2901538 2.962698 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4260 -36250 9950
#> initial value 998.131940
#> iter 2 value 826.018270
#> iter 3 value 808.414068
#> iter 4 value 808.311770
#> iter 5 value 774.883924
#> iter 6 value 768.575295
#> iter 7 value 767.946266
#> iter 8 value 767.930793
#> iter 9 value 767.930691
#> iter 10 value 767.930642
#> iter 11 value 767.930561
#> iter 12 value 767.930517
#> iter 12 value 767.930517
#> iter 12 value 767.930517
#> final value 767.930517
#> converged
#> This is Run number 280
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.23969053 0.5951754 -3.060309 -1.1048246 2
#> 2 1 -1.35 -13.20 -1.34150260 2.4165398 -2.691503 -10.7834602 1
#> 3 1 -2.05 -14.20 0.42909751 -0.1131271 -1.620902 -14.3131271 1
#> 4 1 -1.55 -3.10 -1.00166778 0.9837743 -2.551668 -2.1162257 2
#> 5 1 -1.90 -3.60 -0.09649942 0.9232528 -1.996499 -2.6767472 1
#> 6 1 -13.70 -1.85 0.79363274 1.4339963 -12.906367 -0.4160037 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3880 -36825 8775
#> initial value 998.131940
#> iter 2 value 826.287266
#> iter 3 value 811.019837
#> iter 4 value 809.062091
#> iter 5 value 774.156081
#> iter 6 value 767.239249
#> iter 7 value 766.219732
#> iter 8 value 766.191913
#> iter 9 value 766.191728
#> iter 10 value 766.191715
#> iter 10 value 766.191709
#> iter 10 value 766.191709
#> final value 766.191709
#> converged
#> This is Run number 281
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 3.3724159 -0.7138428 -0.9275841 -2.4138428 1
#> 2 1 -1.35 -13.20 1.9066279 0.5807313 0.5566279 -12.6192687 1
#> 3 1 -2.05 -14.20 2.3269168 0.7649224 0.2769168 -13.4350776 1
#> 4 1 -1.55 -3.10 0.3179216 1.0680150 -1.2320784 -2.0319850 1
#> 5 1 -1.90 -3.60 -0.9249058 1.6567853 -2.8249058 -1.9432147 2
#> 6 1 -13.70 -1.85 -0.1299589 2.4710548 -13.8299589 0.6210548 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4440 -37625 8125
#> initial value 998.131940
#> iter 2 value 819.459136
#> iter 3 value 806.577000
#> iter 4 value 804.718901
#> iter 5 value 771.547942
#> iter 6 value 764.197625
#> iter 7 value 762.992773
#> iter 8 value 762.956848
#> iter 9 value 762.956589
#> iter 10 value 762.956573
#> iter 10 value 762.956569
#> iter 10 value 762.956563
#> final value 762.956563
#> converged
#> This is Run number 282
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.1738455 1.0148237 -4.4738455 -0.6851763 2
#> 2 1 -1.35 -13.20 1.6366625 -0.5205017 0.2866625 -13.7205017 1
#> 3 1 -2.05 -14.20 -0.5760980 -0.8041983 -2.6260980 -15.0041983 1
#> 4 1 -1.55 -3.10 1.7372621 8.7574688 0.1872621 5.6574688 2
#> 5 1 -1.90 -3.60 -0.6541562 0.3302044 -2.5541562 -3.2697956 1
#> 6 1 -13.70 -1.85 0.4267607 1.3811447 -13.2732393 -0.4688553 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3640 -37950 9400
#> initial value 998.131940
#> iter 2 value 805.779052
#> iter 3 value 787.857053
#> iter 4 value 784.945122
#> iter 5 value 751.835432
#> iter 6 value 745.012969
#> iter 7 value 744.119421
#> iter 8 value 744.087869
#> iter 9 value 744.087796
#> iter 9 value 744.087793
#> iter 9 value 744.087793
#> final value 744.087793
#> converged
#> This is Run number 283
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.4621152 2.87549980 -4.7621152 1.175500 2
#> 2 1 -1.35 -13.20 -1.2423211 0.06155155 -2.5923211 -13.138448 1
#> 3 1 -2.05 -14.20 0.2065546 -0.30117746 -1.8434454 -14.501177 1
#> 4 1 -1.55 -3.10 0.7034376 0.88359199 -0.8465624 -2.216408 1
#> 5 1 -1.90 -3.60 2.5234225 1.99824838 0.6234225 -1.601752 1
#> 6 1 -13.70 -1.85 0.9399678 0.22023403 -12.7600322 -1.629766 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3740 -36900 10300
#> initial value 998.131940
#> iter 2 value 814.184553
#> iter 3 value 794.358875
#> iter 4 value 793.515514
#> iter 5 value 760.601741
#> iter 6 value 754.399379
#> iter 7 value 753.758604
#> iter 8 value 753.737636
#> iter 9 value 753.737524
#> iter 10 value 753.737428
#> iter 11 value 753.737389
#> iter 12 value 753.737376
#> iter 12 value 753.737376
#> iter 12 value 753.737376
#> final value 753.737376
#> converged
#> This is Run number 284
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.2543718 0.82039274 -4.5543718 -0.8796073 2
#> 2 1 -1.35 -13.20 -0.2293674 2.22452746 -1.5793674 -10.9754725 1
#> 3 1 -2.05 -14.20 0.1790066 8.89022519 -1.8709934 -5.3097748 1
#> 4 1 -1.55 -3.10 0.7666606 -0.57941848 -0.7833394 -3.6794185 1
#> 5 1 -1.90 -3.60 0.3754616 0.33847883 -1.5245384 -3.2615212 1
#> 6 1 -13.70 -1.85 -0.2416376 -0.05438357 -13.9416376 -1.9043836 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3660 -35625 9375
#> initial value 998.131940
#> iter 2 value 838.003420
#> iter 3 value 821.182253
#> iter 4 value 820.097064
#> iter 5 value 784.087876
#> iter 6 value 777.771439
#> iter 7 value 776.960009
#> iter 8 value 776.940817
#> iter 9 value 776.940672
#> iter 9 value 776.940671
#> iter 9 value 776.940671
#> final value 776.940671
#> converged
#> This is Run number 285
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.9192052 0.4491581 -3.380795 -1.2508419 2
#> 2 1 -1.35 -13.20 -0.8978812 0.9419500 -2.247881 -12.2580500 1
#> 3 1 -2.05 -14.20 -0.6863244 -0.5797289 -2.736324 -14.7797289 1
#> 4 1 -1.55 -3.10 2.5556326 2.8609007 1.005633 -0.2390993 1
#> 5 1 -1.90 -3.60 0.1164613 1.0597029 -1.783539 -2.5402971 1
#> 6 1 -13.70 -1.85 -1.3085983 0.8753279 -15.008598 -0.9746721 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3200 -37750 9150
#> initial value 998.131940
#> iter 2 value 809.872853
#> iter 3 value 791.499414
#> iter 4 value 787.308000
#> iter 5 value 751.414891
#> iter 6 value 744.486596
#> iter 7 value 743.503383
#> iter 8 value 743.471531
#> iter 8 value 743.471527
#> final value 743.471527
#> converged
#> This is Run number 286
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.2781249 -0.7191799 -4.578125e+00 -2.419180 2
#> 2 1 -1.35 -13.20 1.3499826 -0.2496119 -1.739901e-05 -13.449612 1
#> 3 1 -2.05 -14.20 -0.6414822 1.7920959 -2.691482e+00 -12.407904 1
#> 4 1 -1.55 -3.10 1.2562421 1.9046706 -2.937579e-01 -1.195329 1
#> 5 1 -1.90 -3.60 1.1127941 1.2013736 -7.872059e-01 -2.398626 1
#> 6 1 -13.70 -1.85 -0.9778270 -1.0791675 -1.467783e+01 -2.929167 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3840 -37450 9550
#> initial value 998.131940
#> iter 2 value 812.151914
#> iter 3 value 794.521960
#> iter 4 value 792.806359
#> iter 5 value 759.823345
#> iter 6 value 753.131310
#> iter 7 value 752.308301
#> iter 8 value 752.281400
#> iter 9 value 752.281244
#> iter 10 value 752.281227
#> iter 11 value 752.281206
#> iter 12 value 752.281193
#> iter 12 value 752.281193
#> iter 12 value 752.281193
#> final value 752.281193
#> converged
#> This is Run number 287
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.01002142 -0.09028931 -4.2899786 -1.7902893 2
#> 2 1 -1.35 -13.20 0.89112257 -0.53238291 -0.4588774 -13.7323829 1
#> 3 1 -2.05 -14.20 0.45559321 -0.60047563 -1.5944068 -14.8004756 1
#> 4 1 -1.55 -3.10 -0.79662707 0.59398617 -2.3466271 -2.5060138 1
#> 5 1 -1.90 -3.60 -0.08803459 -0.45434818 -1.9880346 -4.0543482 1
#> 6 1 -13.70 -1.85 -1.23708278 1.12219741 -14.9370828 -0.7278026 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3960 -39650 9625
#> initial value 998.131940
#> iter 2 value 778.315333
#> iter 3 value 759.801100
#> iter 4 value 756.487358
#> iter 5 value 727.172069
#> iter 6 value 720.491963
#> iter 7 value 719.635180
#> iter 8 value 719.590215
#> iter 9 value 719.590164
#> iter 9 value 719.590157
#> iter 9 value 719.590148
#> final value 719.590148
#> converged
#> This is Run number 288
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.005592474 1.5207816 -4.3055925 -0.1792184 2
#> 2 1 -1.35 -13.20 1.461260638 -1.3298460 0.1112606 -14.5298460 1
#> 3 1 -2.05 -14.20 -0.099191314 0.9397799 -2.1491913 -13.2602201 1
#> 4 1 -1.55 -3.10 -0.177414215 0.5431427 -1.7274142 -2.5568573 1
#> 5 1 -1.90 -3.60 -1.218760102 0.4557266 -3.1187601 -3.1442734 1
#> 6 1 -13.70 -1.85 -0.097528034 1.3205385 -13.7975280 -0.5294615 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4240 -36875 10475
#> initial value 998.131940
#> iter 2 value 813.455758
#> iter 3 value 793.995916
#> iter 4 value 793.932201
#> iter 5 value 762.000764
#> iter 6 value 755.841071
#> iter 7 value 755.292564
#> iter 8 value 755.275988
#> iter 9 value 755.275917
#> iter 10 value 755.275695
#> iter 11 value 755.275679
#> iter 12 value 755.275642
#> iter 12 value 755.275642
#> iter 12 value 755.275642
#> final value 755.275642
#> converged
#> This is Run number 289
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.4661131 0.65126080 -2.8338869 -1.048739 2
#> 2 1 -1.35 -13.20 2.2461491 0.04720438 0.8961491 -13.152796 1
#> 3 1 -2.05 -14.20 2.6758012 1.23077588 0.6258012 -12.969224 1
#> 4 1 -1.55 -3.10 0.1523104 1.39854980 -1.3976896 -1.701450 1
#> 5 1 -1.90 -3.60 -0.5243699 0.47053169 -2.4243699 -3.129468 1
#> 6 1 -13.70 -1.85 0.2634620 -1.19315477 -13.4365380 -3.043155 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3940 -37475 9175
#> initial value 998.131940
#> iter 2 value 814.516557
#> iter 3 value 798.099422
#> iter 4 value 796.208907
#> iter 5 value 762.989562
#> iter 6 value 756.103005
#> iter 7 value 755.191031
#> iter 8 value 755.162656
#> iter 9 value 755.162477
#> iter 10 value 755.162464
#> iter 10 value 755.162454
#> iter 10 value 755.162452
#> final value 755.162452
#> converged
#> This is Run number 290
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.8811203 1.663137129 -3.418880 -0.03686287 2
#> 2 1 -1.35 -13.20 -0.3469506 -0.037427947 -1.696951 -13.23742795 1
#> 3 1 -2.05 -14.20 -1.4438596 -1.213313887 -3.493860 -15.41331389 1
#> 4 1 -1.55 -3.10 3.8646143 0.009510164 2.314614 -3.09048984 1
#> 5 1 -1.90 -3.60 -0.1882801 0.585403505 -2.088280 -3.01459649 1
#> 6 1 -13.70 -1.85 0.5424111 0.972658397 -13.157589 -0.87734160 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3640 -36900 9100
#> initial value 998.131940
#> iter 2 value 822.853991
#> iter 3 value 806.190765
#> iter 4 value 803.899207
#> iter 5 value 768.924265
#> iter 6 value 762.128850
#> iter 7 value 761.185105
#> iter 8 value 761.158575
#> iter 9 value 761.158431
#> iter 9 value 761.158422
#> iter 9 value 761.158418
#> final value 761.158418
#> converged
#> This is Run number 291
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.0853070 -0.32616675 -3.2146930 -2.026167 2
#> 2 1 -1.35 -13.20 0.5094719 1.98171261 -0.8405281 -11.218287 1
#> 3 1 -2.05 -14.20 -0.4060204 0.71436516 -2.4560204 -13.485635 1
#> 4 1 -1.55 -3.10 -0.7885654 0.04206053 -2.3385654 -3.057939 1
#> 5 1 -1.90 -3.60 -1.4000297 -1.02485418 -3.3000297 -4.624854 1
#> 6 1 -13.70 -1.85 1.1430852 0.02071279 -12.5569148 -1.829287 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3340 -37525 9675
#> initial value 998.131940
#> iter 2 value 809.632510
#> iter 3 value 790.419283
#> iter 4 value 787.353865
#> iter 5 value 753.121434
#> iter 6 value 746.525313
#> iter 7 value 745.674251
#> iter 8 value 745.644612
#> iter 9 value 745.644554
#> iter 9 value 745.644552
#> iter 9 value 745.644552
#> final value 745.644552
#> converged
#> This is Run number 292
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 3.1433160 0.07142622 -1.156684 -1.628574 1
#> 2 1 -1.35 -13.20 0.1913835 -0.02872590 -1.158617 -13.228726 1
#> 3 1 -2.05 -14.20 0.6928527 -0.73433850 -1.357147 -14.934338 1
#> 4 1 -1.55 -3.10 0.4106620 -0.11144728 -1.139338 -3.211447 1
#> 5 1 -1.90 -3.60 0.7939931 1.71694440 -1.106007 -1.883056 1
#> 6 1 -13.70 -1.85 0.4827185 -0.50745524 -13.217282 -2.357455 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3220 -36350 9625
#> initial value 998.131940
#> iter 2 value 826.181938
#> iter 3 value 807.363463
#> iter 4 value 804.993375
#> iter 5 value 768.978549
#> iter 6 value 762.582959
#> iter 7 value 761.759766
#> iter 8 value 761.736951
#> iter 9 value 761.736846
#> iter 9 value 761.736840
#> iter 9 value 761.736837
#> final value 761.736837
#> converged
#> This is Run number 293
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.2939135 0.02065534 -4.0060865 -1.679345 2
#> 2 1 -1.35 -13.20 -0.1326837 -0.20675743 -1.4826837 -13.406757 1
#> 3 1 -2.05 -14.20 -1.2082286 -0.21184312 -3.2582286 -14.411843 1
#> 4 1 -1.55 -3.10 0.9435201 -0.69104557 -0.6064799 -3.791046 1
#> 5 1 -1.90 -3.60 0.3128266 -0.28131191 -1.5871734 -3.881312 1
#> 6 1 -13.70 -1.85 -0.9348729 0.36685095 -14.6348729 -1.483149 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3380 -37600 10000
#> initial value 998.131940
#> iter 2 value 806.200388
#> iter 3 value 786.153894
#> iter 4 value 783.528473
#> iter 5 value 750.105259
#> iter 6 value 743.687310
#> iter 7 value 742.907147
#> iter 8 value 742.877656
#> iter 9 value 742.877586
#> iter 10 value 742.877570
#> iter 10 value 742.877569
#> iter 10 value 742.877566
#> final value 742.877566
#> converged
#> This is Run number 294
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.2047734 -0.07117040 -2.0952266 -1.7711704 2
#> 2 1 -1.35 -13.20 0.6273771 0.82898458 -0.7226229 -12.3710154 1
#> 3 1 -2.05 -14.20 -1.5258126 0.01659252 -3.5758126 -14.1834075 1
#> 4 1 -1.55 -3.10 0.1286212 0.18653849 -1.4213788 -2.9134615 1
#> 5 1 -1.90 -3.60 0.3785517 -1.37234667 -1.5214483 -4.9723467 1
#> 6 1 -13.70 -1.85 1.5414486 1.95913569 -12.1585514 0.1091357 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4300 -38125 9025
#> initial value 998.131940
#> iter 2 value 806.310214
#> iter 3 value 790.792672
#> iter 4 value 789.187862
#> iter 5 value 757.635089
#> iter 6 value 750.555232
#> iter 7 value 749.631805
#> iter 8 value 749.600634
#> iter 9 value 749.600422
#> iter 9 value 749.600417
#> iter 9 value 749.600417
#> final value 749.600417
#> converged
#> This is Run number 295
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.71032338 0.4496104 -3.589677 -1.250390 2
#> 2 1 -1.35 -13.20 0.09175558 0.5889391 -1.258244 -12.611061 1
#> 3 1 -2.05 -14.20 0.16241848 1.0097580 -1.887582 -13.190242 1
#> 4 1 -1.55 -3.10 -0.45753970 -0.1996863 -2.007540 -3.299686 1
#> 5 1 -1.90 -3.60 0.87464914 -0.1078819 -1.025351 -3.707882 1
#> 6 1 -13.70 -1.85 -0.49093673 0.5167196 -14.190937 -1.333280 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3820 -35250 9925
#> initial value 998.131940
#> iter 2 value 838.906152
#> iter 3 value 820.917290
#> iter 4 value 820.617848
#> iter 5 value 785.343048
#> iter 6 value 779.341864
#> iter 7 value 778.707821
#> iter 8 value 778.694325
#> iter 9 value 778.694229
#> iter 9 value 778.694218
#> iter 9 value 778.694218
#> final value 778.694218
#> converged
#> This is Run number 296
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.0842912 2.9801989 -2.2157088 1.280199 2
#> 2 1 -1.35 -13.20 -0.2484459 1.5819958 -1.5984459 -11.618004 1
#> 3 1 -2.05 -14.20 -0.2005461 -0.8319286 -2.2505461 -15.031929 1
#> 4 1 -1.55 -3.10 0.6557030 0.2774537 -0.8942970 -2.822546 1
#> 5 1 -1.90 -3.60 1.2920698 0.4368375 -0.6079302 -3.163163 1
#> 6 1 -13.70 -1.85 -0.5797298 -0.3305493 -14.2797298 -2.180549 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3340 -37600 10500
#> initial value 998.131940
#> iter 2 value 802.282533
#> iter 3 value 780.660276
#> iter 4 value 778.535833
#> iter 5 value 745.783413
#> iter 6 value 739.674243
#> iter 7 value 738.986388
#> iter 8 value 738.957444
#> iter 9 value 738.957374
#> iter 10 value 738.957316
#> iter 10 value 738.957313
#> iter 10 value 738.957313
#> final value 738.957313
#> converged
#> This is Run number 297
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.4525657 1.76602532 -3.8474343 0.06602532 2
#> 2 1 -1.35 -13.20 0.5009320 -0.09320628 -0.8490680 -13.29320628 1
#> 3 1 -2.05 -14.20 0.1526725 -0.36450670 -1.8973275 -14.56450670 1
#> 4 1 -1.55 -3.10 0.5506733 -1.23468605 -0.9993267 -4.33468605 1
#> 5 1 -1.90 -3.60 -0.8312825 0.66470437 -2.7312825 -2.93529563 1
#> 6 1 -13.70 -1.85 -0.2482654 -0.89197829 -13.9482654 -2.74197829 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3180 -38175 10050
#> initial value 998.131940
#> iter 2 value 797.112475
#> iter 3 value 776.107109
#> iter 4 value 772.307630
#> iter 5 value 738.841613
#> iter 6 value 732.450683
#> iter 7 value 731.625117
#> iter 8 value 731.588302
#> iter 9 value 731.588282
#> iter 9 value 731.588278
#> iter 9 value 731.588275
#> final value 731.588275
#> converged
#> This is Run number 298
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.8740672 -0.05785213 -3.4259328 -1.7578521 2
#> 2 1 -1.35 -13.20 0.5307493 0.34144189 -0.8192507 -12.8585581 1
#> 3 1 -2.05 -14.20 0.9586017 1.93236110 -1.0913983 -12.2676389 1
#> 4 1 -1.55 -3.10 2.5131304 0.74722245 0.9631304 -2.3527776 1
#> 5 1 -1.90 -3.60 0.1505890 0.37048629 -1.7494110 -3.2295137 1
#> 6 1 -13.70 -1.85 0.7498464 1.32263263 -12.9501536 -0.5273674 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3640 -36850 8975
#> initial value 998.131940
#> iter 2 value 824.390255
#> iter 3 value 808.064588
#> iter 4 value 805.688929
#> iter 5 value 770.427020
#> iter 6 value 763.583438
#> iter 7 value 762.607730
#> iter 8 value 762.580942
#> iter 9 value 762.580800
#> iter 9 value 762.580792
#> iter 9 value 762.580789
#> final value 762.580789
#> converged
#> This is Run number 299
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.535986552 3.2562979 -3.764013 1.556298 2
#> 2 1 -1.35 -13.20 0.025330936 1.0122806 -1.324669 -12.187719 1
#> 3 1 -2.05 -14.20 0.224726808 -0.9748976 -1.825273 -15.174898 1
#> 4 1 -1.55 -3.10 -0.005009977 -1.0854870 -1.555010 -4.185487 1
#> 5 1 -1.90 -3.60 4.078611722 0.4503419 2.178612 -3.149658 1
#> 6 1 -13.70 -1.85 1.387087027 -0.2563283 -12.312913 -2.106328 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3600 -38850 9900
#> initial value 998.131940
#> iter 2 value 788.541555
#> iter 3 value 768.746015
#> iter 4 value 765.434140
#> iter 5 value 734.156886
#> iter 6 value 727.622226
#> iter 7 value 726.795831
#> iter 8 value 726.756086
#> iter 9 value 726.756049
#> iter 9 value 726.756041
#> iter 9 value 726.756041
#> final value 726.756041
#> converged
#> This is Run number 300
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.1305557 -0.2195508 -4.430556 -1.919551 2
#> 2 1 -1.35 -13.20 -0.9131808 -1.0618957 -2.263181 -14.261896 1
#> 3 1 -2.05 -14.20 -0.7058601 0.7136836 -2.755860 -13.486316 1
#> 4 1 -1.55 -3.10 -0.9529417 1.4572564 -2.502942 -1.642744 2
#> 5 1 -1.90 -3.60 -0.7428810 0.2989471 -2.642881 -3.301053 1
#> 6 1 -13.70 -1.85 -0.7942698 0.1806720 -14.494270 -1.669328 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3960 -37900 9175
#> initial value 998.131940
#> iter 2 value 808.380080
#> iter 3 value 791.828547
#> iter 4 value 789.638738
#> iter 5 value 757.102103
#> iter 6 value 750.145767
#> iter 7 value 749.230232
#> iter 8 value 749.199696
#> iter 9 value 749.199544
#> iter 9 value 749.199543
#> iter 9 value 749.199543
#> final value 749.199543
#> converged
#> This is Run number 301
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.96884238 -0.4213779 -2.3311576 -2.1213779 2
#> 2 1 -1.35 -13.20 3.63900789 0.8245054 2.2890079 -12.3754946 1
#> 3 1 -2.05 -14.20 0.20440814 0.1640179 -1.8455919 -14.0359821 1
#> 4 1 -1.55 -3.10 -0.03692513 -1.6044449 -1.5869251 -4.7044449 1
#> 5 1 -1.90 -3.60 1.52520611 0.2378934 -0.3747939 -3.3621066 1
#> 6 1 -13.70 -1.85 2.58913422 1.6599832 -11.1108658 -0.1900168 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3440 -35775 9500
#> initial value 998.131940
#> iter 2 value 834.953626
#> iter 3 value 817.255196
#> iter 4 value 815.724454
#> iter 5 value 779.563938
#> iter 6 value 773.261753
#> iter 7 value 772.456495
#> iter 8 value 772.436597
#> iter 9 value 772.436461
#> iter 10 value 772.436444
#> iter 11 value 772.436425
#> iter 12 value 772.436411
#> iter 12 value 772.436411
#> iter 12 value 772.436411
#> final value 772.436411
#> converged
#> This is Run number 302
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.4235302 2.3801462 -4.7235302 0.6801462 2
#> 2 1 -1.35 -13.20 -0.1771884 -0.1908309 -1.5271884 -13.3908309 1
#> 3 1 -2.05 -14.20 0.6439952 0.3946314 -1.4060048 -13.8053686 1
#> 4 1 -1.55 -3.10 0.4212451 0.1238533 -1.1287549 -2.9761467 1
#> 5 1 -1.90 -3.60 0.9911122 0.2551301 -0.9088878 -3.3448699 1
#> 6 1 -13.70 -1.85 0.1755289 -0.9636964 -13.5244711 -2.8136964 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3800 -35725 9250
#> initial value 998.131940
#> iter 2 value 837.709156
#> iter 3 value 821.476981
#> iter 4 value 820.506411
#> iter 5 value 784.707210
#> iter 6 value 778.305069
#> iter 7 value 777.464878
#> iter 8 value 777.444906
#> iter 9 value 777.444751
#> iter 10 value 777.444723
#> iter 11 value 777.444687
#> iter 12 value 777.444664
#> iter 12 value 777.444664
#> iter 12 value 777.444664
#> final value 777.444664
#> converged
#> This is Run number 303
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.4697567 0.59650018 -3.8302433 -1.103500 2
#> 2 1 -1.35 -13.20 -0.4048320 0.07684201 -1.7548320 -13.123158 1
#> 3 1 -2.05 -14.20 -0.6660483 -0.20546598 -2.7160483 -14.405466 1
#> 4 1 -1.55 -3.10 0.5192982 -0.65527423 -1.0307018 -3.755274 1
#> 5 1 -1.90 -3.60 2.8411354 -0.12114279 0.9411354 -3.721143 1
#> 6 1 -13.70 -1.85 0.7787265 0.42952182 -12.9212735 -1.420478 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3600 -36375 8875
#> initial value 998.131940
#> iter 2 value 831.490661
#> iter 3 value 815.534854
#> iter 4 value 813.356731
#> iter 5 value 777.201297
#> iter 6 value 770.441309
#> iter 7 value 769.449860
#> iter 8 value 769.424513
#> iter 9 value 769.424367
#> iter 9 value 769.424357
#> iter 9 value 769.424354
#> final value 769.424354
#> converged
#> This is Run number 304
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -1.3599237 1.1799069 -5.6599237 -0.5200931 2
#> 2 1 -1.35 -13.20 0.4157643 -0.5178277 -0.9342357 -13.7178277 1
#> 3 1 -2.05 -14.20 1.1719835 1.4267764 -0.8780165 -12.7732236 1
#> 4 1 -1.55 -3.10 1.6005013 3.2606037 0.0505013 0.1606037 2
#> 5 1 -1.90 -3.60 2.1851942 -0.5429896 0.2851942 -4.1429896 1
#> 6 1 -13.70 -1.85 0.5180413 -1.5906127 -13.1819587 -3.4406127 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3000 -36450 10950
#> initial value 998.131940
#> iter 2 value 814.260260
#> iter 3 value 790.871726
#> iter 4 value 789.229440
#> iter 5 value 755.080336
#> iter 6 value 749.428087
#> iter 7 value 748.844085
#> iter 8 value 748.822562
#> iter 9 value 748.822495
#> iter 10 value 748.822419
#> iter 10 value 748.822419
#> iter 11 value 748.822402
#> iter 11 value 748.822395
#> iter 11 value 748.822395
#> final value 748.822395
#> converged
#> This is Run number 305
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.39303252 -1.3779469 -3.9069675 -3.077947 2
#> 2 1 -1.35 -13.20 -0.33079438 1.2270354 -1.6807944 -11.972965 1
#> 3 1 -2.05 -14.20 1.31629933 1.3057001 -0.7337007 -12.894300 1
#> 4 1 -1.55 -3.10 0.09943472 0.2804925 -1.4505653 -2.819508 1
#> 5 1 -1.90 -3.60 0.49256357 2.4046127 -1.4074364 -1.195387 2
#> 6 1 -13.70 -1.85 1.29263108 -0.4447486 -12.4073689 -2.294749 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4120 -37475 9500
#> initial value 998.131940
#> iter 2 value 812.355346
#> iter 3 value 795.446100
#> iter 4 value 794.353286
#> iter 5 value 761.944155
#> iter 6 value 755.196932
#> iter 7 value 754.392856
#> iter 8 value 754.367125
#> iter 9 value 754.366938
#> iter 10 value 754.366906
#> iter 11 value 754.366864
#> iter 12 value 754.366841
#> iter 12 value 754.366841
#> iter 12 value 754.366841
#> final value 754.366841
#> converged
#> This is Run number 306
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 3.83900662 0.3636394 -0.4609934 -1.3363606 1
#> 2 1 -1.35 -13.20 2.81074471 1.2858730 1.4607447 -11.9141270 1
#> 3 1 -2.05 -14.20 -0.63449643 0.9254302 -2.6844964 -13.2745698 1
#> 4 1 -1.55 -3.10 3.18710020 2.0063756 1.6371002 -1.0936244 1
#> 5 1 -1.90 -3.60 0.02681755 -1.0974921 -1.8731824 -4.6974921 1
#> 6 1 -13.70 -1.85 -0.27267040 1.7048891 -13.9726704 -0.1451109 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3360 -36450 9525
#> initial value 998.131940
#> iter 2 value 825.733054
#> iter 3 value 807.485912
#> iter 4 value 805.286060
#> iter 5 value 769.656721
#> iter 6 value 763.182625
#> iter 7 value 762.342632
#> iter 8 value 762.319351
#> iter 9 value 762.319230
#> iter 9 value 762.319221
#> iter 9 value 762.319217
#> final value 762.319217
#> converged
#> This is Run number 307
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.90505724 -0.6530400 -5.205057 -2.353040 2
#> 2 1 -1.35 -13.20 -0.36728987 -1.0298968 -1.717290 -14.229897 1
#> 3 1 -2.05 -14.20 0.08357732 0.1770891 -1.966423 -14.022911 1
#> 4 1 -1.55 -3.10 -0.79032015 1.9371704 -2.340320 -1.162830 2
#> 5 1 -1.90 -3.60 -0.95137231 0.3048044 -2.851372 -3.295196 1
#> 6 1 -13.70 -1.85 1.26045255 -0.3470694 -12.439547 -2.197069 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3820 -37175 8900
#> initial value 998.131940
#> iter 2 value 820.533959
#> iter 3 value 804.670530
#> iter 4 value 802.405588
#> iter 5 value 768.010174
#> iter 6 value 761.057862
#> iter 7 value 760.065554
#> iter 8 value 760.037075
#> iter 9 value 760.036912
#> iter 9 value 760.036903
#> iter 9 value 760.036899
#> final value 760.036899
#> converged
#> This is Run number 308
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.3875027 0.1761467 -4.687503 -1.52385330 2
#> 2 1 -1.35 -13.20 3.0785665 0.2521829 1.728566 -12.94781714 1
#> 3 1 -2.05 -14.20 -0.6339465 0.1879502 -2.683947 -14.01204979 1
#> 4 1 -1.55 -3.10 -0.1822213 3.0565282 -1.732221 -0.04347175 2
#> 5 1 -1.90 -3.60 -0.9210536 0.8992700 -2.821054 -2.70073001 2
#> 6 1 -13.70 -1.85 2.4980424 -0.5638637 -11.201958 -2.41386369 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3400 -37775 9450
#> initial value 998.131940
#> iter 2 value 807.703941
#> iter 3 value 789.118534
#> iter 4 value 785.720033
#> iter 5 value 751.568711
#> iter 6 value 744.808726
#> iter 7 value 743.906300
#> iter 8 value 743.874902
#> iter 9 value 743.874863
#> iter 9 value 743.874863
#> iter 9 value 743.874863
#> final value 743.874863
#> converged
#> This is Run number 309
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.1084799 -0.7538011 -4.191520 -2.4538011 2
#> 2 1 -1.35 -13.20 -0.1711418 -0.2197460 -1.521142 -13.4197460 1
#> 3 1 -2.05 -14.20 3.4566685 0.9180775 1.406669 -13.2819225 1
#> 4 1 -1.55 -3.10 0.2923903 -0.1829827 -1.257610 -3.2829827 1
#> 5 1 -1.90 -3.60 -0.4696472 0.3591045 -2.369647 -3.2408955 1
#> 6 1 -13.70 -1.85 -0.8748174 1.3216623 -14.574817 -0.5283377 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4040 -36825 9225
#> initial value 998.131940
#> iter 2 value 823.370377
#> iter 3 value 807.285847
#> iter 4 value 806.151202
#> iter 5 value 772.267955
#> iter 6 value 765.537711
#> iter 7 value 764.664969
#> iter 8 value 764.640477
#> iter 9 value 764.640279
#> iter 9 value 764.640277
#> iter 9 value 764.640277
#> final value 764.640277
#> converged
#> This is Run number 310
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.13848341 0.9484683 -4.1615166 -0.7515317 2
#> 2 1 -1.35 -13.20 0.48375194 0.1931457 -0.8662481 -13.0068543 1
#> 3 1 -2.05 -14.20 -0.69155926 0.4951028 -2.7415593 -13.7048972 1
#> 4 1 -1.55 -3.10 0.36902592 0.6426294 -1.1809741 -2.4573706 1
#> 5 1 -1.90 -3.60 0.52379194 0.4859338 -1.3762081 -3.1140662 1
#> 6 1 -13.70 -1.85 0.07783077 -0.5375838 -13.6221692 -2.3875838 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3780 -38200 10075
#> initial value 998.131940
#> iter 2 value 797.263700
#> iter 3 value 777.706532
#> iter 4 value 775.848351
#> iter 5 value 744.464154
#> iter 6 value 737.996967
#> iter 7 value 737.258786
#> iter 8 value 737.227706
#> iter 9 value 737.227614
#> iter 10 value 737.227551
#> iter 10 value 737.227549
#> iter 10 value 737.227541
#> final value 737.227541
#> converged
#> This is Run number 311
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.45090356 -0.7965475 -2.8490964 -2.4965475 2
#> 2 1 -1.35 -13.20 -0.01913328 -1.4609906 -1.3691333 -14.6609906 1
#> 3 1 -2.05 -14.20 0.29798698 -0.7732295 -1.7520130 -14.9732295 1
#> 4 1 -1.55 -3.10 -0.70130370 2.7534386 -2.2513037 -0.3465614 2
#> 5 1 -1.90 -3.60 2.16067466 0.2656153 0.2606747 -3.3343847 1
#> 6 1 -13.70 -1.85 1.38324614 -0.9023655 -12.3167539 -2.7523655 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3500 -37225 9700
#> initial value 998.131940
#> iter 2 value 813.923844
#> iter 3 value 795.187383
#> iter 4 value 792.894788
#> iter 5 value 758.909469
#> iter 6 value 752.359659
#> iter 7 value 751.543129
#> iter 8 value 751.516452
#> iter 9 value 751.516341
#> iter 9 value 751.516333
#> iter 9 value 751.516333
#> final value 751.516333
#> converged
#> This is Run number 312
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.2293938 0.4373371 -4.5293938 -1.2626629 2
#> 2 1 -1.35 -13.20 0.7326824 0.1367228 -0.6173176 -13.0632772 1
#> 3 1 -2.05 -14.20 1.0035999 -0.3086338 -1.0464001 -14.5086338 1
#> 4 1 -1.55 -3.10 0.1227597 2.6159977 -1.4272403 -0.4840023 2
#> 5 1 -1.90 -3.60 -1.1072048 2.1380574 -3.0072048 -1.4619426 2
#> 6 1 -13.70 -1.85 0.1648017 1.6311102 -13.5351983 -0.2188898 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3520 -37450 9475
#> initial value 998.131940
#> iter 2 value 812.367091
#> iter 3 value 794.184719
#> iter 4 value 791.486592
#> iter 5 value 757.457276
#> iter 6 value 750.747636
#> iter 7 value 749.872737
#> iter 8 value 749.844145
#> iter 9 value 749.844051
#> iter 9 value 749.844050
#> iter 9 value 749.844050
#> final value 749.844050
#> converged
#> This is Run number 313
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.9474663 -0.4998076 -2.3525337 -2.199808 2
#> 2 1 -1.35 -13.20 -0.3501361 0.7415333 -1.7001361 -12.458467 1
#> 3 1 -2.05 -14.20 1.1231429 0.1350479 -0.9268571 -14.064952 1
#> 4 1 -1.55 -3.10 0.4632934 -0.8380602 -1.0867066 -3.938060 1
#> 5 1 -1.90 -3.60 -0.2245976 0.5671308 -2.1245976 -3.032869 1
#> 6 1 -13.70 -1.85 -0.1188840 0.1180610 -13.8188840 -1.731939 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3540 -37375 10150
#> initial value 998.131940
#> iter 2 value 808.475122
#> iter 3 value 788.482562
#> iter 4 value 786.697212
#> iter 5 value 753.710349
#> iter 6 value 747.384893
#> iter 7 value 746.666515
#> iter 8 value 746.640319
#> iter 9 value 746.640216
#> iter 10 value 746.640171
#> iter 11 value 746.640160
#> iter 12 value 746.640146
#> iter 12 value 746.640146
#> iter 12 value 746.640146
#> final value 746.640146
#> converged
#> This is Run number 314
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.77634124 0.671356693 -2.5236588 -1.028643 2
#> 2 1 -1.35 -13.20 0.05664087 -0.668926994 -1.2933591 -13.868927 1
#> 3 1 -2.05 -14.20 -0.74403160 -0.482725285 -2.7940316 -14.682725 1
#> 4 1 -1.55 -3.10 -0.26249447 -0.232739072 -1.8124945 -3.332739 1
#> 5 1 -1.90 -3.60 0.92314710 0.002442867 -0.9768529 -3.597557 1
#> 6 1 -13.70 -1.85 -0.13389349 3.201942174 -13.8338935 1.351942 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3780 -37400 9350
#> initial value 998.131940
#> iter 2 value 814.233933
#> iter 3 value 797.028313
#> iter 4 value 794.963653
#> iter 5 value 761.469074
#> iter 6 value 754.689085
#> iter 7 value 753.810001
#> iter 8 value 753.782279
#> iter 9 value 753.782128
#> iter 9 value 753.782126
#> iter 9 value 753.782126
#> final value 753.782126
#> converged
#> This is Run number 315
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.2439110 -0.6366086 -3.0560890 -2.336609 2
#> 2 1 -1.35 -13.20 0.6045262 0.9971439 -0.7454738 -12.202856 1
#> 3 1 -2.05 -14.20 0.1299239 -1.0117828 -1.9200761 -15.211783 1
#> 4 1 -1.55 -3.10 -0.7002077 -0.8455567 -2.2502077 -3.945557 1
#> 5 1 -1.90 -3.60 0.6163777 -0.4901336 -1.2836223 -4.090134 1
#> 6 1 -13.70 -1.85 1.0668010 -0.5230006 -12.6331990 -2.373001 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3060 -37300 9975
#> initial value 998.131940
#> iter 2 value 810.237768
#> iter 3 value 789.563630
#> iter 4 value 786.238470
#> iter 5 value 751.236710
#> iter 6 value 744.868989
#> iter 7 value 744.059283
#> iter 8 value 744.029949
#> iter 9 value 744.029912
#> iter 9 value 744.029910
#> iter 9 value 744.029909
#> final value 744.029909
#> converged
#> This is Run number 316
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.1283850 3.6687405 -4.428385 1.9687405 2
#> 2 1 -1.35 -13.20 -0.6048240 -0.2736267 -1.954824 -13.4736267 1
#> 3 1 -2.05 -14.20 0.8957949 0.5269774 -1.154205 -13.6730226 1
#> 4 1 -1.55 -3.10 3.0676004 -1.2247317 1.517600 -4.3247317 1
#> 5 1 -1.90 -3.60 0.5441498 -0.8196316 -1.355850 -4.4196316 1
#> 6 1 -13.70 -1.85 -1.4418232 1.3937564 -15.141823 -0.4562436 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4160 -37225 9775
#> initial value 998.131940
#> iter 2 value 813.922305
#> iter 3 value 796.392496
#> iter 4 value 795.759400
#> iter 5 value 763.370378
#> iter 6 value 756.790558
#> iter 7 value 756.069790
#> iter 8 value 756.047368
#> iter 9 value 756.047207
#> iter 10 value 756.047140
#> iter 11 value 756.047072
#> iter 12 value 756.047059
#> iter 12 value 756.047059
#> iter 12 value 756.047059
#> final value 756.047059
#> converged
#> This is Run number 317
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.42969864 0.1170132 -1.8703014 -1.582987 2
#> 2 1 -1.35 -13.20 -0.08623965 6.5044182 -1.4362397 -6.695582 1
#> 3 1 -2.05 -14.20 1.51527459 -0.1217496 -0.5347254 -14.321750 1
#> 4 1 -1.55 -3.10 -0.07354377 -1.2149665 -1.6235438 -4.314967 1
#> 5 1 -1.90 -3.60 -0.81973378 -1.6516425 -2.7197338 -5.251643 1
#> 6 1 -13.70 -1.85 -0.60472424 4.1326372 -14.3047242 2.282637 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3760 -38375 9650
#> initial value 998.131940
#> iter 2 value 797.790034
#> iter 3 value 779.303647
#> iter 4 value 776.672990
#> iter 5 value 744.916141
#> iter 6 value 738.195826
#> iter 7 value 737.360545
#> iter 8 value 737.326876
#> iter 9 value 737.326805
#> iter 10 value 737.326788
#> iter 10 value 737.326788
#> iter 10 value 737.326787
#> final value 737.326787
#> converged
#> This is Run number 318
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.2231486 0.8864230 -4.0768514 -0.813577 2
#> 2 1 -1.35 -13.20 -0.9780446 0.2551522 -2.3280446 -12.944848 1
#> 3 1 -2.05 -14.20 2.1360783 0.9259398 0.0860783 -13.274060 1
#> 4 1 -1.55 -3.10 0.5056790 0.1691415 -1.0443210 -2.930859 1
#> 5 1 -1.90 -3.60 0.5514842 -1.2388721 -1.3485158 -4.838872 1
#> 6 1 -13.70 -1.85 -0.9385918 -0.3816640 -14.6385918 -2.231664 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2680 -35325 10275
#> initial value 998.131940
#> iter 2 value 833.889623
#> iter 3 value 812.312957
#> iter 4 value 810.081616
#> iter 5 value 772.670767
#> iter 6 value 766.907363
#> iter 7 value 766.238765
#> iter 8 value 766.221205
#> iter 9 value 766.221134
#> iter 9 value 766.221129
#> iter 9 value 766.221129
#> final value 766.221129
#> converged
#> This is Run number 319
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.3304850 -0.97053527 -3.9695150 -2.670535 2
#> 2 1 -1.35 -13.20 1.5759239 0.77845952 0.2259239 -12.421540 1
#> 3 1 -2.05 -14.20 1.2087106 0.02172083 -0.8412894 -14.178279 1
#> 4 1 -1.55 -3.10 -0.4169531 0.47007372 -1.9669531 -2.629926 1
#> 5 1 -1.90 -3.60 -0.1357496 -0.49815858 -2.0357496 -4.098159 1
#> 6 1 -13.70 -1.85 0.5081276 -0.33559339 -13.1918724 -2.185593 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3000 -35850 10450
#> initial value 998.131940
#> iter 2 value 826.284151
#> iter 3 value 804.745461
#> iter 4 value 803.034423
#> iter 5 value 767.462020
#> iter 6 value 761.637937
#> iter 7 value 761.001585
#> iter 8 value 760.982979
#> iter 9 value 760.982893
#> iter 10 value 760.982863
#> iter 11 value 760.982840
#> iter 11 value 760.982839
#> iter 11 value 760.982839
#> final value 760.982839
#> converged
#> This is Run number 320
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.30117798 -0.08379074 -3.9988220 -1.7837907 2
#> 2 1 -1.35 -13.20 0.49215071 5.72017345 -0.8578493 -7.4798265 1
#> 3 1 -2.05 -14.20 0.10665889 -1.25667513 -1.9433411 -15.4566751 1
#> 4 1 -1.55 -3.10 0.08542169 -0.76000108 -1.4645783 -3.8600011 1
#> 5 1 -1.90 -3.60 -0.21779539 -0.02536509 -2.1177954 -3.6253651 1
#> 6 1 -13.70 -1.85 -0.24157288 2.30276549 -13.9415729 0.4527655 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3300 -37250 9925
#> initial value 998.131940
#> iter 2 value 811.664289
#> iter 3 value 791.790929
#> iter 4 value 789.163974
#> iter 5 value 754.942173
#> iter 6 value 748.530622
#> iter 7 value 747.740987
#> iter 8 value 747.713553
#> iter 9 value 747.713476
#> iter 9 value 747.713466
#> iter 9 value 747.713466
#> final value 747.713466
#> converged
#> This is Run number 321
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.8286142 0.1640196 -3.4713858 -1.535980 2
#> 2 1 -1.35 -13.20 0.8792822 0.7380449 -0.4707178 -12.461955 1
#> 3 1 -2.05 -14.20 -1.2479138 5.0137164 -3.2979138 -9.186284 1
#> 4 1 -1.55 -3.10 -1.7491712 -0.6054083 -3.2991712 -3.705408 1
#> 5 1 -1.90 -3.60 2.2006529 -0.8401632 0.3006529 -4.440163 1
#> 6 1 -13.70 -1.85 0.9045792 0.5262299 -12.7954208 -1.323770 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3580 -36925 9975
#> initial value 998.131940
#> iter 2 value 816.176882
#> iter 3 value 796.974631
#> iter 4 value 795.438655
#> iter 5 value 761.738375
#> iter 6 value 755.379524
#> iter 7 value 754.648328
#> iter 8 value 754.624931
#> iter 9 value 754.624803
#> iter 10 value 754.624768
#> iter 11 value 754.624737
#> iter 11 value 754.624734
#> iter 11 value 754.624734
#> final value 754.624734
#> converged
#> This is Run number 322
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.3564402 4.2671612 -4.6564402 2.5671612 2
#> 2 1 -1.35 -13.20 -0.7308375 -0.3108681 -2.0808375 -13.5108681 1
#> 3 1 -2.05 -14.20 -0.9664308 -1.2812507 -3.0164308 -15.4812507 1
#> 4 1 -1.55 -3.10 -1.3911590 -0.4686264 -2.9411590 -3.5686264 1
#> 5 1 -1.90 -3.60 1.0306228 1.2569639 -0.8693772 -2.3430361 1
#> 6 1 -13.70 -1.85 0.3844099 2.2696256 -13.3155901 0.4196256 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3460 -35325 9625
#> initial value 998.131940
#> iter 2 value 839.845552
#> iter 3 value 822.019764
#> iter 4 value 820.915721
#> iter 5 value 784.561698
#> iter 6 value 778.450561
#> iter 7 value 777.706015
#> iter 8 value 777.688927
#> iter 9 value 777.688803
#> iter 9 value 777.688797
#> iter 9 value 777.688797
#> final value 777.688797
#> converged
#> This is Run number 323
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.7769377 1.63131645 -5.076938 -0.06868355 2
#> 2 1 -1.35 -13.20 -0.8659529 -0.64239655 -2.215953 -13.84239655 1
#> 3 1 -2.05 -14.20 -0.4009665 0.03800023 -2.450967 -14.16199977 1
#> 4 1 -1.55 -3.10 0.3016572 4.12639920 -1.248343 1.02639920 2
#> 5 1 -1.90 -3.60 -0.3376456 1.72016667 -2.237646 -1.87983333 2
#> 6 1 -13.70 -1.85 -0.8187609 0.70457761 -14.518761 -1.14542239 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3620 -35150 9050
#> initial value 998.131940
#> iter 2 value 846.227277
#> iter 3 value 830.380479
#> iter 4 value 829.229562
#> iter 5 value 792.055713
#> iter 6 value 785.774705
#> iter 7 value 784.898798
#> iter 8 value 784.879514
#> iter 9 value 784.879379
#> iter 10 value 784.879357
#> iter 11 value 784.879330
#> iter 12 value 784.879312
#> iter 12 value 784.879312
#> iter 12 value 784.879312
#> final value 784.879312
#> converged
#> This is Run number 324
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.16370333 0.38895107 -4.4637033 -1.3110489 2
#> 2 1 -1.35 -13.20 0.65536849 1.20097812 -0.6946315 -11.9990219 1
#> 3 1 -2.05 -14.20 -1.06189187 0.03050243 -3.1118919 -14.1694976 1
#> 4 1 -1.55 -3.10 0.02293193 -1.40750555 -1.5270681 -4.5075056 1
#> 5 1 -1.90 -3.60 -0.55104656 -0.35798233 -2.4510466 -3.9579823 1
#> 6 1 -13.70 -1.85 -1.15106886 1.69157638 -14.8510689 -0.1584236 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3720 -36675 9225
#> initial value 998.131940
#> iter 2 value 825.174483
#> iter 3 value 808.469822
#> iter 4 value 806.687925
#> iter 5 value 771.867404
#> iter 6 value 765.186822
#> iter 7 value 764.289632
#> iter 8 value 764.264808
#> iter 9 value 764.264641
#> iter 10 value 764.264626
#> iter 11 value 764.264614
#> iter 12 value 764.264602
#> iter 12 value 764.264602
#> iter 12 value 764.264602
#> final value 764.264602
#> converged
#> This is Run number 325
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.5088386 -0.40962283 -3.79116141 -2.10962283 2
#> 2 1 -1.35 -13.20 2.5917153 0.09545749 1.24171526 -13.10454251 1
#> 3 1 -2.05 -14.20 1.2991660 0.38315968 -0.75083398 -13.81684032 1
#> 4 1 -1.55 -3.10 0.6694712 3.68689159 -0.88052879 0.58689159 2
#> 5 1 -1.90 -3.60 1.8803372 3.64730235 -0.01966276 0.04730235 2
#> 6 1 -13.70 -1.85 0.3886913 -0.83285222 -13.31130870 -2.68285222 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4040 -36700 8000
#> initial value 998.131940
#> iter 2 value 832.967537
#> iter 3 value 819.894851
#> iter 4 value 817.695454
#> iter 5 value 781.772460
#> iter 6 value 774.589761
#> iter 7 value 773.339852
#> iter 8 value 773.307302
#> iter 9 value 773.307120
#> iter 9 value 773.307113
#> iter 9 value 773.307110
#> final value 773.307110
#> converged
#> This is Run number 326
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.0407468 0.4144066 -3.25925316 -1.2855934 2
#> 2 1 -1.35 -13.20 -0.1713071 1.6369433 -1.52130706 -11.5630567 1
#> 3 1 -2.05 -14.20 1.4444441 0.4642603 -0.60555591 -13.7357397 1
#> 4 1 -1.55 -3.10 -0.3386587 0.8708887 -1.88865875 -2.2291113 1
#> 5 1 -1.90 -3.60 1.8796938 1.8911763 -0.02030619 -1.7088237 1
#> 6 1 -13.70 -1.85 0.2422851 0.9553887 -13.45771494 -0.8946113 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3300 -36600 9875
#> initial value 998.131940
#> iter 2 value 821.073137
#> iter 3 value 801.640577
#> iter 4 value 799.524523
#> iter 5 value 764.508345
#> iter 6 value 758.184272
#> iter 7 value 757.414534
#> iter 8 value 757.391317
#> iter 9 value 757.391207
#> iter 9 value 757.391198
#> iter 9 value 757.391198
#> final value 757.391198
#> converged
#> This is Run number 327
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.0176417 0.1589333 -2.282358 -1.5410667 2
#> 2 1 -1.35 -13.20 2.8780160 3.0665657 1.528016 -10.1334343 1
#> 3 1 -2.05 -14.20 0.4812888 -0.4684114 -1.568711 -14.6684114 1
#> 4 1 -1.55 -3.10 -0.3461285 1.0889769 -1.896128 -2.0110231 1
#> 5 1 -1.90 -3.60 -0.7809723 1.8660175 -2.680972 -1.7339825 2
#> 6 1 -13.70 -1.85 -0.6316593 2.2987893 -14.331659 0.4487893 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3520 -35875 9925
#> initial value 998.131940
#> iter 2 value 830.637343
#> iter 3 value 811.859254
#> iter 4 value 810.810603
#> iter 5 value 775.674253
#> iter 6 value 769.530716
#> iter 7 value 768.833340
#> iter 8 value 768.815362
#> iter 9 value 768.815236
#> iter 10 value 768.815211
#> iter 11 value 768.815171
#> iter 12 value 768.815148
#> iter 12 value 768.815148
#> iter 12 value 768.815148
#> final value 768.815148
#> converged
#> This is Run number 328
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.1165390 0.3726533 -4.183461 -1.3273467 2
#> 2 1 -1.35 -13.20 -0.1009054 -1.1961589 -1.450905 -14.3961589 1
#> 3 1 -2.05 -14.20 0.8404710 2.1472356 -1.209529 -12.0527644 1
#> 4 1 -1.55 -3.10 0.6640320 -0.9451834 -0.885968 -4.0451834 1
#> 5 1 -1.90 -3.60 -1.0161976 -0.2993636 -2.916198 -3.8993636 1
#> 6 1 -13.70 -1.85 0.8683246 2.2580527 -12.831675 0.4080527 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3700 -35875 9000
#> initial value 998.131940
#> iter 2 value 837.381591
#> iter 3 value 821.548176
#> iter 4 value 820.071716
#> iter 5 value 783.829486
#> iter 6 value 777.284575
#> iter 7 value 776.355402
#> iter 8 value 776.332748
#> iter 9 value 776.332586
#> iter 10 value 776.332567
#> iter 11 value 776.332550
#> iter 12 value 776.332536
#> iter 12 value 776.332536
#> iter 12 value 776.332536
#> final value 776.332536
#> converged
#> This is Run number 329
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.5157436 0.8894838 -4.8157436 -0.8105162 2
#> 2 1 -1.35 -13.20 -1.1238849 -0.3732426 -2.4738849 -13.5732426 1
#> 3 1 -2.05 -14.20 1.5801066 2.6101922 -0.4698934 -11.5898078 1
#> 4 1 -1.55 -3.10 -1.1236651 1.2438757 -2.6736651 -1.8561243 2
#> 5 1 -1.90 -3.60 0.7747393 -0.3062045 -1.1252607 -3.9062045 1
#> 6 1 -13.70 -1.85 -1.1418143 0.6053495 -14.8418143 -1.2446505 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3480 -35525 8950
#> initial value 998.131940
#> iter 2 value 842.012102
#> iter 3 value 825.967442
#> iter 4 value 824.221827
#> iter 5 value 786.888430
#> iter 6 value 780.430722
#> iter 7 value 779.493980
#> iter 8 value 779.472311
#> iter 9 value 779.472175
#> iter 10 value 779.472162
#> iter 10 value 779.472153
#> iter 10 value 779.472151
#> final value 779.472151
#> converged
#> This is Run number 330
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.0816474 0.54609266 -3.21835264 -1.1539073 2
#> 2 1 -1.35 -13.20 0.6413627 -0.52886176 -0.70863729 -13.7288618 1
#> 3 1 -2.05 -14.20 0.4630442 -0.58385343 -1.58695585 -14.7838534 1
#> 4 1 -1.55 -3.10 1.5998861 -0.16946370 0.04988611 -3.2694637 1
#> 5 1 -1.90 -3.60 1.0057081 -0.03890208 -0.89429190 -3.6389021 1
#> 6 1 -13.70 -1.85 -0.7413006 1.37826232 -14.44130064 -0.4717377 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3360 -37000 8675
#> initial value 998.131940
#> iter 2 value 823.942076
#> iter 3 value 807.549175
#> iter 4 value 804.152419
#> iter 5 value 767.179013
#> iter 6 value 760.110380
#> iter 7 value 759.053781
#> iter 8 value 759.026886
#> iter 9 value 759.026848
#> iter 9 value 759.026843
#> iter 9 value 759.026843
#> final value 759.026843
#> converged
#> This is Run number 331
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.4681133 4.6263904 -3.83188668 2.92639039 2
#> 2 1 -1.35 -13.20 1.2607819 0.8568091 -0.08921806 -12.34319092 1
#> 3 1 -2.05 -14.20 -1.1447974 1.9557453 -3.19479744 -12.24425467 1
#> 4 1 -1.55 -3.10 1.1819794 1.1460038 -0.36802060 -1.95399623 1
#> 5 1 -1.90 -3.60 -0.1020060 -1.1396536 -2.00200596 -4.73965356 1
#> 6 1 -13.70 -1.85 -0.7982400 1.8119591 -14.49823999 -0.03804092 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3820 -37075 9375
#> initial value 998.131940
#> iter 2 value 818.683630
#> iter 3 value 801.637067
#> iter 4 value 799.961923
#> iter 5 value 766.159487
#> iter 6 value 759.452345
#> iter 7 value 758.592455
#> iter 8 value 758.566738
#> iter 9 value 758.566566
#> iter 9 value 758.566562
#> iter 9 value 758.566562
#> final value 758.566562
#> converged
#> This is Run number 332
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.8023011 0.49673798 -3.4976989 -1.203262 2
#> 2 1 -1.35 -13.20 0.8370757 -0.73159177 -0.5129243 -13.931592 1
#> 3 1 -2.05 -14.20 -0.5247501 0.02395618 -2.5747501 -14.176044 1
#> 4 1 -1.55 -3.10 0.8098114 -0.93565909 -0.7401886 -4.035659 1
#> 5 1 -1.90 -3.60 -0.3644395 0.26034665 -2.2644395 -3.339653 1
#> 6 1 -13.70 -1.85 -0.8414954 -1.39711507 -14.5414954 -3.247115 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3160 -37650 10175
#> initial value 998.131940
#> iter 2 value 803.850102
#> iter 3 value 782.704000
#> iter 4 value 779.564072
#> iter 5 value 745.713849
#> iter 6 value 739.424457
#> iter 7 value 738.648676
#> iter 8 value 738.617159
#> iter 9 value 738.617119
#> iter 9 value 738.617109
#> iter 9 value 738.617108
#> final value 738.617108
#> converged
#> This is Run number 333
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.06756339 0.32555806 -4.2324366 -1.374442 2
#> 2 1 -1.35 -13.20 0.37557640 0.44599720 -0.9744236 -12.754003 1
#> 3 1 -2.05 -14.20 0.38549491 0.00105752 -1.6645051 -14.198942 1
#> 4 1 -1.55 -3.10 -0.01001389 -0.98194395 -1.5600139 -4.081944 1
#> 5 1 -1.90 -3.60 -0.52282557 0.88047993 -2.4228256 -2.719520 1
#> 6 1 -13.70 -1.85 -1.06334201 -0.84780385 -14.7633420 -2.697804 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3320 -36625 9450
#> initial value 998.131940
#> iter 2 value 823.835945
#> iter 3 value 805.609807
#> iter 4 value 803.085510
#> iter 5 value 767.359696
#> iter 6 value 760.804619
#> iter 7 value 759.935449
#> iter 8 value 759.910953
#> iter 9 value 759.910847
#> iter 9 value 759.910842
#> iter 9 value 759.910839
#> final value 759.910839
#> converged
#> This is Run number 334
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.1841831 -0.2755675 -4.1158169 -1.9755675 2
#> 2 1 -1.35 -13.20 0.7953825 -0.8368368 -0.5546175 -14.0368368 1
#> 3 1 -2.05 -14.20 -0.3727516 1.0999819 -2.4227516 -13.1000181 1
#> 4 1 -1.55 -3.10 2.5622362 -0.6848424 1.0122362 -3.7848424 1
#> 5 1 -1.90 -3.60 0.7306380 2.8572286 -1.1693620 -0.7427714 2
#> 6 1 -13.70 -1.85 -0.2117059 -0.5373624 -13.9117059 -2.3873624 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2380 -34750 11275
#> initial value 998.131940
#> iter 2 value 832.419055
#> iter 3 value 807.126136
#> iter 4 value 805.503507
#> iter 5 value 769.062932
#> iter 6 value 764.026463
#> iter 7 value 763.540924
#> iter 8 value 763.526859
#> iter 9 value 763.526813
#> iter 10 value 763.526769
#> iter 10 value 763.526767
#> iter 10 value 763.526767
#> final value 763.526767
#> converged
#> This is Run number 335
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.97534959 0.14010885 -5.2753496 -1.5598911 2
#> 2 1 -1.35 -13.20 -0.49566011 -0.08910986 -1.8456601 -13.2891099 1
#> 3 1 -2.05 -14.20 0.83371464 -0.01736963 -1.2162854 -14.2173696 1
#> 4 1 -1.55 -3.10 0.01526452 -0.63592440 -1.5347355 -3.7359244 1
#> 5 1 -1.90 -3.60 1.58620269 1.99372789 -0.3137973 -1.6062721 1
#> 6 1 -13.70 -1.85 -0.77244645 1.61501460 -14.4724464 -0.2349854 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3960 -37700 10175
#> initial value 998.131940
#> iter 2 value 803.988121
#> iter 3 value 784.716487
#> iter 4 value 783.781992
#> iter 5 value 752.207591
#> iter 6 value 745.803514
#> iter 7 value 745.129794
#> iter 8 value 745.104552
#> iter 9 value 745.104433
#> iter 10 value 745.104318
#> iter 10 value 745.104313
#> iter 10 value 745.104313
#> final value 745.104313
#> converged
#> This is Run number 336
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.3930272 0.6095210 -4.69302722 -1.090479 2
#> 2 1 -1.35 -13.20 1.4179738 -0.6348329 0.06797383 -13.834833 1
#> 3 1 -2.05 -14.20 3.7528698 0.4238953 1.70286982 -13.776105 1
#> 4 1 -1.55 -3.10 0.3281842 -0.1994531 -1.22181580 -3.299453 1
#> 5 1 -1.90 -3.60 -0.3413476 -0.4300392 -2.24134764 -4.030039 1
#> 6 1 -13.70 -1.85 0.1912207 -0.7219500 -13.50877926 -2.571950 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3220 -36975 10200
#> initial value 998.131940
#> iter 2 value 813.340275
#> iter 3 value 792.599317
#> iter 4 value 790.307931
#> iter 5 value 756.012035
#> iter 6 value 749.807610
#> iter 7 value 749.080196
#> iter 8 value 749.054838
#> iter 9 value 749.054756
#> iter 10 value 749.054735
#> iter 10 value 749.054725
#> iter 10 value 749.054725
#> final value 749.054725
#> converged
#> This is Run number 337
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.75979085 0.0248115 -3.5402092 -1.67518850 2
#> 2 1 -1.35 -13.20 -0.03279583 0.5774298 -1.3827958 -12.62257021 1
#> 3 1 -2.05 -14.20 -1.21479674 -0.9218003 -3.2647967 -15.12180028 1
#> 4 1 -1.55 -3.10 0.93026621 3.0248510 -0.6197338 -0.07514898 2
#> 5 1 -1.90 -3.60 1.06517898 -0.4680953 -0.8348210 -4.06809529 1
#> 6 1 -13.70 -1.85 -0.43530465 -1.1854787 -14.1353046 -3.03547875 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3600 -38475 10275
#> initial value 998.131940
#> iter 2 value 791.415581
#> iter 3 value 770.725576
#> iter 4 value 768.330083
#> iter 5 value 737.089337
#> iter 6 value 730.774713
#> iter 7 value 730.035742
#> iter 8 value 730.000549
#> iter 9 value 730.000485
#> iter 10 value 730.000426
#> iter 11 value 730.000390
#> iter 11 value 730.000383
#> iter 11 value 730.000383
#> final value 730.000383
#> converged
#> This is Run number 338
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -1.5982693 -0.5813733 -5.898269 -2.2813733 2
#> 2 1 -1.35 -13.20 -0.5883010 -0.0139465 -1.938301 -13.2139465 1
#> 3 1 -2.05 -14.20 1.0481251 0.9454787 -1.001875 -13.2545213 1
#> 4 1 -1.55 -3.10 -1.0565285 0.4957745 -2.606528 -2.6042255 2
#> 5 1 -1.90 -3.60 -0.6552423 3.0430656 -2.555242 -0.5569344 2
#> 6 1 -13.70 -1.85 1.2730500 2.6034848 -12.426950 0.7534848 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3180 -38300 10350
#> initial value 998.131940
#> iter 2 value 792.937424
#> iter 3 value 771.012992
#> iter 4 value 767.475982
#> iter 5 value 734.701309
#> iter 6 value 728.505252
#> iter 7 value 727.727889
#> iter 8 value 727.689729
#> iter 9 value 727.689698
#> iter 9 value 727.689696
#> iter 9 value 727.689696
#> final value 727.689696
#> converged
#> This is Run number 339
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -1.1474061 1.33217819 -5.4474061 -0.3678218 2
#> 2 1 -1.35 -13.20 -0.8666738 -0.05869981 -2.2166738 -13.2586998 1
#> 3 1 -2.05 -14.20 1.4438479 0.18940207 -0.6061521 -14.0105979 1
#> 4 1 -1.55 -3.10 0.5126819 -0.34717804 -1.0373181 -3.4471780 1
#> 5 1 -1.90 -3.60 0.3616194 1.78167560 -1.5383806 -1.8183244 1
#> 6 1 -13.70 -1.85 0.5151925 0.29076447 -13.1848075 -1.5592355 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4460 -36600 9100
#> initial value 998.131940
#> iter 2 value 827.501127
#> iter 3 value 812.595862
#> iter 4 value 812.227236
#> iter 5 value 778.511522
#> iter 6 value 771.756648
#> iter 7 value 770.899210
#> iter 8 value 770.877080
#> iter 9 value 770.876887
#> iter 10 value 770.876843
#> iter 11 value 770.876779
#> iter 12 value 770.876737
#> iter 12 value 770.876737
#> iter 12 value 770.876737
#> final value 770.876737
#> converged
#> This is Run number 340
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.1663542 0.01835339 -3.1336458 -1.681647 2
#> 2 1 -1.35 -13.20 -0.5938355 -0.18618551 -1.9438355 -13.386186 1
#> 3 1 -2.05 -14.20 0.9288409 -0.77076825 -1.1211591 -14.970768 1
#> 4 1 -1.55 -3.10 1.1866974 -0.04183662 -0.3633026 -3.141837 1
#> 5 1 -1.90 -3.60 -0.9907265 1.70316291 -2.8907265 -1.896837 2
#> 6 1 -13.70 -1.85 1.1667100 -1.60503826 -12.5332900 -3.455038 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3280 -36950 10125
#> initial value 998.131940
#> iter 2 value 814.342493
#> iter 3 value 793.982598
#> iter 4 value 791.795441
#> iter 5 value 757.532408
#> iter 6 value 751.282625
#> iter 7 value 750.548023
#> iter 8 value 750.523071
#> iter 9 value 750.522980
#> iter 10 value 750.522959
#> iter 11 value 750.522945
#> iter 11 value 750.522944
#> iter 11 value 750.522944
#> final value 750.522944
#> converged
#> This is Run number 341
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.6953858 0.4685101 -2.6046142 -1.2314899 2
#> 2 1 -1.35 -13.20 -0.2669274 1.7798456 -1.6169274 -11.4201544 1
#> 3 1 -2.05 -14.20 0.2163923 0.5987387 -1.8336077 -13.6012613 1
#> 4 1 -1.55 -3.10 0.6069868 -0.5471840 -0.9430132 -3.6471840 1
#> 5 1 -1.90 -3.60 -0.5306166 3.3897575 -2.4306166 -0.2102425 2
#> 6 1 -13.70 -1.85 0.8958436 3.9420738 -12.8041564 2.0920738 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3940 -36725 10650
#> initial value 998.131940
#> iter 2 value 813.961625
#> iter 3 value 793.455758
#> iter 4 value 793.230446
#> iter 5 value 760.920927
#> iter 6 value 754.909665
#> iter 7 value 754.363846
#> iter 8 value 754.346533
#> iter 9 value 754.346458
#> iter 10 value 754.346245
#> iter 10 value 754.346234
#> iter 11 value 754.346220
#> iter 12 value 754.346208
#> iter 12 value 754.346208
#> iter 12 value 754.346205
#> final value 754.346205
#> converged
#> This is Run number 342
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.54750332 0.5308685 -2.7524967 -1.169132 2
#> 2 1 -1.35 -13.20 0.08234867 0.5448786 -1.2676513 -12.655121 1
#> 3 1 -2.05 -14.20 4.12163905 0.2927695 2.0716390 -13.907231 1
#> 4 1 -1.55 -3.10 0.11550514 0.9829865 -1.4344949 -2.117013 1
#> 5 1 -1.90 -3.60 2.10875985 -0.2952565 0.2087598 -3.895256 1
#> 6 1 -13.70 -1.85 1.07217575 0.4474581 -12.6278242 -1.402542 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3440 -37875 11000
#> initial value 998.131940
#> iter 2 value 794.324891
#> iter 3 value 771.243424
#> iter 4 value 769.784096
#> iter 5 value 738.326117
#> iter 6 value 732.514204
#> iter 7 value 731.902941
#> iter 8 value 731.873241
#> iter 9 value 731.873156
#> iter 10 value 731.873006
#> iter 11 value 731.872942
#> iter 12 value 731.872904
#> iter 12 value 731.872904
#> iter 12 value 731.872904
#> final value 731.872904
#> converged
#> This is Run number 343
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.03668924 0.2212259 -4.3366892 -1.478774 2
#> 2 1 -1.35 -13.20 3.66792788 1.8787405 2.3179279 -11.321260 1
#> 3 1 -2.05 -14.20 -0.22043869 0.3809090 -2.2704387 -13.819091 1
#> 4 1 -1.55 -3.10 1.89994341 1.1584679 0.3499434 -1.941532 1
#> 5 1 -1.90 -3.60 0.37892684 0.4098957 -1.5210732 -3.190104 1
#> 6 1 -13.70 -1.85 -1.50598940 -1.4402785 -15.2059894 -3.290279 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3220 -36000 10050
#> initial value 998.131940
#> iter 2 value 827.706124
#> iter 3 value 807.837883
#> iter 4 value 806.158810
#> iter 5 value 770.613209
#> iter 6 value 764.523629
#> iter 7 value 763.817562
#> iter 8 value 763.798010
#> iter 9 value 763.797900
#> iter 10 value 763.797883
#> iter 11 value 763.797861
#> iter 11 value 763.797851
#> iter 11 value 763.797851
#> final value 763.797851
#> converged
#> This is Run number 344
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.75476857 2.8432086 -3.54523143 1.143209 2
#> 2 1 -1.35 -13.20 1.67251835 -0.5833716 0.32251835 -13.783372 1
#> 3 1 -2.05 -14.20 -0.11503230 4.1166644 -2.16503230 -10.083336 1
#> 4 1 -1.55 -3.10 1.64031383 1.5297432 0.09031383 -1.570257 1
#> 5 1 -1.90 -3.60 -0.09513149 1.8913203 -1.99513149 -1.708680 2
#> 6 1 -13.70 -1.85 -0.54192664 -1.0689428 -14.24192664 -2.918943 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4240 -39400 8975
#> initial value 998.131940
#> iter 2 value 787.066039
#> iter 3 value 771.001420
#> iter 4 value 767.982870
#> iter 5 value 738.347733
#> iter 6 value 731.202139
#> iter 7 value 730.265507
#> iter 8 value 730.225924
#> iter 9 value 730.225880
#> iter 9 value 730.225873
#> iter 9 value 730.225873
#> final value 730.225873
#> converged
#> This is Run number 345
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.3140426 -0.4480016 -2.98595744 -2.1480016 2
#> 2 1 -1.35 -13.20 1.4094092 -1.1978881 0.05940921 -14.3978881 1
#> 3 1 -2.05 -14.20 1.9096464 -0.2908291 -0.14035357 -14.4908291 1
#> 4 1 -1.55 -3.10 0.3239186 1.2153818 -1.22608136 -1.8846182 1
#> 5 1 -1.90 -3.60 1.6217679 0.6089728 -0.27823205 -2.9910272 1
#> 6 1 -13.70 -1.85 2.5385967 1.0210095 -11.16140333 -0.8289905 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3560 -35500 9125
#> initial value 998.131940
#> iter 2 value 841.237917
#> iter 3 value 824.928192
#> iter 4 value 823.508643
#> iter 5 value 786.698140
#> iter 6 value 780.324110
#> iter 7 value 779.442595
#> iter 8 value 779.422123
#> iter 9 value 779.421981
#> iter 10 value 779.421962
#> iter 11 value 779.421943
#> iter 12 value 779.421929
#> iter 12 value 779.421929
#> iter 12 value 779.421929
#> final value 779.421929
#> converged
#> This is Run number 346
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.06064871 -0.71990144 -4.360649 -2.419901 2
#> 2 1 -1.35 -13.20 0.27108156 -1.12219395 -1.078918 -14.322194 1
#> 3 1 -2.05 -14.20 -0.79181935 0.09822697 -2.841819 -14.101773 1
#> 4 1 -1.55 -3.10 -0.65473022 0.01357987 -2.204730 -3.086420 1
#> 5 1 -1.90 -3.60 -1.02309228 0.48534518 -2.923092 -3.114655 1
#> 6 1 -13.70 -1.85 3.50227093 -0.96577421 -10.197729 -2.815774 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4180 -37075 8675
#> initial value 998.131940
#> iter 2 value 823.681439
#> iter 3 value 809.198182
#> iter 4 value 807.681771
#> iter 5 value 773.737317
#> iter 6 value 766.722231
#> iter 7 value 765.684796
#> iter 8 value 765.655368
#> iter 9 value 765.655139
#> iter 10 value 765.655118
#> iter 11 value 765.655103
#> iter 12 value 765.655086
#> iter 12 value 765.655086
#> iter 12 value 765.655086
#> final value 765.655086
#> converged
#> This is Run number 347
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.1255783 -0.7338957 -3.17442174 -2.433896 2
#> 2 1 -1.35 -13.20 1.2795456 0.3925273 -0.07045444 -12.807473 1
#> 3 1 -2.05 -14.20 1.4266299 1.1320494 -0.62337013 -13.067951 1
#> 4 1 -1.55 -3.10 0.4196747 0.1339625 -1.13032530 -2.966038 1
#> 5 1 -1.90 -3.60 1.4311714 2.0266955 -0.46882861 -1.573305 1
#> 6 1 -13.70 -1.85 0.6327044 0.3204306 -13.06729563 -1.529569 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4040 -36075 9450
#> initial value 998.131940
#> iter 2 value 831.901337
#> iter 3 value 815.452233
#> iter 4 value 814.886847
#> iter 5 value 780.254149
#> iter 6 value 773.807245
#> iter 7 value 773.029841
#> iter 8 value 773.010722
#> iter 9 value 773.010565
#> iter 9 value 773.010559
#> iter 9 value 773.010559
#> final value 773.010559
#> converged
#> This is Run number 348
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.7100992 -0.1871615 -5.0100992 -1.8871615 2
#> 2 1 -1.35 -13.20 0.5376408 -0.2130706 -0.8123592 -13.4130706 1
#> 3 1 -2.05 -14.20 0.3423017 0.3226642 -1.7076983 -13.8773358 1
#> 4 1 -1.55 -3.10 0.6209673 1.8602052 -0.9290327 -1.2397948 1
#> 5 1 -1.90 -3.60 -0.2079358 -0.8410453 -2.1079358 -4.4410453 1
#> 6 1 -13.70 -1.85 0.7721511 1.1604769 -12.9278489 -0.6895231 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3700 -34975 9425
#> initial value 998.131940
#> iter 2 value 845.879722
#> iter 3 value 829.229779
#> iter 4 value 828.575676
#> iter 5 value 792.010817
#> iter 6 value 785.922538
#> iter 7 value 785.168966
#> iter 8 value 785.153241
#> iter 9 value 785.153124
#> iter 10 value 785.153094
#> iter 11 value 785.153050
#> iter 12 value 785.153026
#> iter 12 value 785.153026
#> iter 12 value 785.153026
#> final value 785.153026
#> converged
#> This is Run number 349
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.40722462 -0.21095561 -4.7072246 -1.910956 2
#> 2 1 -1.35 -13.20 2.92748699 -0.70948041 1.5774870 -13.909480 1
#> 3 1 -2.05 -14.20 0.01603193 3.04838614 -2.0339681 -11.151614 1
#> 4 1 -1.55 -3.10 2.43999428 0.21648611 0.8899943 -2.883514 1
#> 5 1 -1.90 -3.60 0.05610581 -1.04021886 -1.8438942 -4.640219 1
#> 6 1 -13.70 -1.85 -0.67812921 -0.09976269 -14.3781292 -1.949763 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3960 -37775 8900
#> initial value 998.131940
#> iter 2 value 812.068480
#> iter 3 value 796.262679
#> iter 4 value 793.857270
#> iter 5 value 760.736299
#> iter 6 value 753.663237
#> iter 7 value 752.675854
#> iter 8 value 752.644896
#> iter 9 value 752.644741
#> iter 9 value 752.644734
#> iter 9 value 752.644730
#> final value 752.644730
#> converged
#> This is Run number 350
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.73820990 -0.9516274 -5.0382099 -2.651627 2
#> 2 1 -1.35 -13.20 1.45145574 0.3598152 0.1014557 -12.840185 1
#> 3 1 -2.05 -14.20 0.69209260 -0.6827985 -1.3579074 -14.882798 1
#> 4 1 -1.55 -3.10 0.07564411 1.3749116 -1.4743559 -1.725088 1
#> 5 1 -1.90 -3.60 -1.98760216 1.8816752 -3.8876022 -1.718325 2
#> 6 1 -13.70 -1.85 0.04018538 -0.8240224 -13.6598146 -2.674022 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4760 -38350 8225
#> initial value 998.131940
#> iter 2 value 808.286261
#> iter 3 value 795.535536
#> iter 4 value 794.054683
#> iter 5 value 762.973482
#> iter 6 value 755.518213
#> iter 7 value 754.385344
#> iter 8 value 754.348111
#> iter 9 value 754.347801
#> iter 10 value 754.347779
#> iter 10 value 754.347768
#> iter 11 value 754.347757
#> iter 11 value 754.347755
#> iter 11 value 754.347753
#> final value 754.347753
#> converged
#> This is Run number 351
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.6930877 -0.7608615 -4.9930877 -2.460861 2
#> 2 1 -1.35 -13.20 0.2742211 -1.0438702 -1.0757789 -14.243870 1
#> 3 1 -2.05 -14.20 3.4087434 -0.3393930 1.3587434 -14.539393 1
#> 4 1 -1.55 -3.10 -0.4223636 0.6850653 -1.9723636 -2.414935 1
#> 5 1 -1.90 -3.60 1.5560873 -0.8855745 -0.3439127 -4.485574 1
#> 6 1 -13.70 -1.85 0.1528302 -1.0399180 -13.5471698 -2.889918 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2700 -36450 10875
#> initial value 998.131940
#> iter 2 value 814.391603
#> iter 3 value 790.469846
#> iter 4 value 787.929117
#> iter 5 value 752.647986
#> iter 6 value 746.990586
#> iter 7 value 746.358879
#> iter 8 value 746.334865
#> iter 9 value 746.334816
#> iter 10 value 746.334790
#> iter 10 value 746.334789
#> iter 10 value 746.334782
#> final value 746.334782
#> converged
#> This is Run number 352
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.33214117 -1.43967902 -2.96785883 -3.139679 1
#> 2 1 -1.35 -13.20 1.86515780 2.18649786 0.51515780 -11.013502 1
#> 3 1 -2.05 -14.20 1.45986677 0.52183277 -0.59013323 -13.678167 1
#> 4 1 -1.55 -3.10 1.59763121 4.48321938 0.04763121 1.383219 2
#> 5 1 -1.90 -3.60 -0.01809294 1.11437489 -1.91809294 -2.485625 1
#> 6 1 -13.70 -1.85 0.31121408 -0.05655177 -13.38878592 -1.906552 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3600 -36600 9225
#> initial value 998.131940
#> iter 2 value 826.078606
#> iter 3 value 809.132644
#> iter 4 value 807.111705
#> iter 5 value 771.860417
#> iter 6 value 765.199796
#> iter 7 value 764.295869
#> iter 8 value 764.271167
#> iter 9 value 764.271016
#> iter 10 value 764.271005
#> iter 10 value 764.270998
#> iter 10 value 764.270994
#> final value 764.270994
#> converged
#> This is Run number 353
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.0760295 2.0687626 -3.2239705 0.3687626 2
#> 2 1 -1.35 -13.20 0.7028666 0.7441343 -0.6471334 -12.4558657 1
#> 3 1 -2.05 -14.20 -1.0235181 0.5151653 -3.0735181 -13.6848347 1
#> 4 1 -1.55 -3.10 -0.2489742 1.1668830 -1.7989742 -1.9331170 1
#> 5 1 -1.90 -3.60 -0.7217853 1.3603971 -2.6217853 -2.2396029 2
#> 6 1 -13.70 -1.85 -0.3610135 1.9852452 -14.0610135 0.1352452 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3700 -36500 9350
#> initial value 998.131940
#> iter 2 value 826.666948
#> iter 3 value 809.657294
#> iter 4 value 808.079585
#> iter 5 value 773.181516
#> iter 6 value 766.602631
#> iter 7 value 765.744679
#> iter 8 value 765.721312
#> iter 9 value 765.721147
#> iter 10 value 765.721129
#> iter 11 value 765.721111
#> iter 12 value 765.721096
#> iter 12 value 765.721096
#> iter 12 value 765.721096
#> final value 765.721096
#> converged
#> This is Run number 354
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.8280468 0.6575452 -5.128047 -1.0424548 2
#> 2 1 -1.35 -13.20 -1.0972241 -0.6875107 -2.447224 -13.8875107 1
#> 3 1 -2.05 -14.20 0.3782986 -0.1676377 -1.671701 -14.3676377 1
#> 4 1 -1.55 -3.10 -0.5584446 0.4775008 -2.108445 -2.6224992 1
#> 5 1 -1.90 -3.60 0.4417644 2.8458602 -1.458236 -0.7541398 2
#> 6 1 -13.70 -1.85 2.2735837 0.4203717 -11.426416 -1.4296283 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3760 -37500 9800
#> initial value 998.131940
#> iter 2 value 809.542778
#> iter 3 value 791.016427
#> iter 4 value 789.331087
#> iter 5 value 756.566673
#> iter 6 value 750.005250
#> iter 7 value 749.231870
#> iter 8 value 749.205188
#> iter 9 value 749.205054
#> iter 10 value 749.205022
#> iter 11 value 749.204994
#> iter 11 value 749.204993
#> iter 11 value 749.204993
#> final value 749.204993
#> converged
#> This is Run number 355
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.28494870 3.0396031 -4.5849487 1.339603 2
#> 2 1 -1.35 -13.20 0.11002782 0.6487232 -1.2399722 -12.551277 1
#> 3 1 -2.05 -14.20 0.06833971 -2.2109330 -1.9816603 -16.410933 1
#> 4 1 -1.55 -3.10 0.37976635 0.2125522 -1.1702337 -2.887448 1
#> 5 1 -1.90 -3.60 0.99738179 -0.4946616 -0.9026182 -4.094662 1
#> 6 1 -13.70 -1.85 4.96083599 0.1841759 -8.7391640 -1.665824 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3120 -36900 9875
#> initial value 998.131940
#> iter 2 value 816.694184
#> iter 3 value 796.662728
#> iter 4 value 793.793377
#> iter 5 value 758.449533
#> iter 6 value 752.078011
#> iter 7 value 751.274428
#> iter 8 value 751.248419
#> iter 9 value 751.248353
#> iter 9 value 751.248350
#> iter 9 value 751.248350
#> final value 751.248350
#> converged
#> This is Run number 356
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.493859562 0.58085255 -3.806140 -1.1191475 2
#> 2 1 -1.35 -13.20 0.006197033 -0.05073614 -1.343803 -13.2507361 1
#> 3 1 -2.05 -14.20 0.908180818 2.59398349 -1.141819 -11.6060165 1
#> 4 1 -1.55 -3.10 -0.198641754 -0.42669242 -1.748642 -3.5266924 1
#> 5 1 -1.90 -3.60 0.315001927 1.66841410 -1.584998 -1.9315859 1
#> 6 1 -13.70 -1.85 1.043643126 2.17775456 -12.656357 0.3277546 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3880 -36350 8775
#> initial value 998.131940
#> iter 2 value 832.747751
#> iter 3 value 817.677662
#> iter 4 value 816.070799
#> iter 5 value 780.517001
#> iter 6 value 773.738819
#> iter 7 value 772.732155
#> iter 8 value 772.706156
#> iter 9 value 772.705970
#> iter 10 value 772.705951
#> iter 11 value 772.705938
#> iter 12 value 772.705926
#> iter 12 value 772.705926
#> iter 12 value 772.705926
#> final value 772.705926
#> converged
#> This is Run number 357
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.6677742 1.9866488 -4.967774 0.2866488 2
#> 2 1 -1.35 -13.20 0.0472669 0.6881176 -1.302733 -12.5118824 1
#> 3 1 -2.05 -14.20 3.2915369 1.2226625 1.241537 -12.9773375 1
#> 4 1 -1.55 -3.10 0.1534111 -0.7941660 -1.396589 -3.8941660 1
#> 5 1 -1.90 -3.60 -0.5487727 0.7617277 -2.448773 -2.8382723 1
#> 6 1 -13.70 -1.85 -0.2122041 0.1749201 -13.912204 -1.6750799 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3360 -36875 10050
#> initial value 998.131940
#> iter 2 value 816.055558
#> iter 3 value 796.143070
#> iter 4 value 794.152971
#> iter 5 value 759.921742
#> iter 6 value 753.634602
#> iter 7 value 752.897004
#> iter 8 value 752.872865
#> iter 9 value 752.872760
#> iter 10 value 752.872738
#> iter 11 value 752.872719
#> iter 11 value 752.872718
#> iter 11 value 752.872718
#> final value 752.872718
#> converged
#> This is Run number 358
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.5824587 -0.3865554 -1.71754131 -2.086555 1
#> 2 1 -1.35 -13.20 1.3350190 -0.7825154 -0.01498102 -13.982515 1
#> 3 1 -2.05 -14.20 0.9407773 1.4464402 -1.10922267 -12.753560 1
#> 4 1 -1.55 -3.10 -0.1773595 0.2101963 -1.72735949 -2.889804 1
#> 5 1 -1.90 -3.60 -0.6042140 1.0500175 -2.50421399 -2.549982 1
#> 6 1 -13.70 -1.85 0.7509201 0.4394742 -12.94907991 -1.410526 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4700 -38825 8225
#> initial value 998.131940
#> iter 2 value 801.071750
#> iter 3 value 788.019962
#> iter 4 value 785.995374
#> iter 5 value 755.697858
#> iter 6 value 748.171279
#> iter 7 value 747.062309
#> iter 8 value 747.024233
#> iter 9 value 747.023984
#> iter 10 value 747.023972
#> iter 10 value 747.023970
#> iter 10 value 747.023962
#> final value 747.023962
#> converged
#> This is Run number 359
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 4.1601716 -0.2821955 -0.1398284 -1.9821955 1
#> 2 1 -1.35 -13.20 -0.5195638 -0.4630761 -1.8695638 -13.6630761 1
#> 3 1 -2.05 -14.20 1.8179858 -1.2466309 -0.2320142 -15.4466309 1
#> 4 1 -1.55 -3.10 1.4483258 -0.6609147 -0.1016742 -3.7609147 1
#> 5 1 -1.90 -3.60 2.2181504 -0.4226800 0.3181504 -4.0226800 1
#> 6 1 -13.70 -1.85 5.0189641 1.6777873 -8.6810359 -0.1722127 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4140 -37650 9175
#> initial value 998.131940
#> iter 2 value 812.140884
#> iter 3 value 796.084607
#> iter 4 value 794.584391
#> iter 5 value 762.095534
#> iter 6 value 755.166823
#> iter 7 value 754.271966
#> iter 8 value 754.243431
#> iter 9 value 754.243227
#> iter 9 value 754.243221
#> iter 9 value 754.243221
#> final value 754.243221
#> converged
#> This is Run number 360
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.89686045 -0.3328263 -3.403140 -2.032826 2
#> 2 1 -1.35 -13.20 0.07698910 1.4091544 -1.273011 -11.790846 1
#> 3 1 -2.05 -14.20 0.33702950 -0.6372516 -1.712970 -14.837252 1
#> 4 1 -1.55 -3.10 -0.04307282 -0.7349836 -1.593073 -3.834984 1
#> 5 1 -1.90 -3.60 -0.55302215 0.7162066 -2.453022 -2.883793 1
#> 6 1 -13.70 -1.85 1.00097325 0.8374605 -12.699027 -1.012540 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3620 -36950 9800
#> initial value 998.131940
#> iter 2 value 817.174385
#> iter 3 value 798.556632
#> iter 4 value 796.918595
#> iter 5 value 763.084927
#> iter 6 value 756.626670
#> iter 7 value 755.858081
#> iter 8 value 755.834081
#> iter 9 value 755.833943
#> iter 10 value 755.833920
#> iter 11 value 755.833895
#> iter 11 value 755.833886
#> iter 11 value 755.833886
#> final value 755.833886
#> converged
#> This is Run number 361
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.2031276 3.1028091 -4.5031276 1.4028091 2
#> 2 1 -1.35 -13.20 0.5280561 3.0817623 -0.8219439 -10.1182377 1
#> 3 1 -2.05 -14.20 0.5588406 -0.5705703 -1.4911594 -14.7705703 1
#> 4 1 -1.55 -3.10 1.2690753 -0.3073787 -0.2809247 -3.4073787 1
#> 5 1 -1.90 -3.60 0.2602291 0.6707287 -1.6397709 -2.9292713 1
#> 6 1 -13.70 -1.85 -0.5139477 1.0406379 -14.2139477 -0.8093621 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3540 -36200 10525
#> initial value 998.131940
#> iter 2 value 821.737644
#> iter 3 value 801.035959
#> iter 4 value 800.339918
#> iter 5 value 766.546656
#> iter 6 value 760.619105
#> iter 7 value 760.034665
#> iter 8 value 760.017425
#> iter 9 value 760.017333
#> iter 10 value 760.017237
#> iter 11 value 760.017195
#> iter 11 value 760.017185
#> iter 11 value 760.017185
#> final value 760.017185
#> converged
#> This is Run number 362
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.90373433 -0.1696859 -5.2037343 -1.8696859 2
#> 2 1 -1.35 -13.20 -0.74185923 3.1553496 -2.0918592 -10.0446504 1
#> 3 1 -2.05 -14.20 2.15388611 1.0908395 0.1038861 -13.1091605 1
#> 4 1 -1.55 -3.10 0.47932879 -0.7952811 -1.0706712 -3.8952811 1
#> 5 1 -1.90 -3.60 0.05351123 0.8851316 -1.8464888 -2.7148684 1
#> 6 1 -13.70 -1.85 2.03494700 1.5350796 -11.6650530 -0.3149204 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4140 -38100 9275
#> initial value 998.131940
#> iter 2 value 804.868556
#> iter 3 value 788.373391
#> iter 4 value 786.646117
#> iter 5 value 754.992284
#> iter 6 value 748.047901
#> iter 7 value 747.175306
#> iter 8 value 747.144850
#> iter 9 value 747.144675
#> iter 10 value 747.144660
#> iter 11 value 747.144640
#> iter 12 value 747.144627
#> iter 12 value 747.144627
#> iter 12 value 747.144627
#> final value 747.144627
#> converged
#> This is Run number 363
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.61014063 0.3370451 -4.9101406 -1.3629549 2
#> 2 1 -1.35 -13.20 0.07737053 0.5315491 -1.2726295 -12.6684509 1
#> 3 1 -2.05 -14.20 -1.57403005 1.6342724 -3.6240301 -12.5657276 1
#> 4 1 -1.55 -3.10 0.61165755 0.5464110 -0.9383424 -2.5535890 1
#> 5 1 -1.90 -3.60 0.44375319 4.4184784 -1.4562468 0.8184784 2
#> 6 1 -13.70 -1.85 0.22162846 0.1776341 -13.4783715 -1.6723659 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3260 -37200 9725
#> initial value 998.131940
#> iter 2 value 813.792944
#> iter 3 value 794.395015
#> iter 4 value 791.470955
#> iter 5 value 756.673511
#> iter 6 value 750.157349
#> iter 7 value 749.321969
#> iter 8 value 749.294342
#> iter 9 value 749.294274
#> iter 9 value 749.294272
#> iter 9 value 749.294272
#> final value 749.294272
#> converged
#> This is Run number 364
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.6843081 0.5077307 -3.615692 -1.1922693 2
#> 2 1 -1.35 -13.20 -1.6501342 0.8439884 -3.000134 -12.3560116 1
#> 3 1 -2.05 -14.20 0.7571827 2.4868032 -1.292817 -11.7131968 1
#> 4 1 -1.55 -3.10 -0.5656979 -1.2520622 -2.115698 -4.3520622 1
#> 5 1 -1.90 -3.60 -0.1483672 -0.8118115 -2.048367 -4.4118115 1
#> 6 1 -13.70 -1.85 3.3537251 1.0349922 -10.346275 -0.8150078 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3640 -36625 8975
#> initial value 998.131940
#> iter 2 value 827.480243
#> iter 3 value 811.256521
#> iter 4 value 809.067082
#> iter 5 value 773.527298
#> iter 6 value 766.743736
#> iter 7 value 765.773822
#> iter 8 value 765.747926
#> iter 9 value 765.747775
#> iter 9 value 765.747765
#> iter 9 value 765.747761
#> final value 765.747761
#> converged
#> This is Run number 365
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.2494459 -0.5736082 -4.5494459 -2.273608 2
#> 2 1 -1.35 -13.20 0.7447043 -0.9745849 -0.6052957 -14.174585 1
#> 3 1 -2.05 -14.20 -1.6618170 1.2437139 -3.7118170 -12.956286 1
#> 4 1 -1.55 -3.10 1.3023987 -0.4296654 -0.2476013 -3.529665 1
#> 5 1 -1.90 -3.60 0.7092174 -1.0427777 -1.1907826 -4.642778 1
#> 6 1 -13.70 -1.85 0.8880767 0.2708953 -12.8119233 -1.579105 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4160 -37800 9500
#> initial value 998.131940
#> iter 2 value 807.690230
#> iter 3 value 790.744440
#> iter 4 value 789.537734
#> iter 5 value 757.710193
#> iter 6 value 750.911039
#> iter 7 value 750.104363
#> iter 8 value 750.076965
#> iter 9 value 750.076784
#> iter 10 value 750.076746
#> iter 11 value 750.076705
#> iter 12 value 750.076693
#> iter 12 value 750.076693
#> iter 12 value 750.076693
#> final value 750.076693
#> converged
#> This is Run number 366
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.1056079 -0.1753520 -4.4056079 -1.875352 2
#> 2 1 -1.35 -13.20 0.8404577 -0.8275544 -0.5095423 -14.027554 1
#> 3 1 -2.05 -14.20 -0.2473771 -0.9430835 -2.2973771 -15.143083 1
#> 4 1 -1.55 -3.10 -1.1687730 0.7042485 -2.7187730 -2.395751 2
#> 5 1 -1.90 -3.60 0.4362037 0.4354568 -1.4637963 -3.164543 1
#> 6 1 -13.70 -1.85 3.5942901 0.3207793 -10.1057099 -1.529221 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2680 -36350 10900
#> initial value 998.131940
#> iter 2 value 815.503788
#> iter 3 value 791.496446
#> iter 4 value 789.015895
#> iter 5 value 753.642173
#> iter 6 value 748.018294
#> iter 7 value 747.395189
#> iter 8 value 747.371860
#> iter 9 value 747.371810
#> iter 10 value 747.371782
#> iter 10 value 747.371782
#> iter 10 value 747.371774
#> final value 747.371774
#> converged
#> This is Run number 367
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.03796936 0.6704990 -4.337969 -1.02950097 2
#> 2 1 -1.35 -13.20 2.39736383 -0.7323296 1.047364 -13.93232964 1
#> 3 1 -2.05 -14.20 -0.04102684 1.7773218 -2.091027 -12.42267818 1
#> 4 1 -1.55 -3.10 -0.69248884 0.1314504 -2.242489 -2.96854961 1
#> 5 1 -1.90 -3.60 4.14155127 1.1544969 2.241551 -2.44550312 1
#> 6 1 -13.70 -1.85 2.27647874 1.8306359 -11.423521 -0.01936411 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3880 -37475 8750
#> initial value 998.131940
#> iter 2 value 817.319348
#> iter 3 value 801.826036
#> iter 4 value 799.300472
#> iter 5 value 765.258938
#> iter 6 value 758.169600
#> iter 7 value 757.137636
#> iter 8 value 757.107386
#> iter 9 value 757.107237
#> iter 9 value 757.107230
#> iter 9 value 757.107227
#> final value 757.107227
#> converged
#> This is Run number 368
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.9243019 -0.7621694 -2.3756981 -2.4621694 1
#> 2 1 -1.35 -13.20 -0.4502375 1.0356326 -1.8002375 -12.1643674 1
#> 3 1 -2.05 -14.20 1.4016576 2.5256878 -0.6483424 -11.6743122 1
#> 4 1 -1.55 -3.10 -0.8048955 -0.3032226 -2.3548955 -3.4032226 1
#> 5 1 -1.90 -3.60 1.6253287 3.0406371 -0.2746713 -0.5593629 1
#> 6 1 -13.70 -1.85 0.8783684 0.8536065 -12.8216316 -0.9963935 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2880 -35775 11450
#> initial value 998.131940
#> iter 2 value 818.811250
#> iter 3 value 793.710632
#> iter 4 value 792.691968
#> iter 5 value 758.601054
#> iter 6 value 753.378289
#> iter 7 value 752.896298
#> iter 8 value 752.879454
#> iter 9 value 752.879399
#> iter 10 value 752.879256
#> iter 10 value 752.879253
#> iter 10 value 752.879247
#> final value 752.879247
#> converged
#> This is Run number 369
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.08373031 -1.1541795 -2.216270 -2.8541795 1
#> 2 1 -1.35 -13.20 0.11574547 1.1829660 -1.234255 -12.0170340 1
#> 3 1 -2.05 -14.20 -0.02127318 -0.1507864 -2.071273 -14.3507864 1
#> 4 1 -1.55 -3.10 -0.11296428 1.7159450 -1.662964 -1.3840550 2
#> 5 1 -1.90 -3.60 -0.13695026 0.4768277 -2.036950 -3.1231723 1
#> 6 1 -13.70 -1.85 -0.17993297 1.1070545 -13.879933 -0.7429455 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4040 -37425 9275
#> initial value 998.131940
#> iter 2 value 814.610493
#> iter 3 value 798.166833
#> iter 4 value 796.684233
#> iter 5 value 763.758524
#> iter 6 value 756.922300
#> iter 7 value 756.048759
#> iter 8 value 756.021555
#> iter 9 value 756.021361
#> iter 9 value 756.021354
#> iter 9 value 756.021354
#> final value 756.021354
#> converged
#> This is Run number 370
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.04481537 2.4918578 -3.255185 0.7918578 2
#> 2 1 -1.35 -13.20 -0.54170388 1.7771498 -1.891704 -11.4228502 1
#> 3 1 -2.05 -14.20 0.27861201 -0.4555028 -1.771388 -14.6555028 1
#> 4 1 -1.55 -3.10 -0.27475207 1.6833795 -1.824752 -1.4166205 2
#> 5 1 -1.90 -3.60 -1.28072852 1.8350465 -3.180729 -1.7649535 2
#> 6 1 -13.70 -1.85 0.03398748 0.2176585 -13.666013 -1.6323415 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3500 -37725 9950
#> initial value 998.131940
#> iter 2 value 804.910206
#> iter 3 value 785.248664
#> iter 4 value 782.809265
#> iter 5 value 749.841156
#> iter 6 value 743.367933
#> iter 7 value 742.586916
#> iter 8 value 742.557213
#> iter 9 value 742.557133
#> iter 10 value 742.557113
#> iter 10 value 742.557112
#> iter 10 value 742.557112
#> final value 742.557112
#> converged
#> This is Run number 371
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -1.4987915 -0.3359387 -5.7987915 -2.0359387 2
#> 2 1 -1.35 -13.20 1.0638898 0.2239183 -0.2861102 -12.9760817 1
#> 3 1 -2.05 -14.20 1.0143130 1.5891818 -1.0356870 -12.6108182 1
#> 4 1 -1.55 -3.10 0.4011225 2.1039672 -1.1488775 -0.9960328 2
#> 5 1 -1.90 -3.60 2.0218186 -0.1117602 0.1218186 -3.7117602 1
#> 6 1 -13.70 -1.85 2.6862415 -0.8145232 -11.0137585 -2.6645232 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3900 -38925 9975
#> initial value 998.131940
#> iter 2 value 787.112881
#> iter 3 value 767.819448
#> iter 4 value 765.564823
#> iter 5 value 735.413662
#> iter 6 value 728.875916
#> iter 7 value 728.105420
#> iter 8 value 728.068442
#> iter 9 value 728.068371
#> iter 10 value 728.068307
#> iter 11 value 728.068269
#> iter 11 value 728.068261
#> iter 11 value 728.068261
#> final value 728.068261
#> converged
#> This is Run number 372
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.32213802 -1.375197472 -1.9778620 -3.075197 1
#> 2 1 -1.35 -13.20 3.28348744 1.467772530 1.9334874 -11.732227 1
#> 3 1 -2.05 -14.20 -0.08771016 -0.387591558 -2.1377102 -14.587592 1
#> 4 1 -1.55 -3.10 -0.58452625 0.002577193 -2.1345263 -3.097423 1
#> 5 1 -1.90 -3.60 1.91943020 1.422708124 0.0194302 -2.177292 1
#> 6 1 -13.70 -1.85 2.98471963 0.095495400 -10.7152804 -1.754505 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3540 -37025 10100
#> initial value 998.131940
#> iter 2 value 813.795484
#> iter 3 value 794.094807
#> iter 4 value 792.518063
#> iter 5 value 759.028350
#> iter 6 value 752.724074
#> iter 7 value 752.011353
#> iter 8 value 751.987490
#> iter 9 value 751.987373
#> iter 10 value 751.987330
#> iter 11 value 751.987301
#> iter 11 value 751.987300
#> iter 11 value 751.987300
#> final value 751.987300
#> converged
#> This is Run number 373
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.1042026 -0.20871038 -3.1957974 -1.908710 2
#> 2 1 -1.35 -13.20 -0.6032502 0.62559660 -1.9532502 -12.574403 1
#> 3 1 -2.05 -14.20 -1.0237174 0.52768387 -3.0737174 -13.672316 1
#> 4 1 -1.55 -3.10 1.7460462 0.07023661 0.1960462 -3.029763 1
#> 5 1 -1.90 -3.60 -1.4674316 -0.20367820 -3.3674316 -3.803678 1
#> 6 1 -13.70 -1.85 1.4777285 -0.75131150 -12.2222715 -2.601312 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3140 -36050 10150
#> initial value 998.131940
#> iter 2 value 826.179032
#> iter 3 value 805.802280
#> iter 4 value 803.991366
#> iter 5 value 768.443717
#> iter 6 value 762.400110
#> iter 7 value 761.704727
#> iter 8 value 761.684833
#> iter 9 value 761.684732
#> iter 10 value 761.684713
#> iter 11 value 761.684694
#> iter 11 value 761.684688
#> iter 11 value 761.684688
#> final value 761.684688
#> converged
#> This is Run number 374
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.3581952 -1.4652686 -4.6581952 -3.1652686 2
#> 2 1 -1.35 -13.20 1.0311563 -0.9225877 -0.3188437 -14.1225877 1
#> 3 1 -2.05 -14.20 -0.8268722 -1.6065640 -2.8768722 -15.8065640 1
#> 4 1 -1.55 -3.10 0.2365710 -0.8443230 -1.3134290 -3.9443230 1
#> 5 1 -1.90 -3.60 3.3925580 -0.5287893 1.4925580 -4.1287893 1
#> 6 1 -13.70 -1.85 1.7544209 1.9822507 -11.9455791 0.1322507 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3600 -35200 8575
#> initial value 998.131940
#> iter 2 value 848.700234
#> iter 3 value 833.992089
#> iter 4 value 832.412097
#> iter 5 value 794.368737
#> iter 6 value 787.891946
#> iter 7 value 786.872791
#> iter 8 value 786.850082
#> iter 9 value 786.849944
#> iter 10 value 786.849931
#> iter 11 value 786.849919
#> iter 11 value 786.849910
#> iter 11 value 786.849910
#> final value 786.849910
#> converged
#> This is Run number 375
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.5304202 0.744170136 -4.83042021 -0.9558299 2
#> 2 1 -1.35 -13.20 -1.0024513 -0.519214662 -2.35245129 -13.7192147 1
#> 3 1 -2.05 -14.20 0.2743289 0.007433027 -1.77567111 -14.1925670 1
#> 4 1 -1.55 -3.10 1.6350345 -0.801914564 0.08503447 -3.9019146 1
#> 5 1 -1.90 -3.60 -0.5699108 -0.920232679 -2.46991077 -4.5202327 1
#> 6 1 -13.70 -1.85 1.9735085 0.398151328 -11.72649147 -1.4518487 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2820 -37250 11125
#> initial value 998.131940
#> iter 2 value 801.418396
#> iter 3 value 776.631567
#> iter 4 value 774.011448
#> iter 5 value 740.263801
#> iter 6 value 734.664972
#> iter 7 value 734.034642
#> iter 8 value 734.004679
#> iter 9 value 734.004632
#> iter 10 value 734.004582
#> iter 11 value 734.004549
#> iter 11 value 734.004544
#> iter 11 value 734.004544
#> final value 734.004544
#> converged
#> This is Run number 376
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 2.03200797 1.0036634 -2.26799203 -0.6963366 2
#> 2 1 -1.35 -13.20 -0.50531906 0.2684152 -1.85531906 -12.9315848 1
#> 3 1 -2.05 -14.20 1.40942010 1.1764181 -0.64057990 -13.0235819 1
#> 4 1 -1.55 -3.10 1.49715128 3.3145822 -0.05284872 0.2145822 2
#> 5 1 -1.90 -3.60 -1.93106877 0.1627425 -3.83106877 -3.4372575 2
#> 6 1 -13.70 -1.85 -0.01197599 0.3700398 -13.71197599 -1.4799602 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3820 -36475 8325
#> initial value 998.131940
#> iter 2 value 833.878563
#> iter 3 value 819.691655
#> iter 4 value 817.455887
#> iter 5 value 781.108278
#> iter 6 value 774.097657
#> iter 7 value 772.951619
#> iter 8 value 772.922681
#> iter 9 value 772.922522
#> iter 9 value 772.922514
#> iter 9 value 772.922512
#> final value 772.922512
#> converged
#> This is Run number 377
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.29527575 1.5128487 -4.595276 -0.1871513 2
#> 2 1 -1.35 -13.20 -0.05983271 -0.7698310 -1.409833 -13.9698310 1
#> 3 1 -2.05 -14.20 0.61473660 -0.3654838 -1.435263 -14.5654838 1
#> 4 1 -1.55 -3.10 2.00338402 -0.5111758 0.453384 -3.6111758 1
#> 5 1 -1.90 -3.60 0.28425752 -0.2641840 -1.615742 -3.8641840 1
#> 6 1 -13.70 -1.85 -0.28085283 -0.4538075 -13.980853 -2.3038075 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2740 -36425 10275
#> initial value 998.131940
#> iter 2 value 819.571228
#> iter 3 value 797.605153
#> iter 4 value 794.561002
#> iter 5 value 758.111328
#> iter 6 value 752.086560
#> iter 7 value 751.350782
#> iter 8 value 751.326559
#> iter 9 value 751.326514
#> iter 9 value 751.326511
#> iter 9 value 751.326511
#> final value 751.326511
#> converged
#> This is Run number 378
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 4.7737172 2.463713023 0.4737172 0.763713 2
#> 2 1 -1.35 -13.20 0.1490473 -0.008102119 -1.2009527 -13.208102 1
#> 3 1 -2.05 -14.20 1.2896515 0.101042974 -0.7603485 -14.098957 1
#> 4 1 -1.55 -3.10 2.6591001 0.755670513 1.1091001 -2.344329 1
#> 5 1 -1.90 -3.60 1.3076491 -0.063106334 -0.5923509 -3.663106 1
#> 6 1 -13.70 -1.85 1.1216524 -0.629810962 -12.5783476 -2.479811 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3900 -35350 8050
#> initial value 998.131940
#> iter 2 value 850.321556
#> iter 3 value 837.412544
#> iter 4 value 835.913429
#> iter 5 value 797.904591
#> iter 6 value 791.223783
#> iter 7 value 790.036863
#> iter 8 value 790.009241
#> iter 9 value 790.009077
#> iter 10 value 790.009064
#> iter 11 value 790.009050
#> iter 11 value 790.009040
#> iter 11 value 790.009040
#> final value 790.009040
#> converged
#> This is Run number 379
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.5004269 0.4503141 -3.79957313 -1.2496859 2
#> 2 1 -1.35 -13.20 0.3806638 1.4080109 -0.96933617 -11.7919891 1
#> 3 1 -2.05 -14.20 -0.2118419 1.1752249 -2.26184189 -13.0247751 1
#> 4 1 -1.55 -3.10 1.8191562 -0.2561109 0.26915624 -3.3561109 1
#> 5 1 -1.90 -3.60 1.9523832 -1.5008345 0.05238321 -5.1008345 1
#> 6 1 -13.70 -1.85 -1.1094914 2.4283147 -14.80949142 0.5783147 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3280 -37775 9850
#> initial value 998.131940
#> iter 2 value 804.649259
#> iter 3 value 784.676332
#> iter 4 value 781.382360
#> iter 5 value 747.523934
#> iter 6 value 741.011789
#> iter 7 value 740.180145
#> iter 8 value 740.148213
#> iter 9 value 740.148176
#> iter 9 value 740.148172
#> iter 9 value 740.148172
#> final value 740.148172
#> converged
#> This is Run number 380
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.8238235 -0.36789829 -5.12382348 -2.067898 2
#> 2 1 -1.35 -13.20 0.3858726 0.63378694 -0.96412743 -12.566213 1
#> 3 1 -2.05 -14.20 0.5237378 0.65483458 -1.52626219 -13.545165 1
#> 4 1 -1.55 -3.10 1.4506927 -0.53698379 -0.09930726 -3.636984 1
#> 5 1 -1.90 -3.60 1.1255678 0.14031834 -0.77443219 -3.459682 1
#> 6 1 -13.70 -1.85 -0.5728860 -0.04157317 -14.27288601 -1.891573 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3460 -36725 9200
#> initial value 998.131940
#> iter 2 value 824.383509
#> iter 3 value 807.110808
#> iter 4 value 804.609549
#> iter 5 value 769.003893
#> iter 6 value 762.296982
#> iter 7 value 761.372627
#> iter 8 value 761.347129
#> iter 9 value 761.347011
#> iter 9 value 761.347004
#> iter 9 value 761.347002
#> final value 761.347002
#> converged
#> This is Run number 381
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.85760768 0.1593707 -2.442392 -1.540629 2
#> 2 1 -1.35 -13.20 -0.05279297 0.6203270 -1.402793 -12.579673 1
#> 3 1 -2.05 -14.20 0.32029435 0.7356314 -1.729706 -13.464369 1
#> 4 1 -1.55 -3.10 0.17708938 1.5847611 -1.372911 -1.515239 1
#> 5 1 -1.90 -3.60 -1.61047892 0.5943495 -3.510479 -3.005651 2
#> 6 1 -13.70 -1.85 -0.48710711 -0.1760377 -14.187107 -2.026038 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2980 -37750 10450
#> initial value 998.131940
#> iter 2 value 799.985535
#> iter 3 value 777.492037
#> iter 4 value 774.014748
#> iter 5 value 740.061548
#> iter 6 value 733.966858
#> iter 7 value 733.212364
#> iter 8 value 733.178220
#> iter 9 value 733.178192
#> iter 9 value 733.178183
#> iter 9 value 733.178183
#> final value 733.178183
#> converged
#> This is Run number 382
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.5757730 -0.04900852 -4.8757730 -1.7490085 2
#> 2 1 -1.35 -13.20 -0.8864095 0.04445981 -2.2364095 -13.1555402 1
#> 3 1 -2.05 -14.20 -0.6520247 -0.95828076 -2.7020247 -15.1582808 1
#> 4 1 -1.55 -3.10 1.3616196 2.14496112 -0.1883804 -0.9550389 1
#> 5 1 -1.90 -3.60 1.7440940 -0.15353866 -0.1559060 -3.7535387 1
#> 6 1 -13.70 -1.85 1.7547992 0.98881260 -11.9452008 -0.8611874 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3740 -37375 8900
#> initial value 998.131940
#> iter 2 value 817.627550
#> iter 3 value 801.483974
#> iter 4 value 798.832130
#> iter 5 value 764.445623
#> iter 6 value 757.445723
#> iter 7 value 756.447274
#> iter 8 value 756.418044
#> iter 9 value 756.417917
#> iter 9 value 756.417912
#> iter 9 value 756.417909
#> final value 756.417909
#> converged
#> This is Run number 383
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.9400618 1.07367366 -5.2400618 -0.6263263 2
#> 2 1 -1.35 -13.20 0.6277262 2.01935340 -0.7222738 -11.1806466 1
#> 3 1 -2.05 -14.20 1.7021077 0.22244379 -0.3478923 -13.9775562 1
#> 4 1 -1.55 -3.10 0.2092025 -0.49853397 -1.3407975 -3.5985340 1
#> 5 1 -1.90 -3.60 -0.9942759 -0.09642462 -2.8942759 -3.6964246 1
#> 6 1 -13.70 -1.85 -0.8354033 0.77153072 -14.5354033 -1.0784693 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4800 -38000 8125
#> initial value 998.131940
#> iter 2 value 814.092893
#> iter 3 value 801.770020
#> iter 4 value 800.525984
#> iter 5 value 768.747308
#> iter 6 value 761.328837
#> iter 7 value 760.147340
#> iter 8 value 760.109880
#> iter 9 value 760.109554
#> iter 10 value 760.109527
#> iter 11 value 760.109509
#> iter 12 value 760.109485
#> iter 12 value 760.109485
#> iter 12 value 760.109485
#> final value 760.109485
#> converged
#> This is Run number 384
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.50849055 1.74844451 -3.7915095 0.04844451 2
#> 2 1 -1.35 -13.20 1.10398435 1.12593663 -0.2460156 -12.07406337 1
#> 3 1 -2.05 -14.20 -0.04720084 -0.03340665 -2.0972008 -14.23340665 1
#> 4 1 -1.55 -3.10 1.31251666 2.23333065 -0.2374833 -0.86666935 1
#> 5 1 -1.90 -3.60 0.89830707 -0.55645122 -1.0016929 -4.15645122 1
#> 6 1 -13.70 -1.85 1.19891370 -0.03636525 -12.5010863 -1.88636525 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3520 -37875 9800
#> initial value 998.131940
#> iter 2 value 803.860157
#> iter 3 value 784.599380
#> iter 4 value 781.891187
#> iter 5 value 748.936531
#> iter 6 value 742.360549
#> iter 7 value 741.544071
#> iter 8 value 741.513015
#> iter 9 value 741.512945
#> iter 10 value 741.512933
#> iter 10 value 741.512933
#> iter 10 value 741.512933
#> final value 741.512933
#> converged
#> This is Run number 385
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.5539792 0.41970509 -4.8539792 -1.280295 2
#> 2 1 -1.35 -13.20 1.1524147 0.17229695 -0.1975853 -13.027703 1
#> 3 1 -2.05 -14.20 -1.3465936 1.05376325 -3.3965936 -13.146237 1
#> 4 1 -1.55 -3.10 -0.8364167 1.31781372 -2.3864167 -1.782186 2
#> 5 1 -1.90 -3.60 1.3273159 -0.03606547 -0.5726841 -3.636065 1
#> 6 1 -13.70 -1.85 0.2577498 0.61305068 -13.4422502 -1.236949 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3620 -37175 9725
#> initial value 998.131940
#> iter 2 value 814.577033
#> iter 3 value 796.077349
#> iter 4 value 794.185102
#> iter 5 value 760.523051
#> iter 6 value 753.985479
#> iter 7 value 753.189968
#> iter 8 value 753.164299
#> iter 9 value 753.164166
#> iter 10 value 753.164150
#> iter 11 value 753.164132
#> iter 11 value 753.164124
#> iter 11 value 753.164124
#> final value 753.164124
#> converged
#> This is Run number 386
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.3307772 -0.97703070 -2.96922283 -2.677031 2
#> 2 1 -1.35 -13.20 0.3730126 0.78300180 -0.97698740 -12.416998 1
#> 3 1 -2.05 -14.20 0.4874007 -0.07852559 -1.56259928 -14.278526 1
#> 4 1 -1.55 -3.10 1.8877448 0.30292876 0.33774480 -2.797071 1
#> 5 1 -1.90 -3.60 1.8036487 1.95206607 -0.09635131 -1.647934 1
#> 6 1 -13.70 -1.85 1.6053658 -0.62949742 -12.09463420 -2.479497 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3680 -36775 10000
#> initial value 998.131940
#> iter 2 value 818.160301
#> iter 3 value 799.162524
#> iter 4 value 797.990337
#> iter 5 value 764.372453
#> iter 6 value 758.043002
#> iter 7 value 757.335913
#> iter 8 value 757.314150
#> iter 9 value 757.314015
#> iter 10 value 757.313969
#> iter 11 value 757.313925
#> iter 11 value 757.313920
#> iter 11 value 757.313920
#> final value 757.313920
#> converged
#> This is Run number 387
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.5447201 0.0879990564 -3.7552799 -1.612001 2
#> 2 1 -1.35 -13.20 -0.8898646 0.0001200102 -2.2398646 -13.199880 1
#> 3 1 -2.05 -14.20 1.0327780 0.0407585915 -1.0172220 -14.159241 1
#> 4 1 -1.55 -3.10 2.7397075 -1.5797860793 1.1897075 -4.679786 1
#> 5 1 -1.90 -3.60 1.1994292 1.2346254260 -0.7005708 -2.365375 1
#> 6 1 -13.70 -1.85 -1.3037933 -0.4343162309 -15.0037933 -2.284316 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3740 -35825 9725
#> initial value 998.131940
#> iter 2 value 832.974919
#> iter 3 value 815.250541
#> iter 4 value 814.487790
#> iter 5 value 779.424351
#> iter 6 value 773.185670
#> iter 7 value 772.463835
#> iter 8 value 772.446150
#> iter 9 value 772.446014
#> iter 10 value 772.445996
#> iter 11 value 772.445949
#> iter 12 value 772.445908
#> iter 12 value 772.445908
#> iter 12 value 772.445908
#> final value 772.445908
#> converged
#> This is Run number 388
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.97509032 -0.404418521 -2.3249097 -2.104419 2
#> 2 1 -1.35 -13.20 0.05565761 0.005060358 -1.2943424 -13.194940 1
#> 3 1 -2.05 -14.20 0.91800570 1.229265139 -1.1319943 -12.970735 1
#> 4 1 -1.55 -3.10 0.99767453 0.277554196 -0.5523255 -2.822446 1
#> 5 1 -1.90 -3.60 1.78081326 0.580708197 -0.1191867 -3.019292 1
#> 6 1 -13.70 -1.85 1.02464190 -0.432978883 -12.6753581 -2.282979 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4080 -35950 8525
#> initial value 998.131940
#> iter 2 value 839.805539
#> iter 3 value 825.913953
#> iter 4 value 824.767752
#> iter 5 value 788.734214
#> iter 6 value 782.003889
#> iter 7 value 780.944975
#> iter 8 value 780.918845
#> iter 9 value 780.918652
#> iter 10 value 780.918627
#> iter 11 value 780.918598
#> iter 12 value 780.918578
#> iter 12 value 780.918578
#> iter 12 value 780.918578
#> final value 780.918578
#> converged
#> This is Run number 389
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.8275207 -0.639394606 -2.4724793 -2.339395 2
#> 2 1 -1.35 -13.20 0.4973062 -0.743076586 -0.8526938 -13.943077 1
#> 3 1 -2.05 -14.20 -1.4117191 -0.003443956 -3.4617191 -14.203444 1
#> 4 1 -1.55 -3.10 4.3032816 -0.541583766 2.7532816 -3.641584 1
#> 5 1 -1.90 -3.60 1.0500830 -1.149952996 -0.8499170 -4.749953 1
#> 6 1 -13.70 -1.85 2.0575200 -0.274205162 -11.6424800 -2.124205 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2920 -37650 10125
#> initial value 998.131940
#> iter 2 value 803.855053
#> iter 3 value 782.180043
#> iter 4 value 778.226442
#> iter 5 value 743.221554
#> iter 6 value 736.930464
#> iter 7 value 736.113180
#> iter 8 value 736.079392
#> iter 9 value 736.079378
#> iter 9 value 736.079376
#> iter 9 value 736.079375
#> final value 736.079375
#> converged
#> This is Run number 390
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.6821045 0.7181798 -3.617895 -0.9818202 2
#> 2 1 -1.35 -13.20 4.0757349 0.9527783 2.725735 -12.2472217 1
#> 3 1 -2.05 -14.20 0.3982918 0.3490549 -1.651708 -13.8509451 1
#> 4 1 -1.55 -3.10 -1.0493160 0.2966815 -2.599316 -2.8033185 1
#> 5 1 -1.90 -3.60 0.6839480 0.3739646 -1.216052 -3.2260354 1
#> 6 1 -13.70 -1.85 -0.3167600 0.5912664 -14.016760 -1.2587336 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3260 -35675 8825
#> initial value 998.131940
#> iter 2 value 840.637641
#> iter 3 value 824.310202
#> iter 4 value 821.921961
#> iter 5 value 783.667850
#> iter 6 value 777.075771
#> iter 7 value 776.091094
#> iter 8 value 776.068791
#> iter 9 value 776.068690
#> iter 9 value 776.068685
#> iter 9 value 776.068683
#> final value 776.068683
#> converged
#> This is Run number 391
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.9106917 -0.8125360 -3.389308 -2.512536 2
#> 2 1 -1.35 -13.20 0.7613620 0.8236074 -0.588638 -12.376393 1
#> 3 1 -2.05 -14.20 -0.5783761 -0.6640253 -2.628376 -14.864025 1
#> 4 1 -1.55 -3.10 6.4560417 -0.1213165 4.906042 -3.221316 1
#> 5 1 -1.90 -3.60 -0.6298621 1.9372185 -2.529862 -1.662781 2
#> 6 1 -13.70 -1.85 1.2342138 0.4195981 -12.465786 -1.430402 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4440 -37825 8375
#> initial value 998.131940
#> iter 2 value 815.022211
#> iter 3 value 801.493226
#> iter 4 value 799.750925
#> iter 5 value 767.234179
#> iter 6 value 759.930471
#> iter 7 value 758.813805
#> iter 8 value 758.779433
#> iter 9 value 758.779172
#> iter 10 value 758.779154
#> iter 10 value 758.779147
#> iter 10 value 758.779140
#> final value 758.779140
#> converged
#> This is Run number 392
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.7657366 -1.4671450 -5.0657366 -3.1671450 2
#> 2 1 -1.35 -13.20 1.1977104 -0.7639236 -0.1522896 -13.9639236 1
#> 3 1 -2.05 -14.20 0.5830636 0.3322872 -1.4669364 -13.8677128 1
#> 4 1 -1.55 -3.10 1.1336049 -0.3462181 -0.4163951 -3.4462181 1
#> 5 1 -1.90 -3.60 -0.8896255 0.8752495 -2.7896255 -2.7247505 2
#> 6 1 -13.70 -1.85 -0.3171901 1.6015377 -14.0171901 -0.2484623 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 2920 -36650 11000
#> initial value 998.131940
#> iter 2 value 810.997704
#> iter 3 value 787.158696
#> iter 4 value 785.206003
#> iter 5 value 751.073970
#> iter 6 value 745.436262
#> iter 7 value 744.838300
#> iter 8 value 744.814653
#> iter 9 value 744.814592
#> iter 10 value 744.814526
#> iter 10 value 744.814526
#> iter 10 value 744.814526
#> final value 744.814526
#> converged
#> This is Run number 393
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.4902876 0.6735175 -3.8097124 -1.0264825 2
#> 2 1 -1.35 -13.20 -0.5068213 -0.7401942 -1.8568213 -13.9401942 1
#> 3 1 -2.05 -14.20 -0.1989112 0.3348379 -2.2489112 -13.8651621 1
#> 4 1 -1.55 -3.10 0.3328177 -0.9039621 -1.2171823 -4.0039621 1
#> 5 1 -1.90 -3.60 1.5255733 2.5135634 -0.3744267 -1.0864366 1
#> 6 1 -13.70 -1.85 -0.5064764 1.8791741 -14.2064764 0.0291741 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3340 -36825 10650
#> initial value 998.131940
#> iter 2 value 812.034807
#> iter 3 value 790.268294
#> iter 4 value 788.905555
#> iter 5 value 755.529255
#> iter 6 value 749.593226
#> iter 7 value 748.975513
#> iter 8 value 748.953188
#> iter 9 value 748.953103
#> iter 10 value 748.953016
#> iter 10 value 748.953012
#> iter 11 value 748.952999
#> iter 11 value 748.952989
#> iter 11 value 748.952986
#> final value 748.952986
#> converged
#> This is Run number 394
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.66372044 0.51364269 -3.6362796 -1.1863573 2
#> 2 1 -1.35 -13.20 0.61903933 -0.46948893 -0.7309607 -13.6694889 1
#> 3 1 -2.05 -14.20 0.04191658 -0.09950792 -2.0080834 -14.2995079 1
#> 4 1 -1.55 -3.10 0.46127621 0.27754037 -1.0887238 -2.8224596 1
#> 5 1 -1.90 -3.60 1.08725135 4.47028958 -0.8127487 0.8702896 2
#> 6 1 -13.70 -1.85 3.05063436 1.65761842 -10.6493656 -0.1923816 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4160 -37025 9850
#> initial value 998.131940
#> iter 2 value 816.167658
#> iter 3 value 798.479829
#> iter 4 value 797.988564
#> iter 5 value 765.395905
#> iter 6 value 758.886779
#> iter 7 value 758.191307
#> iter 8 value 758.170465
#> iter 9 value 758.170317
#> iter 10 value 758.170242
#> iter 11 value 758.170168
#> iter 12 value 758.170154
#> iter 12 value 758.170154
#> iter 12 value 758.170154
#> final value 758.170154
#> converged
#> This is Run number 395
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.3258676 2.5605552 -4.625868 0.8605552 2
#> 2 1 -1.35 -13.20 -0.9648202 -0.4647609 -2.314820 -13.6647609 1
#> 3 1 -2.05 -14.20 0.6408942 0.9080456 -1.409106 -13.2919544 1
#> 4 1 -1.55 -3.10 3.7189169 3.7562104 2.168917 0.6562104 1
#> 5 1 -1.90 -3.60 0.4748912 1.2227608 -1.425109 -2.3772392 1
#> 6 1 -13.70 -1.85 1.3607732 -0.3238756 -12.339227 -2.1738756 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3720 -35975 9675
#> initial value 998.131940
#> iter 2 value 831.362607
#> iter 3 value 813.690389
#> iter 4 value 812.775513
#> iter 5 value 777.775061
#> iter 6 value 771.475935
#> iter 7 value 770.731449
#> iter 8 value 770.712636
#> iter 9 value 770.712492
#> iter 10 value 770.712476
#> iter 11 value 770.712434
#> iter 12 value 770.712395
#> iter 12 value 770.712395
#> iter 12 value 770.712395
#> final value 770.712395
#> converged
#> This is Run number 396
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.1554860 0.4993881 -4.4554860 -1.200612 2
#> 2 1 -1.35 -13.20 0.9525896 0.7329201 -0.3974104 -12.467080 1
#> 3 1 -2.05 -14.20 2.7461798 -1.1668117 0.6961798 -15.366812 1
#> 4 1 -1.55 -3.10 -1.6611499 -0.7112677 -3.2111499 -3.811268 1
#> 5 1 -1.90 -3.60 0.1267441 1.5217781 -1.7732559 -2.078222 1
#> 6 1 -13.70 -1.85 -0.7683023 0.1841228 -14.4683023 -1.665877 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3460 -36675 8900
#> initial value 998.131940
#> iter 2 value 827.094089
#> iter 3 value 810.595844
#> iter 4 value 807.862986
#> iter 5 value 771.585064
#> iter 6 value 764.737832
#> iter 7 value 763.739818
#> iter 8 value 763.713774
#> iter 9 value 763.713670
#> iter 9 value 763.713665
#> iter 9 value 763.713663
#> final value 763.713663
#> converged
#> This is Run number 397
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.5367730 -0.90910000 -3.7632270 -2.609100 2
#> 2 1 -1.35 -13.20 0.9568558 -0.60709962 -0.3931442 -13.807100 1
#> 3 1 -2.05 -14.20 -0.3020944 0.01629013 -2.3520944 -14.183710 1
#> 4 1 -1.55 -3.10 -0.1288342 1.67811765 -1.6788342 -1.421882 2
#> 5 1 -1.90 -3.60 0.4207107 1.85729938 -1.4792893 -1.742701 1
#> 6 1 -13.70 -1.85 -0.4818181 0.10236337 -14.1818181 -1.747637 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3080 -35500 9375
#> initial value 998.131940
#> iter 2 value 838.912140
#> iter 3 value 820.819290
#> iter 4 value 818.594622
#> iter 5 value 780.762651
#> iter 6 value 774.482009
#> iter 7 value 773.635593
#> iter 8 value 773.615809
#> iter 9 value 773.615710
#> iter 9 value 773.615702
#> iter 9 value 773.615700
#> final value 773.615700
#> converged
#> This is Run number 398
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 1.1405424 1.48939543 -3.15945762 -0.2106046 2
#> 2 1 -1.35 -13.20 1.2676851 0.90987849 -0.08231489 -12.2901215 1
#> 3 1 -2.05 -14.20 1.3490974 -0.85440133 -0.70090258 -15.0544013 1
#> 4 1 -1.55 -3.10 -0.3633263 -0.08507850 -1.91332630 -3.1850785 1
#> 5 1 -1.90 -3.60 0.3948403 -0.02191982 -1.50515973 -3.6219198 1
#> 6 1 -13.70 -1.85 -0.7931612 -0.39154719 -14.49316115 -2.2415472 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3340 -36800 9525
#> initial value 998.131940
#> iter 2 value 820.926267
#> iter 3 value 802.467129
#> iter 4 value 799.917465
#> iter 5 value 764.598033
#> iter 6 value 758.042821
#> iter 7 value 757.186058
#> iter 8 value 757.160855
#> iter 9 value 757.160753
#> iter 9 value 757.160748
#> iter 9 value 757.160745
#> final value 757.160745
#> converged
#> This is Run number 399
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 0.83279221 1.106997 -3.4672078 -0.5930031 2
#> 2 1 -1.35 -13.20 0.91866047 1.212756 -0.4313395 -11.9872444 1
#> 3 1 -2.05 -14.20 0.43158686 -1.018879 -1.6184131 -15.2188793 1
#> 4 1 -1.55 -3.10 -0.02309454 4.918777 -1.5730945 1.8187774 2
#> 5 1 -1.90 -3.60 -0.52709839 3.173096 -2.4270984 -0.4269043 2
#> 6 1 -13.70 -1.85 1.69581656 3.819838 -12.0041834 1.9698376 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3000 -36550 10425
#> initial value 998.131940
#> iter 2 value 817.135422
#> iter 3 value 795.358301
#> iter 4 value 793.071301
#> iter 5 value 758.049672
#> iter 6 value 752.069022
#> iter 7 value 751.384737
#> iter 8 value 751.361474
#> iter 9 value 751.361401
#> iter 10 value 751.361379
#> iter 10 value 751.361371
#> iter 10 value 751.361371
#> final value 751.361371
#> converged
#> This is Run number 400
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 3 80 50 0 20 50 100 1
#> 2 1 5 60 25 50 20 200 50 1
#> 3 1 10 80 25 25 20 200 0 1
#> 4 1 34 80 25 50 60 50 50 1
#> 5 1 37 40 50 100 60 50 25 1
#> 6 1 39 20 200 25 60 25 25 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -1.70 -0.7851164 0.3567035 -5.0851164 -1.343297 2
#> 2 1 -1.35 -13.20 1.6493827 1.6266524 0.2993827 -11.573348 1
#> 3 1 -2.05 -14.20 1.2573106 -0.4512297 -0.7926894 -14.651230 1
#> 4 1 -1.55 -3.10 6.4384044 0.4736591 4.8884044 -2.626341 1
#> 5 1 -1.90 -3.60 0.5671376 -0.1417393 -1.3328624 -3.741739 1
#> 6 1 -13.70 -1.85 2.1371718 -1.2514683 -11.5628282 -3.101468 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3160 -36300 11050
#> initial value 998.131940
#> iter 2 value 815.673429
#> iter 3 value 792.391816
#> iter 4 value 791.323814
#> iter 5 value 757.637547
#> iter 6 value 752.043899
#> iter 7 value 751.502306
#> iter 8 value 751.483239
#> iter 9 value 751.483169
#> iter 10 value 751.483044
#> iter 10 value 751.483044
#> iter 11 value 751.483032
#> iter 12 value 751.483019
#> iter 12 value 751.483019
#> iter 12 value 751.483019
#> final value 751.483019
#> converged
#>
#>
#> ================ ==== === ===== ==== ====== ===== ===== ===== ===== ======== ===
#> \ vars n mean sd median min max range skew kurtosis se
#> ================ ==== === ===== ==== ====== ===== ===== ===== ===== ======== ===
#> est_bpreis 1 400 -0.01 0.00 -0.01 -0.01 0.00 0.01 0.15 -0.19 0
#> est_blade 2 400 -0.01 0.00 -0.01 -0.02 -0.01 0.00 -0.01 -0.22 0
#> est_bwarte 3 400 0.01 0.00 0.01 0.00 0.01 0.01 0.06 -0.23 0
#> rob_pval0_bpreis 4 400 0.00 0.01 0.00 0.00 0.13 0.13 7.20 59.94 0
#> rob_pval0_blade 5 400 0.00 0.00 0.00 0.00 0.00 0.00 NaN NaN 0
#> rob_pval0_bwarte 6 400 0.00 0.00 0.00 0.00 0.00 0.00 NaN NaN 0
#> ================ ==== === ===== ==== ====== ===== ===== ===== ===== ======== ===
#>
#> FALSE TRUE
#> 1.75 98.25
#> 'simple' is deprecated and will be removed in the future. Use 'exact' instead.
#> bcoeff_lookup already exists; skipping modification.
#> Utility function used in simulation, ie the true utility:
#>
#> $u1
#> $u1$v1
#> V.1 ~ bpreis * alt1.x1 + blade * alt1.x2 + bwarte * alt1.x3
#> <environment: 0x5cc5f94640f8>
#>
#> $u1$v2
#> V.2 ~ bpreis * alt2.x1 + blade * alt2.x2 + bwarte * alt2.x3
#> <environment: 0x5cc60a0df5b0>
#>
#>
#> $u2
#> $u2$v1
#> V.1 ~ bpreis * alt1.x1
#> <environment: 0x5cc603c834c0>
#>
#> $u2$v2
#> V.2 ~ bpreis * alt2.x1
#> <environment: 0x5cc6045c21d8>
#> 'destype' is deprecated. Please use 'designtype' instead.
#> New names:
#>
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.7059880 1.89525318 -3.5940120 -10.704747 1
#> 2 1 -0.35 -14.40 -0.3851185 0.05753665 -0.7351185 -14.342463 1
#> 3 1 -12.20 -2.55 -1.4435342 -0.63271598 -13.6435342 -3.182716 2
#> 4 1 -2.30 -13.70 2.0661038 0.02056119 -0.2338962 -13.679439 1
#> 5 1 -12.60 -7.80 0.5351904 0.48198354 -12.0648096 -7.318016 2
#> 6 1 -7.60 -12.40 -0.1241744 0.58144088 -7.7241744 -11.818559 1
#>
#>
#> Transformed utility function (type: simple ):
#> [1] "U_1 = @bpreis * $alt1_x1 + @blade * $alt1_x2 + @bwarte * $alt1_x3 ;U_2 = @bpreis * $alt2_x1 + @blade * $alt2_x2 + @bwarte * $alt2_x3 ;"
#> This is Run number 1
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.9193104 -0.2744702 -3.380690 -12.874470 1
#> 2 1 -0.35 -14.40 -0.5474400 0.3399819 -0.897440 -14.060018 1
#> 3 1 -12.20 -2.55 -1.3134361 -0.4939840 -13.513436 -3.043984 2
#> 4 1 -2.30 -13.70 0.1781223 0.1963674 -2.121878 -13.503633 1
#> 5 1 -12.60 -7.80 0.8697516 1.7431924 -11.730248 -6.056808 2
#> 6 1 -7.60 -12.40 0.3825124 0.2436270 -7.217488 -12.156373 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4580 -75700 15525
#> initial value 998.131940
#> iter 2 value 640.172849
#> iter 3 value 640.049988
#> iter 4 value 639.986869
#> iter 5 value 615.096583
#> iter 6 value 611.625281
#> iter 7 value 611.500316
#> iter 8 value 611.498883
#> iter 9 value 611.498871
#> iter 9 value 611.498864
#> iter 9 value 611.498864
#> final value 611.498864
#> converged
#> This is Run number 2
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.05554268 0.3602343 -4.355543 -12.239766 1
#> 2 1 -0.35 -14.40 3.69826972 1.9012154 3.348270 -12.498785 1
#> 3 1 -12.20 -2.55 0.89757842 -1.1257758 -11.302422 -3.675776 2
#> 4 1 -2.30 -13.70 0.47256631 0.7138095 -1.827434 -12.986191 1
#> 5 1 -12.60 -7.80 0.53439641 0.1799763 -12.065604 -7.620024 2
#> 6 1 -7.60 -12.40 0.25211904 1.1483597 -7.347881 -11.251640 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5960 -74050 13775
#> initial value 998.131940
#> iter 2 value 657.805051
#> iter 3 value 657.333061
#> iter 4 value 656.923798
#> iter 5 value 634.872575
#> iter 6 value 632.285859
#> iter 7 value 632.222331
#> iter 8 value 632.222090
#> iter 8 value 632.222090
#> final value 632.222090
#> converged
#> This is Run number 3
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.7228770 0.20586216 -3.57712299 -12.394138 1
#> 2 1 -0.35 -14.40 0.3713074 -0.04235023 0.02130739 -14.442350 1
#> 3 1 -12.20 -2.55 -0.4737728 1.12363912 -12.67377276 -1.426361 2
#> 4 1 -2.30 -13.70 4.8570819 0.54079153 2.55708192 -13.159208 1
#> 5 1 -12.60 -7.80 2.3798812 1.31340953 -10.22011884 -6.486590 2
#> 6 1 -7.60 -12.40 -0.6281472 -0.30097492 -8.22814721 -12.700975 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4260 -72475 15000
#> initial value 998.131940
#> iter 2 value 671.074872
#> iter 3 value 670.910487
#> iter 4 value 670.825637
#> iter 5 value 650.057658
#> iter 6 value 647.641058
#> iter 7 value 647.576203
#> iter 8 value 647.575700
#> iter 8 value 647.575697
#> final value 647.575697
#> converged
#> This is Run number 4
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.0982470 -0.66588292 -5.3982470 -13.265883 1
#> 2 1 -0.35 -14.40 -0.3993748 3.60804600 -0.7493748 -10.791954 1
#> 3 1 -12.20 -2.55 -0.3232124 -0.61525010 -12.5232124 -3.165250 2
#> 4 1 -2.30 -13.70 0.6550289 1.72194663 -1.6449711 -11.978053 1
#> 5 1 -12.60 -7.80 2.5009970 -0.56096743 -10.0990030 -8.360967 2
#> 6 1 -7.60 -12.40 2.3267573 0.03634543 -5.2732427 -12.363655 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5020 -74400 14700
#> initial value 998.131940
#> iter 2 value 653.641209
#> iter 3 value 653.634606
#> iter 4 value 653.633488
#> iter 5 value 630.557273
#> iter 6 value 628.237952
#> iter 7 value 628.172062
#> iter 8 value 628.171674
#> iter 8 value 628.171671
#> final value 628.171671
#> converged
#> This is Run number 5
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.2321829 -0.290056706 -4.0678171 -12.890057 1
#> 2 1 -0.35 -14.40 4.9728788 -1.036634361 4.6228788 -15.436634 1
#> 3 1 -12.20 -2.55 -0.1439534 0.818484581 -12.3439534 -1.731515 2
#> 4 1 -2.30 -13.70 1.3210914 -0.383154007 -0.9789086 -14.083154 1
#> 5 1 -12.60 -7.80 2.4607879 0.009601869 -10.1392121 -7.790398 2
#> 6 1 -7.60 -12.40 5.6485271 1.768373404 -1.9514729 -10.631627 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4960 -72475 13875
#> initial value 998.131940
#> iter 2 value 672.695641
#> iter 3 value 672.628951
#> iter 4 value 672.627793
#> iter 5 value 652.229246
#> iter 6 value 650.384838
#> iter 7 value 650.342852
#> iter 8 value 650.342682
#> iter 8 value 650.342681
#> final value 650.342681
#> converged
#> This is Run number 6
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 3.4083739 -1.1193423 -0.8916261 -13.719342 1
#> 2 1 -0.35 -14.40 1.8575247 -0.7885583 1.5075247 -15.188558 1
#> 3 1 -12.20 -2.55 1.0660093 -0.5798027 -11.1339907 -3.129803 2
#> 4 1 -2.30 -13.70 0.2698273 0.3022642 -2.0301727 -13.397736 1
#> 5 1 -12.60 -7.80 -0.2641107 0.7768931 -12.8641107 -7.023107 2
#> 6 1 -7.60 -12.40 2.7589991 0.7141656 -4.8410009 -11.685834 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4500 -69850 13325
#> initial value 998.131940
#> iter 2 value 696.988010
#> iter 3 value 696.881945
#> iter 4 value 696.808281
#> iter 5 value 679.616301
#> iter 6 value 677.987830
#> iter 7 value 677.958816
#> iter 8 value 677.958712
#> iter 8 value 677.958711
#> final value 677.958711
#> converged
#> This is Run number 7
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.7485822 -1.0283519 -5.0485822 -13.628352 1
#> 2 1 -0.35 -14.40 -0.6111353 -0.6827324 -0.9611353 -15.082732 1
#> 3 1 -12.20 -2.55 2.8518924 -1.5672787 -9.3481076 -4.117279 2
#> 4 1 -2.30 -13.70 1.1025005 0.1710741 -1.1974995 -13.528926 1
#> 5 1 -12.60 -7.80 2.3271123 -0.8231013 -10.2728877 -8.623101 2
#> 6 1 -7.60 -12.40 -0.3313798 0.2901016 -7.9313798 -12.109898 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5380 -71400 12425
#> initial value 998.131940
#> iter 2 value 684.258526
#> iter 3 value 683.658299
#> iter 4 value 683.611663
#> iter 5 value 665.013881
#> iter 6 value 663.165016
#> iter 7 value 663.130273
#> iter 8 value 663.130184
#> iter 8 value 663.130184
#> final value 663.130184
#> converged
#> This is Run number 8
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.7524202 2.9770078 -1.5475798 -9.6229922 1
#> 2 1 -0.35 -14.40 -0.2423397 -0.4403906 -0.5923397 -14.8403906 1
#> 3 1 -12.20 -2.55 1.4207605 1.9175808 -10.7792395 -0.6324192 2
#> 4 1 -2.30 -13.70 -0.4718021 -0.1271697 -2.7718021 -13.8271697 1
#> 5 1 -12.60 -7.80 -0.5129995 4.1491038 -13.1129995 -3.6508962 2
#> 6 1 -7.60 -12.40 0.5635570 1.3518293 -7.0364430 -11.0481707 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4640 -71850 14075
#> initial value 998.131940
#> iter 2 value 678.137100
#> iter 3 value 678.096564
#> iter 4 value 678.065865
#> iter 5 value 658.586447
#> iter 6 value 656.495016
#> iter 7 value 656.449003
#> iter 8 value 656.448775
#> iter 8 value 656.448773
#> final value 656.448773
#> converged
#> This is Run number 9
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.4295719 0.8039655 -5.7295719 -11.7960345 1
#> 2 1 -0.35 -14.40 0.6391664 2.1755329 0.2891664 -12.2244671 1
#> 3 1 -12.20 -2.55 1.5134205 1.9885634 -10.6865795 -0.5614366 2
#> 4 1 -2.30 -13.70 -1.1240888 1.2145729 -3.4240888 -12.4854271 1
#> 5 1 -12.60 -7.80 -0.1838256 2.2999210 -12.7838256 -5.5000790 2
#> 6 1 -7.60 -12.40 -0.3770556 0.7023616 -7.9770556 -11.6976384 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5240 -70350 15925
#> initial value 998.131940
#> iter 2 value 687.431821
#> iter 3 value 686.768938
#> iter 4 value 686.252659
#> iter 5 value 667.569933
#> iter 6 value 665.638303
#> iter 7 value 665.598101
#> iter 8 value 665.597952
#> iter 8 value 665.597951
#> final value 665.597951
#> converged
#> This is Run number 10
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.8398136 1.2790753 -5.1398136 -11.320925 1
#> 2 1 -0.35 -14.40 1.0552166 1.7240189 0.7052166 -12.675981 1
#> 3 1 -12.20 -2.55 0.1282802 0.3570956 -12.0717198 -2.192904 2
#> 4 1 -2.30 -13.70 3.1963200 0.3399888 0.8963200 -13.360011 1
#> 5 1 -12.60 -7.80 -0.9934452 2.0442510 -13.5934452 -5.755749 2
#> 6 1 -7.60 -12.40 -0.4511060 0.5460933 -8.0511060 -11.853907 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4580 -73900 15075
#> initial value 998.131940
#> iter 2 value 657.816408
#> iter 3 value 657.748097
#> iter 4 value 657.729829
#> iter 5 value 635.421175
#> iter 6 value 632.647976
#> iter 7 value 632.566907
#> iter 8 value 632.566244
#> iter 8 value 632.566240
#> final value 632.566240
#> converged
#> This is Run number 11
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.4289934 -0.7187056 -3.8710066 -13.3187056 1
#> 2 1 -0.35 -14.40 1.1067301 -0.1382295 0.7567301 -14.5382295 1
#> 3 1 -12.20 -2.55 4.6433545 1.9764282 -7.5566455 -0.5735718 2
#> 4 1 -2.30 -13.70 -0.4971627 -0.3503827 -2.7971627 -14.0503827 1
#> 5 1 -12.60 -7.80 0.5052678 -0.6215517 -12.0947322 -8.4215517 2
#> 6 1 -7.60 -12.40 -0.1631554 0.9032637 -7.7631554 -11.4967363 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5120 -72750 14800
#> initial value 998.131940
#> iter 2 value 668.483543
#> iter 3 value 668.451284
#> iter 4 value 668.427295
#> iter 5 value 647.771857
#> iter 6 value 645.443260
#> iter 7 value 645.388411
#> iter 8 value 645.388149
#> iter 8 value 645.388147
#> final value 645.388147
#> converged
#> This is Run number 12
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.09975262 -0.73262882 -4.399753 -13.332629 1
#> 2 1 -0.35 -14.40 -1.31839137 -0.89757215 -1.668391 -15.297572 1
#> 3 1 -12.20 -2.55 -0.62493813 1.05367991 -12.824938 -1.496320 2
#> 4 1 -2.30 -13.70 1.00227885 0.79835478 -1.297721 -12.901645 1
#> 5 1 -12.60 -7.80 -0.02617004 1.87441859 -12.626170 -5.925581 2
#> 6 1 -7.60 -12.40 0.56309378 0.09669358 -7.036906 -12.303306 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4400 -70550 15550
#> initial value 998.131940
#> iter 2 value 686.967163
#> iter 3 value 686.683904
#> iter 4 value 686.675879
#> iter 5 value 667.997262
#> iter 6 value 666.071877
#> iter 7 value 666.030008
#> iter 8 value 666.029794
#> iter 8 value 666.029793
#> final value 666.029793
#> converged
#> This is Run number 13
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.2294679 2.5470979 -4.0705321 -10.052902 1
#> 2 1 -0.35 -14.40 0.1240267 -0.7046942 -0.2259733 -15.104694 1
#> 3 1 -12.20 -2.55 0.4009340 1.4261849 -11.7990660 -1.123815 2
#> 4 1 -2.30 -13.70 1.2694437 2.9539571 -1.0305563 -10.746043 1
#> 5 1 -12.60 -7.80 1.7876890 -0.1398500 -10.8123110 -7.939850 2
#> 6 1 -7.60 -12.40 1.5770850 1.5894832 -6.0229150 -10.810517 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4380 -73500 15775
#> initial value 998.131940
#> iter 2 value 660.216043
#> iter 3 value 659.968696
#> iter 4 value 659.842737
#> iter 5 value 637.736769
#> iter 6 value 634.950378
#> iter 7 value 634.867119
#> iter 8 value 634.866377
#> iter 8 value 634.866372
#> final value 634.866372
#> converged
#> This is Run number 14
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 3.0599843 1.9102539 -1.2400157 -10.689746 1
#> 2 1 -0.35 -14.40 0.7952674 -0.8052189 0.4452674 -15.205219 1
#> 3 1 -12.20 -2.55 -0.4112932 -0.1135727 -12.6112932 -2.663573 2
#> 4 1 -2.30 -13.70 1.0645121 -0.2366272 -1.2354879 -13.936627 1
#> 5 1 -12.60 -7.80 1.9915866 1.4085760 -10.6084134 -6.391424 2
#> 6 1 -7.60 -12.40 -0.8045080 -1.0278836 -8.4045080 -13.427884 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5040 -73250 14550
#> initial value 998.131940
#> iter 2 value 664.459724
#> iter 3 value 664.453417
#> iter 4 value 664.448505
#> iter 5 value 643.244910
#> iter 6 value 640.877661
#> iter 7 value 640.819025
#> iter 8 value 640.818724
#> iter 8 value 640.818722
#> final value 640.818722
#> converged
#> This is Run number 15
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.4117970 1.0367817 -4.7117970 -11.563218 1
#> 2 1 -0.35 -14.40 0.1822419 -1.1958615 -0.1677581 -15.595861 1
#> 3 1 -12.20 -2.55 0.2857328 0.1514573 -11.9142672 -2.398543 2
#> 4 1 -2.30 -13.70 -1.2252305 4.9886572 -3.5252305 -8.711343 1
#> 5 1 -12.60 -7.80 -1.5128472 -0.1949998 -14.1128472 -7.995000 2
#> 6 1 -7.60 -12.40 0.4712054 1.6443585 -7.1287946 -10.755641 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4800 -71400 13650
#> initial value 998.131940
#> iter 2 value 682.753840
#> iter 3 value 682.680802
#> iter 4 value 682.668649
#> iter 5 value 663.830449
#> iter 6 value 661.913851
#> iter 7 value 661.874726
#> iter 8 value 661.874570
#> iter 8 value 661.874569
#> final value 661.874569
#> converged
#> This is Run number 16
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 3.6628998 0.1323652 -0.6371002 -12.4676348 1
#> 2 1 -0.35 -14.40 1.2192824 1.4258443 0.8692824 -12.9741557 1
#> 3 1 -12.20 -2.55 7.6161671 1.8520873 -4.5838329 -0.6979127 2
#> 4 1 -2.30 -13.70 0.7249565 1.3030729 -1.5750435 -12.3969271 1
#> 5 1 -12.60 -7.80 0.5146706 -0.1223649 -12.0853294 -7.9223649 2
#> 6 1 -7.60 -12.40 0.6091346 1.1500608 -6.9908654 -11.2499392 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4800 -72625 13200
#> initial value 998.131940
#> iter 2 value 672.533067
#> iter 3 value 672.229587
#> iter 4 value 672.142743
#> iter 5 value 652.017004
#> iter 6 value 649.797748
#> iter 7 value 649.747022
#> iter 8 value 649.746780
#> iter 8 value 649.746779
#> final value 649.746779
#> converged
#> This is Run number 17
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.3650858 -0.1400813 -5.665086 -12.7400813 1
#> 2 1 -0.35 -14.40 1.4243317 -1.0421106 1.074332 -15.4421106 1
#> 3 1 -12.20 -2.55 -0.1014611 1.7597149 -12.301461 -0.7902851 2
#> 4 1 -2.30 -13.70 0.3585941 -0.3288604 -1.941406 -14.0288604 1
#> 5 1 -12.60 -7.80 1.0722720 1.1535716 -11.527728 -6.6464284 2
#> 6 1 -7.60 -12.40 0.2376137 -0.8773833 -7.362386 -13.2773833 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5200 -70250 14975
#> initial value 998.131940
#> iter 2 value 690.214747
#> iter 3 value 689.975002
#> iter 4 value 689.812072
#> iter 5 value 671.597865
#> iter 6 value 669.807969
#> iter 7 value 669.772959
#> iter 8 value 669.772846
#> iter 8 value 669.772846
#> final value 669.772846
#> converged
#> This is Run number 18
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.19579597 -0.10295234 -3.104204032 -12.702952 1
#> 2 1 -0.35 -14.40 0.35828614 0.01944969 0.008286141 -14.380550 1
#> 3 1 -12.20 -2.55 0.01361797 0.29537234 -12.186382032 -2.254628 2
#> 4 1 -2.30 -13.70 -0.10496944 -0.10803920 -2.404969436 -13.808039 1
#> 5 1 -12.60 -7.80 2.38587663 -0.22559597 -10.214123365 -8.025596 2
#> 6 1 -7.60 -12.40 -0.47868891 0.39028117 -8.078688914 -12.009719 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5800 -73425 13300
#> initial value 998.131940
#> iter 2 value 664.431666
#> iter 3 value 663.925120
#> iter 4 value 663.642017
#> iter 5 value 642.570273
#> iter 6 value 640.191969
#> iter 7 value 640.137584
#> iter 8 value 640.137400
#> iter 8 value 640.137400
#> final value 640.137400
#> converged
#> This is Run number 19
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.30216169 -1.43318278 -4.6021617 -14.0331828 1
#> 2 1 -0.35 -14.40 0.17285637 0.05161694 -0.1771436 -14.3483831 1
#> 3 1 -12.20 -2.55 -0.68470962 1.89310333 -12.8847096 -0.6568967 2
#> 4 1 -2.30 -13.70 -0.07495668 0.12787366 -2.3749567 -13.5721263 1
#> 5 1 -12.60 -7.80 -0.54425565 -0.74705443 -13.1442556 -8.5470544 2
#> 6 1 -7.60 -12.40 1.27771078 -0.10004515 -6.3222892 -12.5000452 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4900 -70975 13825
#> initial value 998.131940
#> iter 2 value 686.146574
#> iter 3 value 686.115588
#> iter 4 value 686.113278
#> iter 5 value 667.586700
#> iter 6 value 665.878470
#> iter 7 value 665.845123
#> iter 8 value 665.845010
#> iter 8 value 665.845009
#> final value 665.845009
#> converged
#> This is Run number 20
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.5057454 4.0276660 -2.7942546 -8.572334 1
#> 2 1 -0.35 -14.40 -1.2301331 -0.5855654 -1.5801331 -14.985565 1
#> 3 1 -12.20 -2.55 2.6845947 1.4782747 -9.5154053 -1.071725 2
#> 4 1 -2.30 -13.70 1.6190676 2.0385823 -0.6809324 -11.661418 1
#> 5 1 -12.60 -7.80 0.2114763 0.3780838 -12.3885237 -7.421916 2
#> 6 1 -7.60 -12.40 -0.7991912 -1.5024815 -8.3991912 -13.902482 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5200 -73025 15800
#> initial value 998.131940
#> iter 2 value 664.004004
#> iter 3 value 663.740853
#> iter 4 value 663.556405
#> iter 5 value 642.162915
#> iter 6 value 639.629061
#> iter 7 value 639.563850
#> iter 8 value 639.563501
#> iter 8 value 639.563499
#> final value 639.563499
#> converged
#> This is Run number 21
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.9992289 0.6952202 -5.299229 -11.904780 1
#> 2 1 -0.35 -14.40 -0.6715010 -0.1457243 -1.021501 -14.545724 1
#> 3 1 -12.20 -2.55 -0.5240440 0.7998783 -12.724044 -1.750122 2
#> 4 1 -2.30 -13.70 0.3232300 1.0099074 -1.976770 -12.690093 1
#> 5 1 -12.60 -7.80 -0.5822402 -1.6134855 -13.182240 -9.413485 2
#> 6 1 -7.60 -12.40 1.1671804 1.6989290 -6.432820 -10.701071 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4600 -72350 15775
#> initial value 998.131940
#> iter 2 value 670.503125
#> iter 3 value 670.266167
#> iter 4 value 670.264037
#> iter 5 value 649.400981
#> iter 6 value 647.201406
#> iter 7 value 647.144788
#> iter 8 value 647.144442
#> iter 8 value 647.144440
#> final value 647.144440
#> converged
#> This is Run number 22
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.0948781 -0.2312166 -5.394878 -12.831217 1
#> 2 1 -0.35 -14.40 -0.7789312 0.5678984 -1.128931 -13.832102 1
#> 3 1 -12.20 -2.55 2.0148925 0.7968320 -10.185107 -1.753168 2
#> 4 1 -2.30 -13.70 -1.0312677 3.7836420 -3.331268 -9.916358 1
#> 5 1 -12.60 -7.80 -0.1976326 -1.0647231 -12.797633 -8.864723 2
#> 6 1 -7.60 -12.40 0.9005747 -0.8090584 -6.699425 -13.209058 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4020 -71100 15675
#> initial value 998.131940
#> iter 2 value 682.087702
#> iter 3 value 681.657439
#> iter 4 value 681.443292
#> iter 5 value 662.002212
#> iter 6 value 659.819600
#> iter 7 value 659.765231
#> iter 8 value 659.764837
#> iter 8 value 659.764835
#> final value 659.764835
#> converged
#> This is Run number 23
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.5156695 -0.76084928 -2.7843305 -13.360849 1
#> 2 1 -0.35 -14.40 2.6716224 0.81985090 2.3216224 -13.580149 1
#> 3 1 -12.20 -2.55 -0.7183199 -0.06611882 -12.9183199 -2.616119 2
#> 4 1 -2.30 -13.70 1.6148333 -0.26844904 -0.6851667 -13.968449 1
#> 5 1 -12.60 -7.80 -0.8112570 0.68614428 -13.4112570 -7.113856 2
#> 6 1 -7.60 -12.40 0.7086253 -1.28793791 -6.8913747 -13.687938 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4800 -73375 13550
#> initial value 998.131940
#> iter 2 value 665.172946
#> iter 3 value 664.940679
#> iter 4 value 664.844239
#> iter 5 value 643.762841
#> iter 6 value 641.319094
#> iter 7 value 641.258189
#> iter 8 value 641.257846
#> iter 8 value 641.257844
#> final value 641.257844
#> converged
#> This is Run number 24
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.26938799 -0.4237315 -2.030612 -13.023732 1
#> 2 1 -0.35 -14.40 -0.17217104 -1.0201653 -0.522171 -15.420165 1
#> 3 1 -12.20 -2.55 -0.34061799 1.5216206 -12.540618 -1.028379 2
#> 4 1 -2.30 -13.70 -0.09067659 1.0272951 -2.390677 -12.672705 1
#> 5 1 -12.60 -7.80 -0.37951390 1.2350744 -12.979514 -6.564926 2
#> 6 1 -7.60 -12.40 4.00534982 1.7600741 -3.594650 -10.639926 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5220 -69575 14150
#> initial value 998.131940
#> iter 2 value 697.528009
#> iter 3 value 697.127420
#> iter 4 value 697.123321
#> iter 5 value 680.026367
#> iter 6 value 678.446714
#> iter 7 value 678.420082
#> iter 8 value 678.420016
#> iter 8 value 678.420016
#> final value 678.420016
#> converged
#> This is Run number 25
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.01806578 -1.234873537 -4.281934 -13.834874 1
#> 2 1 -0.35 -14.40 4.17930226 -0.630747058 3.829302 -15.030747 1
#> 3 1 -12.20 -2.55 1.91346215 -0.005308368 -10.286538 -2.555308 2
#> 4 1 -2.30 -13.70 -1.27694655 -0.877013116 -3.576947 -14.577013 1
#> 5 1 -12.60 -7.80 -0.31410290 0.474187073 -12.914103 -7.325813 2
#> 6 1 -7.60 -12.40 0.05080539 -0.422265938 -7.549195 -12.822266 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4760 -74500 15375
#> initial value 998.131940
#> iter 2 value 651.601264
#> iter 3 value 651.551168
#> iter 4 value 651.522387
#> iter 5 value 628.483047
#> iter 6 value 625.530776
#> iter 7 value 625.441325
#> iter 8 value 625.440588
#> iter 8 value 625.440583
#> final value 625.440583
#> converged
#> This is Run number 26
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.26690882 1.49259340 -4.566908816 -11.107407 1
#> 2 1 -0.35 -14.40 0.35160079 3.23083885 0.001600788 -11.169161 1
#> 3 1 -12.20 -2.55 1.38149956 -0.01289101 -10.818500437 -2.562891 2
#> 4 1 -2.30 -13.70 -0.03692617 1.26380435 -2.336926174 -12.436196 1
#> 5 1 -12.60 -7.80 -1.39707851 0.34309113 -13.997078513 -7.456909 2
#> 6 1 -7.60 -12.40 2.98523917 -0.97068829 -4.614760832 -13.370688 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5200 -75175 13450
#> initial value 998.131940
#> iter 2 value 648.423641
#> iter 3 value 648.033239
#> iter 4 value 648.013826
#> iter 5 value 624.740868
#> iter 6 value 621.825889
#> iter 7 value 621.742801
#> iter 8 value 621.742302
#> iter 8 value 621.742299
#> final value 621.742299
#> converged
#> This is Run number 27
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.3471397 1.70894768 -3.9528603 -10.891052 1
#> 2 1 -0.35 -14.40 -0.5608906 0.54205132 -0.9108906 -13.857949 1
#> 3 1 -12.20 -2.55 -0.5985341 -0.86361320 -12.7985341 -3.413613 2
#> 4 1 -2.30 -13.70 0.0603011 0.50308605 -2.2396989 -13.196914 1
#> 5 1 -12.60 -7.80 -1.0304791 -0.02385136 -13.6304791 -7.823851 2
#> 6 1 -7.60 -12.40 0.9115701 -0.44636904 -6.6884299 -12.846369 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4920 -73475 14675
#> initial value 998.131940
#> iter 2 value 662.256993
#> iter 3 value 662.255870
#> iter 4 value 662.254879
#> iter 5 value 640.476893
#> iter 6 value 638.258820
#> iter 7 value 638.201059
#> iter 8 value 638.200743
#> iter 8 value 638.200740
#> final value 638.200740
#> converged
#> This is Run number 28
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 4.0992171 -0.43778397 -0.2007829 -13.037784 1
#> 2 1 -0.35 -14.40 -0.2753681 -0.11019764 -0.6253681 -14.510198 1
#> 3 1 -12.20 -2.55 2.3531010 -1.22928841 -9.8468990 -3.779288 2
#> 4 1 -2.30 -13.70 -0.8868808 0.66318193 -3.1868808 -13.036818 1
#> 5 1 -12.60 -7.80 -1.2567054 0.57193421 -13.8567054 -7.228066 2
#> 6 1 -7.60 -12.40 2.9528358 -0.03420792 -4.6471642 -12.434208 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5280 -77625 16350
#> initial value 998.131940
#> iter 2 value 619.626378
#> iter 3 value 619.511899
#> iter 4 value 619.486732
#> iter 5 value 591.821170
#> iter 6 value 587.608011
#> iter 7 value 587.438668
#> iter 8 value 587.436730
#> iter 9 value 587.436714
#> iter 9 value 587.436710
#> iter 9 value 587.436709
#> final value 587.436709
#> converged
#> This is Run number 29
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.2163777 1.6514653 -4.5163777 -10.948535 1
#> 2 1 -0.35 -14.40 0.1611594 0.7815301 -0.1888406 -13.618470 1
#> 3 1 -12.20 -2.55 0.5042880 0.2227413 -11.6957120 -2.327259 2
#> 4 1 -2.30 -13.70 1.9292716 -1.5163572 -0.3707284 -15.216357 1
#> 5 1 -12.60 -7.80 1.7341392 -0.4185978 -10.8658608 -8.218598 2
#> 6 1 -7.60 -12.40 0.6926779 0.5949528 -6.9073221 -11.805047 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4800 -73275 15050
#> initial value 998.131940
#> iter 2 value 663.456233
#> iter 3 value 663.433599
#> iter 4 value 663.428854
#> iter 5 value 641.962332
#> iter 6 value 639.517667
#> iter 7 value 639.453484
#> iter 8 value 639.453085
#> iter 8 value 639.453082
#> final value 639.453082
#> converged
#> This is Run number 30
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.0559991 -0.56522529 -3.2440009 -13.165225 1
#> 2 1 -0.35 -14.40 -0.1660974 -0.14743160 -0.5160974 -14.547432 1
#> 3 1 -12.20 -2.55 1.0301346 -0.61288513 -11.1698654 -3.162885 2
#> 4 1 -2.30 -13.70 -0.4879584 -0.06506244 -2.7879584 -13.765062 1
#> 5 1 -12.60 -7.80 -1.5163743 0.72016879 -14.1163743 -7.079831 2
#> 6 1 -7.60 -12.40 2.9578226 4.38701521 -4.6421774 -8.012985 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4200 -72425 15025
#> initial value 998.131940
#> iter 2 value 671.505476
#> iter 3 value 671.310447
#> iter 4 value 671.216207
#> iter 5 value 650.427567
#> iter 6 value 648.007397
#> iter 7 value 647.941724
#> iter 8 value 647.941200
#> iter 8 value 647.941197
#> final value 647.941197
#> converged
#> This is Run number 31
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.2831872 0.2699589 -3.0168128 -12.330041 1
#> 2 1 -0.35 -14.40 -0.5160231 0.1316440 -0.8660231 -14.268356 1
#> 3 1 -12.20 -2.55 0.3643910 0.1904049 -11.8356090 -2.359595 2
#> 4 1 -2.30 -13.70 2.1578455 -0.5773831 -0.1421545 -14.277383 1
#> 5 1 -12.60 -7.80 1.0714669 -0.9323047 -11.5285331 -8.732305 2
#> 6 1 -7.60 -12.40 -0.4672801 0.7514636 -8.0672801 -11.648536 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4380 -71125 14225
#> initial value 998.131940
#> iter 2 value 684.433232
#> iter 3 value 684.225228
#> iter 4 value 684.224994
#> iter 5 value 665.157527
#> iter 6 value 663.466995
#> iter 7 value 663.429935
#> iter 8 value 663.429753
#> iter 8 value 663.429751
#> final value 663.429751
#> converged
#> This is Run number 32
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.9123573 -0.5095972 -5.2123573 -13.109597 1
#> 2 1 -0.35 -14.40 0.4528003 2.5019504 0.1028003 -11.898050 1
#> 3 1 -12.20 -2.55 -0.2428971 0.5511229 -12.4428971 -1.998877 2
#> 4 1 -2.30 -13.70 -1.8560739 0.1264995 -4.1560739 -13.573501 1
#> 5 1 -12.60 -7.80 0.6634495 2.5468569 -11.9365505 -5.253143 2
#> 6 1 -7.60 -12.40 1.9387815 -0.3583180 -5.6612185 -12.758318 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4920 -71725 14250
#> initial value 998.131940
#> iter 2 value 678.779961
#> iter 3 value 678.773838
#> iter 4 value 678.770119
#> iter 5 value 659.370919
#> iter 6 value 657.417616
#> iter 7 value 657.375967
#> iter 8 value 657.375797
#> iter 8 value 657.375796
#> final value 657.375796
#> converged
#> This is Run number 33
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.45762560 0.5683258 -3.8423744 -12.031674 1
#> 2 1 -0.35 -14.40 -0.49563518 -1.6690809 -0.8456352 -16.069081 1
#> 3 1 -12.20 -2.55 -0.28739986 1.4181748 -12.4873999 -1.131825 2
#> 4 1 -2.30 -13.70 0.04649887 1.1879504 -2.2535011 -12.512050 1
#> 5 1 -12.60 -7.80 -0.76801833 -0.1410116 -13.3680183 -7.941012 2
#> 6 1 -7.60 -12.40 -0.22969427 -0.8844691 -7.8296943 -13.284469 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4400 -71650 15600
#> initial value 998.131940
#> iter 2 value 677.202474
#> iter 3 value 676.955898
#> iter 4 value 676.920643
#> iter 5 value 657.067798
#> iter 6 value 654.842491
#> iter 7 value 654.788293
#> iter 8 value 654.787952
#> iter 8 value 654.787950
#> final value 654.787950
#> converged
#> This is Run number 34
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.99834159 0.3371204 -3.3016584 -12.262880 1
#> 2 1 -0.35 -14.40 -0.22370613 -0.5692984 -0.5737061 -14.969298 1
#> 3 1 -12.20 -2.55 1.21083651 -0.2881133 -10.9891635 -2.838113 2
#> 4 1 -2.30 -13.70 3.04659568 1.3545334 0.7465957 -12.345467 1
#> 5 1 -12.60 -7.80 0.08644764 -1.0738525 -12.5135524 -8.873852 2
#> 6 1 -7.60 -12.40 -0.03290724 2.2836365 -7.6329072 -10.116363 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4840 -69850 14250
#> initial value 998.131940
#> iter 2 value 695.234087
#> iter 3 value 695.216163
#> iter 4 value 695.202950
#> iter 5 value 677.820134
#> iter 6 value 676.169913
#> iter 7 value 676.140548
#> iter 8 value 676.140457
#> iter 8 value 676.140456
#> final value 676.140456
#> converged
#> This is Run number 35
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.29873229 0.4333447 -3.0012677 -12.166655 1
#> 2 1 -0.35 -14.40 0.58713568 2.4276764 0.2371357 -11.972324 1
#> 3 1 -12.20 -2.55 0.26436933 -0.7934203 -11.9356307 -3.343420 2
#> 4 1 -2.30 -13.70 0.65235117 -0.4364213 -1.6476488 -14.136421 1
#> 5 1 -12.60 -7.80 1.79511444 0.9387943 -10.8048856 -6.861206 2
#> 6 1 -7.60 -12.40 0.07574261 0.5559699 -7.5242574 -11.844030 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4440 -70875 14325
#> initial value 998.131940
#> iter 2 value 686.421123
#> iter 3 value 686.344351
#> iter 4 value 686.316087
#> iter 5 value 667.784027
#> iter 6 value 665.873109
#> iter 7 value 665.833413
#> iter 8 value 665.833216
#> iter 8 value 665.833215
#> final value 665.833215
#> converged
#> This is Run number 36
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.1020781 -0.1194992 -4.19792191 -12.719499 1
#> 2 1 -0.35 -14.40 0.3300795 3.5456426 -0.01992053 -10.854357 1
#> 3 1 -12.20 -2.55 0.1430231 0.2658064 -12.05697689 -2.284194 2
#> 4 1 -2.30 -13.70 0.4427922 -0.2618696 -1.85720779 -13.961870 1
#> 5 1 -12.60 -7.80 1.8007270 0.4680276 -10.79927303 -7.331972 2
#> 6 1 -7.60 -12.40 1.6481143 0.8513325 -5.95188566 -11.548667 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4940 -72600 13875
#> initial value 998.131940
#> iter 2 value 671.582633
#> iter 3 value 671.510956
#> iter 4 value 671.506946
#> iter 5 value 651.221032
#> iter 6 value 649.087834
#> iter 7 value 649.038965
#> iter 8 value 649.038744
#> iter 8 value 649.038742
#> final value 649.038742
#> converged
#> This is Run number 37
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.35257563 0.7233672 -1.9474244 -11.8766328 1
#> 2 1 -0.35 -14.40 -0.37197321 0.1344885 -0.7219732 -14.2655115 1
#> 3 1 -12.20 -2.55 0.64030029 1.6434133 -11.5596997 -0.9065867 2
#> 4 1 -2.30 -13.70 0.03417973 0.9079870 -2.2658203 -12.7920130 1
#> 5 1 -12.60 -7.80 -0.41344794 -0.2750187 -13.0134479 -8.0750187 2
#> 6 1 -7.60 -12.40 2.23561829 0.4953253 -5.3643817 -11.9046747 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4320 -72125 13475
#> initial value 998.131940
#> iter 2 value 676.849644
#> iter 3 value 676.530975
#> iter 4 value 676.281642
#> iter 5 value 656.337204
#> iter 6 value 654.153325
#> iter 7 value 654.102380
#> iter 8 value 654.102067
#> iter 8 value 654.102065
#> final value 654.102065
#> converged
#> This is Run number 38
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.46834797 1.2459834 -3.8316520 -11.354017 1
#> 2 1 -0.35 -14.40 -0.50948329 1.6242082 -0.8594833 -12.775792 1
#> 3 1 -12.20 -2.55 -0.80171746 -0.2966299 -13.0017175 -2.846630 2
#> 4 1 -2.30 -13.70 -1.03458194 1.6721107 -3.3345819 -12.027889 1
#> 5 1 -12.60 -7.80 1.87808227 -1.1317741 -10.7219177 -8.931774 2
#> 6 1 -7.60 -12.40 0.01683582 -0.3813714 -7.5831642 -12.781371 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4700 -71050 15350
#> initial value 998.131940
#> iter 2 value 682.827296
#> iter 3 value 682.660266
#> iter 4 value 682.649593
#> iter 5 value 663.606226
#> iter 6 value 661.616664
#> iter 7 value 661.573608
#> iter 8 value 661.573409
#> iter 8 value 661.573408
#> final value 661.573408
#> converged
#> This is Run number 39
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.9217939 -0.3454955 -3.378206 -12.945495 1
#> 2 1 -0.35 -14.40 2.1223582 -0.1858888 1.772358 -14.585889 1
#> 3 1 -12.20 -2.55 -0.2379937 -0.2385891 -12.437994 -2.788589 2
#> 4 1 -2.30 -13.70 -0.0643311 -0.1876371 -2.364331 -13.887637 1
#> 5 1 -12.60 -7.80 0.8882532 -0.3728214 -11.711747 -8.172821 2
#> 6 1 -7.60 -12.40 1.5584833 2.6476753 -6.041517 -9.752325 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4480 -72375 13875
#> initial value 998.131940
#> iter 2 value 673.869024
#> iter 3 value 673.718277
#> iter 4 value 673.619526
#> iter 5 value 653.437327
#> iter 6 value 651.195581
#> iter 7 value 651.142772
#> iter 8 value 651.142458
#> iter 8 value 651.142456
#> final value 651.142456
#> converged
#> This is Run number 40
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.4559201 -0.5314222 -5.755920 -13.131422 1
#> 2 1 -0.35 -14.40 2.3581228 -0.6777979 2.008123 -15.077798 1
#> 3 1 -12.20 -2.55 -0.8550778 -0.9196064 -13.055078 -3.469606 2
#> 4 1 -2.30 -13.70 -1.2034462 0.8256517 -3.503446 -12.874348 1
#> 5 1 -12.60 -7.80 3.3274605 1.6136888 -9.272539 -6.186311 2
#> 6 1 -7.60 -12.40 -0.6958261 -0.8595749 -8.295826 -13.259575 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4920 -71625 13600
#> initial value 998.131940
#> iter 2 value 680.770405
#> iter 3 value 680.679348
#> iter 4 value 680.678276
#> iter 5 value 661.305300
#> iter 6 value 659.665550
#> iter 7 value 659.631472
#> iter 8 value 659.631355
#> iter 8 value 659.631354
#> final value 659.631354
#> converged
#> This is Run number 41
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.5006194 2.0397986 -1.7993806 -10.560201 1
#> 2 1 -0.35 -14.40 -0.1151263 -0.5379216 -0.4651263 -14.937922 1
#> 3 1 -12.20 -2.55 -0.2861677 -0.3062905 -12.4861677 -2.856290 2
#> 4 1 -2.30 -13.70 3.3502749 0.7072410 1.0502749 -12.992759 1
#> 5 1 -12.60 -7.80 0.5683409 3.6294642 -12.0316591 -4.170536 2
#> 6 1 -7.60 -12.40 1.4085514 1.0595375 -6.1914486 -11.340462 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4680 -73025 14475
#> initial value 998.131940
#> iter 2 value 666.853585
#> iter 3 value 666.795888
#> iter 4 value 666.773640
#> iter 5 value 645.844021
#> iter 6 value 643.419202
#> iter 7 value 643.357679
#> iter 8 value 643.357299
#> iter 8 value 643.357296
#> final value 643.357296
#> converged
#> This is Run number 42
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.46835192 -0.30822848 -3.8316481 -12.9082285 1
#> 2 1 -0.35 -14.40 1.12145867 -0.92961895 0.7714587 -15.3296190 1
#> 3 1 -12.20 -2.55 0.55238903 2.11688084 -11.6476110 -0.4331192 2
#> 4 1 -2.30 -13.70 0.08291128 -0.07514927 -2.2170887 -13.7751493 1
#> 5 1 -12.60 -7.80 2.23194385 1.23483176 -10.3680562 -6.5651682 2
#> 6 1 -7.60 -12.40 0.98144657 0.90475115 -6.6185534 -11.4952489 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4660 -71475 14775
#> initial value 998.131940
#> iter 2 value 680.202315
#> iter 3 value 680.172803
#> iter 4 value 680.168370
#> iter 5 value 660.840411
#> iter 6 value 658.858748
#> iter 7 value 658.815054
#> iter 8 value 658.814843
#> iter 8 value 658.814842
#> final value 658.814842
#> converged
#> This is Run number 43
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.51220581 -0.7417049 -3.78779419 -13.341705 1
#> 2 1 -0.35 -14.40 0.38176998 -0.2630988 0.03176998 -14.663099 1
#> 3 1 -12.20 -2.55 0.54110366 -0.4513020 -11.65889634 -3.001302 2
#> 4 1 -2.30 -13.70 -0.35580892 -0.9791653 -2.65580892 -14.679165 1
#> 5 1 -12.60 -7.80 -0.05032185 1.8880742 -12.65032185 -5.911926 2
#> 6 1 -7.60 -12.40 0.01481295 0.9773041 -7.58518705 -11.422696 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4740 -76475 13775
#> initial value 998.131940
#> iter 2 value 635.855116
#> iter 3 value 635.357729
#> iter 4 value 634.986981
#> iter 5 value 609.654069
#> iter 6 value 606.095453
#> iter 7 value 605.971057
#> iter 8 value 605.969799
#> iter 9 value 605.969789
#> iter 9 value 605.969784
#> iter 9 value 605.969784
#> final value 605.969784
#> converged
#> This is Run number 44
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.4859882 1.320240701 -4.785988 -11.279759 1
#> 2 1 -0.35 -14.40 1.9775223 -0.009601275 1.627522 -14.409601 1
#> 3 1 -12.20 -2.55 1.1135257 -0.568196113 -11.086474 -3.118196 2
#> 4 1 -2.30 -13.70 1.2017421 1.193584311 -1.098258 -12.506416 1
#> 5 1 -12.60 -7.80 -0.5084480 -0.521158662 -13.108448 -8.321159 2
#> 6 1 -7.60 -12.40 0.1716515 1.083918377 -7.428348 -11.316082 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4760 -72475 14250
#> initial value 998.131940
#> iter 2 value 672.172536
#> iter 3 value 672.150192
#> iter 4 value 672.130790
#> iter 5 value 651.935222
#> iter 6 value 649.698687
#> iter 7 value 649.646521
#> iter 8 value 649.646248
#> iter 8 value 649.646246
#> final value 649.646246
#> converged
#> This is Run number 45
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.2607447 1.33416310 -4.5607447 -11.265837 1
#> 2 1 -0.35 -14.40 1.0261053 -0.56396839 0.6761053 -14.963968 1
#> 3 1 -12.20 -2.55 -0.1135404 0.35321921 -12.3135404 -2.196781 2
#> 4 1 -2.30 -13.70 -0.8755173 1.17789863 -3.1755173 -12.522101 1
#> 5 1 -12.60 -7.80 1.5841029 -0.06931979 -11.0158971 -7.869320 2
#> 6 1 -7.60 -12.40 0.5384327 0.43567732 -7.0615673 -11.964323 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5160 -74075 15225
#> initial value 998.131940
#> iter 2 value 655.573826
#> iter 3 value 655.534959
#> iter 4 value 655.500044
#> iter 5 value 633.132400
#> iter 6 value 630.387856
#> iter 7 value 630.312368
#> iter 8 value 630.311907
#> iter 8 value 630.311905
#> final value 630.311905
#> converged
#> This is Run number 46
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.2373443 -0.1743745 -4.5373443 -12.774375 1
#> 2 1 -0.35 -14.40 -0.5347819 -0.1085134 -0.8847819 -14.508513 1
#> 3 1 -12.20 -2.55 -0.6454785 0.5069905 -12.8454785 -2.043010 2
#> 4 1 -2.30 -13.70 -1.1417449 1.0705089 -3.4417449 -12.629491 1
#> 5 1 -12.60 -7.80 1.8318904 -0.2720847 -10.7681096 -8.072085 2
#> 6 1 -7.60 -12.40 -1.0654629 -0.3336993 -8.6654629 -12.733699 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4320 -72500 14800
#> initial value 998.131940
#> iter 2 value 671.194399
#> iter 3 value 671.114135
#> iter 4 value 671.012369
#> iter 5 value 650.292521
#> iter 6 value 647.913642
#> iter 7 value 647.852849
#> iter 8 value 647.852395
#> iter 8 value 647.852391
#> final value 647.852391
#> converged
#> This is Run number 47
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.87610462 0.3319354 -5.176105 -12.268065 1
#> 2 1 -0.35 -14.40 1.72666729 -1.6132784 1.376667 -16.013278 1
#> 3 1 -12.20 -2.55 -0.06839598 0.6536494 -12.268396 -1.896351 2
#> 4 1 -2.30 -13.70 1.14665864 0.5025057 -1.153341 -13.197494 1
#> 5 1 -12.60 -7.80 -0.43546123 0.2364152 -13.035461 -7.563585 2
#> 6 1 -7.60 -12.40 -0.49865891 -1.0242610 -8.098659 -13.424261 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4420 -71125 14025
#> initial value 998.131940
#> iter 2 value 684.759893
#> iter 3 value 684.634716
#> iter 4 value 684.583667
#> iter 5 value 665.839678
#> iter 6 value 663.888256
#> iter 7 value 663.846518
#> iter 8 value 663.846309
#> iter 8 value 663.846308
#> final value 663.846308
#> converged
#> This is Run number 48
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.03364587 -0.3408331 -4.3336459 -12.9408331 1
#> 2 1 -0.35 -14.40 -0.28965539 -1.0117259 -0.6396554 -15.4117259 1
#> 3 1 -12.20 -2.55 0.06361234 1.8055141 -12.1363877 -0.7444859 2
#> 4 1 -2.30 -13.70 0.22169461 -0.1373610 -2.0783054 -13.8373610 1
#> 5 1 -12.60 -7.80 -0.18706121 1.5502158 -12.7870612 -6.2497842 2
#> 6 1 -7.60 -12.40 -0.47967196 0.3569597 -8.0796720 -12.0430403 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4820 -70775 13300
#> initial value 998.131940
#> iter 2 value 688.807449
#> iter 3 value 688.681583
#> iter 4 value 688.673789
#> iter 5 value 670.567383
#> iter 6 value 668.821235
#> iter 7 value 668.788247
#> iter 8 value 668.788136
#> iter 8 value 668.788135
#> final value 668.788135
#> converged
#> This is Run number 49
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.66200178 -1.64477446 -4.9620018 -14.244774 1
#> 2 1 -0.35 -14.40 0.11748422 0.70570941 -0.2325158 -13.694291 1
#> 3 1 -12.20 -2.55 -1.19614869 1.25600586 -13.3961487 -1.293994 2
#> 4 1 -2.30 -13.70 0.08327724 0.52147248 -2.2167228 -13.178528 1
#> 5 1 -12.60 -7.80 -0.00359192 0.08062541 -12.6035919 -7.719375 2
#> 6 1 -7.60 -12.40 0.42927130 2.13200380 -7.1707287 -10.267996 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4780 -73850 14950
#> initial value 998.131940
#> iter 2 value 658.398736
#> iter 3 value 658.381620
#> iter 4 value 658.371923
#> iter 5 value 636.303271
#> iter 6 value 633.616891
#> iter 7 value 633.542247
#> iter 8 value 633.541720
#> iter 8 value 633.541717
#> final value 633.541717
#> converged
#> This is Run number 50
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.9461617 0.9494711 -3.353838 -11.65053 1
#> 2 1 -0.35 -14.40 3.2769910 -0.7390514 2.926991 -15.13905 1
#> 3 1 -12.20 -2.55 2.5491906 -0.3204796 -9.650809 -2.87048 2
#> 4 1 -2.30 -13.70 -1.2026552 2.9910474 -3.502655 -10.70895 1
#> 5 1 -12.60 -7.80 2.6395958 1.6750295 -9.960404 -6.12497 2
#> 6 1 -7.60 -12.40 4.4930736 1.4149575 -3.106926 -10.98504 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5240 -73250 14150
#> initial value 998.131940
#> iter 2 value 665.034088
#> iter 3 value 664.965244
#> iter 4 value 664.930085
#> iter 5 value 643.936880
#> iter 6 value 641.547679
#> iter 7 value 641.490804
#> iter 8 value 641.490548
#> iter 8 value 641.490547
#> final value 641.490547
#> converged
#> This is Run number 51
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.1366384 -0.7902318 -4.436638 -13.390232 1
#> 2 1 -0.35 -14.40 -1.2978301 -1.0512555 -1.647830 -15.451255 1
#> 3 1 -12.20 -2.55 1.0258595 0.7855134 -11.174140 -1.764487 2
#> 4 1 -2.30 -13.70 -1.4420343 -0.3982767 -3.742034 -14.098277 1
#> 5 1 -12.60 -7.80 0.8454796 0.5839691 -11.754520 -7.216031 2
#> 6 1 -7.60 -12.40 0.9259096 0.1795666 -6.674090 -12.220433 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5540 -73800 13975
#> initial value 998.131940
#> iter 2 value 660.094604
#> iter 3 value 659.899748
#> iter 4 value 659.763638
#> iter 5 value 638.148631
#> iter 6 value 635.626190
#> iter 7 value 635.564684
#> iter 8 value 635.564426
#> iter 8 value 635.564425
#> final value 635.564425
#> converged
#> This is Run number 52
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.004782451 0.3305092 -4.3047825 -12.269491 1
#> 2 1 -0.35 -14.40 0.792989726 2.4822266 0.4429897 -11.917773 1
#> 3 1 -12.20 -2.55 2.973108281 0.4226295 -9.2268917 -2.127371 2
#> 4 1 -2.30 -13.70 -0.319135893 -0.4562851 -2.6191359 -14.156285 1
#> 5 1 -12.60 -7.80 -1.747023855 2.5530051 -14.3470239 -5.246995 2
#> 6 1 -7.60 -12.40 -1.061644896 2.6327407 -8.6616449 -9.767259 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5060 -71650 14000
#> initial value 998.131940
#> iter 2 value 679.790903
#> iter 3 value 679.752125
#> iter 4 value 679.729039
#> iter 5 value 660.576413
#> iter 6 value 658.588080
#> iter 7 value 658.547187
#> iter 8 value 658.547037
#> iter 8 value 658.547036
#> final value 658.547036
#> converged
#> This is Run number 53
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.9406410 2.3700374 -2.3593590 -10.229963 1
#> 2 1 -0.35 -14.40 0.9121414 -0.1587098 0.5621414 -14.558710 1
#> 3 1 -12.20 -2.55 -0.2063946 -0.3616148 -12.4063946 -2.911615 2
#> 4 1 -2.30 -13.70 -0.4125045 1.5507723 -2.7125045 -12.149228 1
#> 5 1 -12.60 -7.80 -0.2667149 -0.2675250 -12.8667149 -8.067525 2
#> 6 1 -7.60 -12.40 -0.2322885 -0.1955551 -7.8322885 -12.595555 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3940 -71925 15625
#> initial value 998.131940
#> iter 2 value 674.924554
#> iter 3 value 674.475884
#> iter 4 value 674.117629
#> iter 5 value 653.677637
#> iter 6 value 651.258277
#> iter 7 value 651.191246
#> iter 8 value 651.190661
#> iter 8 value 651.190658
#> final value 651.190658
#> converged
#> This is Run number 54
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.07457869 -0.6296307 -3.2254213 -13.229631 1
#> 2 1 -0.35 -14.40 0.06168772 0.8622029 -0.2883123 -13.537797 1
#> 3 1 -12.20 -2.55 0.93877653 -0.7485346 -11.2612235 -3.298535 2
#> 4 1 -2.30 -13.70 2.82628411 1.1716337 0.5262841 -12.528366 1
#> 5 1 -12.60 -7.80 -0.12321064 1.2981714 -12.7232106 -6.501829 2
#> 6 1 -7.60 -12.40 1.45426052 -0.4980588 -6.1457395 -12.898059 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4880 -73225 14250
#> initial value 998.131940
#> iter 2 value 665.317454
#> iter 3 value 665.284932
#> iter 4 value 665.271265
#> iter 5 value 644.214134
#> iter 6 value 641.806293
#> iter 7 value 641.746436
#> iter 8 value 641.746104
#> iter 8 value 641.746102
#> final value 641.746102
#> converged
#> This is Run number 55
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.9466554 0.1472509 -2.353345 -12.452749 1
#> 2 1 -0.35 -14.40 1.6351147 1.2786102 1.285115 -13.121390 1
#> 3 1 -12.20 -2.55 -0.1199046 -0.4909588 -12.319905 -3.040959 2
#> 4 1 -2.30 -13.70 0.3449496 -0.8653605 -1.955050 -14.565360 1
#> 5 1 -12.60 -7.80 1.7150788 0.6452861 -10.884921 -7.154714 2
#> 6 1 -7.60 -12.40 3.7166215 3.9322191 -3.883379 -8.467781 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4660 -73500 15375
#> initial value 998.131940
#> iter 2 value 660.861429
#> iter 3 value 660.780326
#> iter 4 value 660.752895
#> iter 5 value 638.928353
#> iter 6 value 636.272474
#> iter 7 value 636.198587
#> iter 8 value 636.198044
#> iter 8 value 636.198040
#> final value 636.198040
#> converged
#> This is Run number 56
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.03581406 -1.3280294 -4.2641859 -13.928029 1
#> 2 1 -0.35 -14.40 -0.30704658 1.2664594 -0.6570466 -13.133541 1
#> 3 1 -12.20 -2.55 -0.17279930 -0.4451340 -12.3727993 -2.995134 2
#> 4 1 -2.30 -13.70 0.37750516 0.7270787 -1.9224948 -12.972921 1
#> 5 1 -12.60 -7.80 -0.97694996 0.6623929 -13.5769500 -7.137607 2
#> 6 1 -7.60 -12.40 0.68843941 0.4618834 -6.9115606 -11.938117 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4660 -70000 15675
#> initial value 998.131940
#> iter 2 value 691.339459
#> iter 3 value 690.967815
#> iter 4 value 690.919405
#> iter 5 value 672.822750
#> iter 6 value 670.988877
#> iter 7 value 670.952108
#> iter 8 value 670.951958
#> iter 8 value 670.951957
#> final value 670.951957
#> converged
#> This is Run number 57
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.1486709 1.79302603 -4.1513291 -10.806974 1
#> 2 1 -0.35 -14.40 -0.4788542 1.63269544 -0.8288542 -12.767305 1
#> 3 1 -12.20 -2.55 0.6498560 0.64113201 -11.5501440 -1.908868 2
#> 4 1 -2.30 -13.70 0.8953531 -0.01737112 -1.4046469 -13.717371 1
#> 5 1 -12.60 -7.80 -1.1827508 0.02559926 -13.7827508 -7.774401 2
#> 6 1 -7.60 -12.40 -0.8068423 0.24680996 -8.4068423 -12.153190 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4800 -69925 14250
#> initial value 998.131940
#> iter 2 value 694.611699
#> iter 3 value 694.600323
#> iter 4 value 694.592869
#> iter 5 value 677.130856
#> iter 6 value 675.473538
#> iter 7 value 675.443426
#> iter 8 value 675.443326
#> iter 8 value 675.443326
#> final value 675.443326
#> converged
#> This is Run number 58
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.1433126 -0.7915781 -5.443313 -13.391578 1
#> 2 1 -0.35 -14.40 1.7730610 -0.2048416 1.423061 -14.604842 1
#> 3 1 -12.20 -2.55 -0.6414468 -0.3210028 -12.841447 -2.871003 2
#> 4 1 -2.30 -13.70 0.6008224 -0.2651426 -1.699178 -13.965143 1
#> 5 1 -12.60 -7.80 1.4162743 2.6005108 -11.183726 -5.199489 2
#> 6 1 -7.60 -12.40 0.8210613 -1.3600193 -6.778939 -13.760019 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4840 -69925 13450
#> initial value 998.131940
#> iter 2 value 695.944569
#> iter 3 value 695.886986
#> iter 4 value 695.885806
#> iter 5 value 678.418221
#> iter 6 value 677.041024
#> iter 7 value 677.016924
#> iter 8 value 677.016860
#> iter 8 value 677.016859
#> final value 677.016859
#> converged
#> This is Run number 59
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.1624243 1.7666755 -4.1375757 -10.833324 1
#> 2 1 -0.35 -14.40 0.7020426 4.6224300 0.3520426 -9.777570 1
#> 3 1 -12.20 -2.55 0.5727292 1.3787752 -11.6272708 -1.171225 2
#> 4 1 -2.30 -13.70 0.9608171 0.1793189 -1.3391829 -13.520681 1
#> 5 1 -12.60 -7.80 0.8761813 -0.3138276 -11.7238187 -8.113828 2
#> 6 1 -7.60 -12.40 1.3450602 -0.7019151 -6.2549398 -13.101915 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4420 -74125 15800
#> initial value 998.131940
#> iter 2 value 654.411042
#> iter 3 value 654.183571
#> iter 4 value 654.044455
#> iter 5 value 631.160127
#> iter 6 value 628.175871
#> iter 7 value 628.081322
#> iter 8 value 628.080403
#> iter 8 value 628.080397
#> final value 628.080397
#> converged
#> This is Run number 60
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.1391067 0.80214857 -4.4391067 -11.797851 1
#> 2 1 -0.35 -14.40 0.7489255 -0.51899718 0.3989255 -14.918997 1
#> 3 1 -12.20 -2.55 0.8034251 -0.01325533 -11.3965749 -2.563255 2
#> 4 1 -2.30 -13.70 1.6599129 2.40850323 -0.6400871 -11.291497 1
#> 5 1 -12.60 -7.80 -0.3124362 1.32485224 -12.9124362 -6.475148 2
#> 6 1 -7.60 -12.40 1.3075876 2.35626833 -6.2924124 -10.043732 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5640 -70725 12650
#> initial value 998.131940
#> iter 2 value 689.681706
#> iter 3 value 689.109612
#> iter 4 value 688.822945
#> iter 5 value 670.861586
#> iter 6 value 669.136880
#> iter 7 value 669.106722
#> iter 8 value 669.106657
#> iter 8 value 669.106657
#> final value 669.106657
#> converged
#> This is Run number 61
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.07651337 -0.889713724 -3.223487 -13.489714 1
#> 2 1 -0.35 -14.40 -1.13879418 3.237301097 -1.488794 -11.162699 1
#> 3 1 -12.20 -2.55 -0.27045752 0.006804569 -12.470458 -2.543195 2
#> 4 1 -2.30 -13.70 0.05403065 1.909160591 -2.245969 -11.790839 1
#> 5 1 -12.60 -7.80 -2.36462244 0.496687539 -14.964622 -7.303312 2
#> 6 1 -7.60 -12.40 0.58585966 -0.491491582 -7.014140 -12.891492 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4760 -74550 15225
#> initial value 998.131940
#> iter 2 value 651.426322
#> iter 3 value 651.389959
#> iter 4 value 651.357222
#> iter 5 value 628.311659
#> iter 6 value 625.357119
#> iter 7 value 625.267687
#> iter 8 value 625.266950
#> iter 8 value 625.266944
#> final value 625.266944
#> converged
#> This is Run number 62
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.9544663 2.71265727 -3.34553370 -9.887343 1
#> 2 1 -0.35 -14.40 0.2880513 0.84690403 -0.06194869 -13.553096 1
#> 3 1 -12.20 -2.55 0.1154849 0.08398573 -12.08451510 -2.466014 2
#> 4 1 -2.30 -13.70 0.3978235 0.71434606 -1.90217649 -12.985654 1
#> 5 1 -12.60 -7.80 0.6173740 2.11930783 -11.98262595 -5.680692 2
#> 6 1 -7.60 -12.40 -1.1590327 0.88607023 -8.75903273 -11.513930 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5100 -72750 15800
#> initial value 998.131940
#> iter 2 value 666.555335
#> iter 3 value 666.297484
#> iter 4 value 666.159072
#> iter 5 value 645.091787
#> iter 6 value 642.627262
#> iter 7 value 642.565156
#> iter 8 value 642.564825
#> iter 8 value 642.564823
#> final value 642.564823
#> converged
#> This is Run number 63
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.09267736 0.85127948 -4.3926774 -11.748721 1
#> 2 1 -0.35 -14.40 -0.16050357 2.37154774 -0.5105036 -12.028452 1
#> 3 1 -12.20 -2.55 0.04630562 -0.27128212 -12.1536944 -2.821282 2
#> 4 1 -2.30 -13.70 -0.06047967 0.80276767 -2.3604797 -12.897232 1
#> 5 1 -12.60 -7.80 -0.05377888 -0.42701485 -12.6537789 -8.227015 2
#> 6 1 -7.60 -12.40 2.24896521 0.08128666 -5.3510348 -12.318713 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3980 -73075 15400
#> initial value 998.131940
#> iter 2 value 665.015110
#> iter 3 value 664.626356
#> iter 4 value 664.369312
#> iter 5 value 642.402279
#> iter 6 value 639.678095
#> iter 7 value 639.592969
#> iter 8 value 639.592089
#> iter 8 value 639.592084
#> final value 639.592084
#> converged
#> This is Run number 64
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.1217177 1.8173802 -4.1782823 -10.782620 1
#> 2 1 -0.35 -14.40 0.0287250 -0.3783157 -0.3212750 -14.778316 1
#> 3 1 -12.20 -2.55 -0.8346982 -0.5156240 -13.0346982 -3.065624 2
#> 4 1 -2.30 -13.70 1.3268614 -1.3559969 -0.9731386 -15.055997 1
#> 5 1 -12.60 -7.80 -1.0227456 2.7779935 -13.6227456 -5.022007 2
#> 6 1 -7.60 -12.40 -0.7960357 -0.1198505 -8.3960357 -12.519851 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4860 -71525 14825
#> initial value 998.131940
#> iter 2 value 679.549729
#> iter 3 value 679.515135
#> iter 4 value 679.501318
#> iter 5 value 660.191587
#> iter 6 value 658.156783
#> iter 7 value 658.112790
#> iter 8 value 658.112596
#> iter 8 value 658.112595
#> final value 658.112595
#> converged
#> This is Run number 65
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.409162009 -0.2175019 -4.7091620 -12.817502 1
#> 2 1 -0.35 -14.40 0.670733128 1.3416881 0.3207331 -13.058312 1
#> 3 1 -12.20 -2.55 -0.613934165 0.2951767 -12.8139342 -2.254823 2
#> 4 1 -2.30 -13.70 0.007057131 0.2269132 -2.2929429 -13.473087 1
#> 5 1 -12.60 -7.80 -0.909001010 -0.2126393 -13.5090010 -8.012639 2
#> 6 1 -7.60 -12.40 -1.820283343 -0.2053892 -9.4202833 -12.605389 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4920 -72050 14750
#> initial value 998.131940
#> iter 2 value 674.985772
#> iter 3 value 674.969624
#> iter 4 value 674.958166
#> iter 5 value 655.101470
#> iter 6 value 652.960568
#> iter 7 value 652.912295
#> iter 8 value 652.912072
#> iter 8 value 652.912070
#> final value 652.912070
#> converged
#> This is Run number 66
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.32743620 1.1446541 -5.6274362 -11.4553459 1
#> 2 1 -0.35 -14.40 -0.23538842 -0.3977565 -0.5853884 -14.7977565 1
#> 3 1 -12.20 -2.55 -0.69341427 1.7801421 -12.8934143 -0.7698579 2
#> 4 1 -2.30 -13.70 1.62303433 0.3923220 -0.6769657 -13.3076780 1
#> 5 1 -12.60 -7.80 -0.03539243 -0.5604174 -12.6353924 -8.3604174 2
#> 6 1 -7.60 -12.40 -0.12105675 1.6426279 -7.7210568 -10.7573721 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5620 -74125 15350
#> initial value 998.131940
#> iter 2 value 654.549229
#> iter 3 value 654.189603
#> iter 4 value 654.019444
#> iter 5 value 631.374462
#> iter 6 value 628.613355
#> iter 7 value 628.539409
#> iter 8 value 628.539012
#> iter 8 value 628.539009
#> final value 628.539009
#> converged
#> This is Run number 67
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.0961397 -0.1317027 -5.3961397 -12.731703 1
#> 2 1 -0.35 -14.40 -0.3274696 1.0351243 -0.6774696 -13.364876 1
#> 3 1 -12.20 -2.55 0.7533956 -0.3352148 -11.4466044 -2.885215 2
#> 4 1 -2.30 -13.70 -0.6473130 1.4536338 -2.9473130 -12.246366 1
#> 5 1 -12.60 -7.80 4.1163643 -0.2788631 -8.4836357 -8.078863 2
#> 6 1 -7.60 -12.40 0.5032685 2.6744475 -7.0967315 -9.725552 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5240 -74500 14025
#> initial value 998.131940
#> iter 2 value 653.756741
#> iter 3 value 653.628810
#> iter 4 value 653.626092
#> iter 5 value 630.955889
#> iter 6 value 628.396419
#> iter 7 value 628.327344
#> iter 8 value 628.326980
#> iter 8 value 628.326978
#> final value 628.326978
#> converged
#> This is Run number 68
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.65478525 0.5461493 -2.645215 -12.053851 1
#> 2 1 -0.35 -14.40 -1.19341886 0.6629951 -1.543419 -13.737005 1
#> 3 1 -12.20 -2.55 1.10698520 -1.0421209 -11.093015 -3.592121 2
#> 4 1 -2.30 -13.70 -0.03476897 2.1248576 -2.334769 -11.575142 1
#> 5 1 -12.60 -7.80 -0.14292779 -0.7222493 -12.742928 -8.522249 2
#> 6 1 -7.60 -12.40 -0.26595270 -0.2950156 -7.865953 -12.695016 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4340 -71825 14625
#> initial value 998.131940
#> iter 2 value 677.543874
#> iter 3 value 677.459788
#> iter 4 value 677.382475
#> iter 5 value 657.574328
#> iter 6 value 655.394439
#> iter 7 value 655.343142
#> iter 8 value 655.342811
#> iter 8 value 655.342808
#> final value 655.342808
#> converged
#> This is Run number 69
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.6920017 -0.2516188 -4.992002 -12.851619 1
#> 2 1 -0.35 -14.40 1.9089580 -1.1974846 1.558958 -15.597485 1
#> 3 1 -12.20 -2.55 0.9048175 -0.1374006 -11.295183 -2.687401 2
#> 4 1 -2.30 -13.70 1.1018301 0.9032942 -1.198170 -12.796706 1
#> 5 1 -12.60 -7.80 2.6655378 1.3247017 -9.934462 -6.475298 2
#> 6 1 -7.60 -12.40 -1.3204263 -0.2748454 -8.920426 -12.674845 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4900 -74350 15700
#> initial value 998.131940
#> iter 2 value 652.267600
#> iter 3 value 652.170980
#> iter 4 value 652.170365
#> iter 5 value 628.251307
#> iter 6 value 626.271019
#> iter 7 value 626.210075
#> iter 8 value 626.209699
#> iter 8 value 626.209695
#> final value 626.209695
#> converged
#> This is Run number 70
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.00480859 3.18962067 -2.2951914 -9.410379 1
#> 2 1 -0.35 -14.40 0.51485835 -0.11066583 0.1648584 -14.510666 1
#> 3 1 -12.20 -2.55 -0.95980525 -1.31194726 -13.1598053 -3.861947 2
#> 4 1 -2.30 -13.70 1.13748449 -1.21664878 -1.1625155 -14.916649 1
#> 5 1 -12.60 -7.80 0.07302557 1.85774157 -12.5269744 -5.942258 2
#> 6 1 -7.60 -12.40 -0.86277774 0.07524391 -8.4627777 -12.324756 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4600 -72375 13975
#> initial value 998.131940
#> iter 2 value 673.635667
#> iter 3 value 673.545430
#> iter 4 value 673.469982
#> iter 5 value 653.390945
#> iter 6 value 651.163681
#> iter 7 value 651.111874
#> iter 8 value 651.111586
#> iter 8 value 651.111584
#> final value 651.111584
#> converged
#> This is Run number 71
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.6379599 0.5146197 -4.937960 -12.085380 1
#> 2 1 -0.35 -14.40 3.0601433 0.3748955 2.710143 -14.025104 1
#> 3 1 -12.20 -2.55 1.8207942 -1.4581952 -10.379206 -4.008195 2
#> 4 1 -2.30 -13.70 -0.4339657 2.4473693 -2.733966 -11.252631 1
#> 5 1 -12.60 -7.80 -0.1334463 -2.2505837 -12.733446 -10.050584 2
#> 6 1 -7.60 -12.40 0.5641948 -0.7761765 -7.035805 -13.176176 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5160 -74250 14725
#> initial value 998.131940
#> iter 2 value 654.894295
#> iter 3 value 654.883154
#> iter 4 value 654.873155
#> iter 5 value 632.458089
#> iter 6 value 629.748579
#> iter 7 value 629.675109
#> iter 8 value 629.674678
#> iter 8 value 629.674675
#> final value 629.674675
#> converged
#> This is Run number 72
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.1187584 1.1616961 -5.4187584 -11.438304 1
#> 2 1 -0.35 -14.40 0.6180925 -0.6775066 0.2680925 -15.077507 1
#> 3 1 -12.20 -2.55 0.6502805 1.3230008 -11.5497195 -1.226999 2
#> 4 1 -2.30 -13.70 1.9501556 -0.2579866 -0.3498444 -13.957987 1
#> 5 1 -12.60 -7.80 1.2029309 2.0838801 -11.3970691 -5.716120 2
#> 6 1 -7.60 -12.40 -0.4235191 0.9247238 -8.0235191 -11.475276 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4680 -71150 16000
#> initial value 998.131940
#> iter 2 value 680.646155
#> iter 3 value 680.224089
#> iter 4 value 680.191466
#> iter 5 value 660.749421
#> iter 6 value 658.630916
#> iter 7 value 658.582629
#> iter 8 value 658.582386
#> iter 8 value 658.582384
#> final value 658.582384
#> converged
#> This is Run number 73
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.49755225 0.47033071 -4.7975522 -12.129669 1
#> 2 1 -0.35 -14.40 0.78395216 -1.72903873 0.4339522 -16.129039 1
#> 3 1 -12.20 -2.55 -1.06203659 -1.00072106 -13.2620366 -3.550721 2
#> 4 1 -2.30 -13.70 0.80147963 0.08929004 -1.4985204 -13.610710 1
#> 5 1 -12.60 -7.80 0.00824271 -1.28612924 -12.5917573 -9.086129 2
#> 6 1 -7.60 -12.40 0.91443115 0.56878283 -6.6855688 -11.831217 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4760 -70000 13000
#> initial value 998.131940
#> iter 2 value 696.055956
#> iter 3 value 695.885216
#> iter 4 value 695.871852
#> iter 5 value 678.629208
#> iter 6 value 677.028941
#> iter 7 value 677.001102
#> iter 8 value 677.001019
#> iter 8 value 677.001019
#> final value 677.001019
#> converged
#> This is Run number 74
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.3540840 0.01829728 -4.654084 -12.581703 1
#> 2 1 -0.35 -14.40 2.0083907 -0.62284846 1.658391 -15.022848 1
#> 3 1 -12.20 -2.55 1.5024345 -1.32762272 -10.697565 -3.877623 2
#> 4 1 -2.30 -13.70 -0.1226293 -0.25670000 -2.422629 -13.956700 1
#> 5 1 -12.60 -7.80 0.6444968 0.97441465 -11.955503 -6.825585 2
#> 6 1 -7.60 -12.40 -0.9377523 -0.17251761 -8.537752 -12.572518 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4600 -70950 14125
#> initial value 998.131940
#> iter 2 value 686.028356
#> iter 3 value 686.004102
#> iter 4 value 685.991962
#> iter 5 value 667.482125
#> iter 6 value 665.597830
#> iter 7 value 665.559282
#> iter 8 value 665.559113
#> iter 8 value 665.559112
#> final value 665.559112
#> converged
#> This is Run number 75
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.37951571 -0.6922312 -4.679516 -13.292231 1
#> 2 1 -0.35 -14.40 -0.13099503 3.4174968 -0.480995 -10.982503 1
#> 3 1 -12.20 -2.55 1.09756201 1.0582243 -11.102438 -1.491776 2
#> 4 1 -2.30 -13.70 0.61724330 3.0495946 -1.682757 -10.650405 1
#> 5 1 -12.60 -7.80 -0.44175636 -0.1185990 -13.041756 -7.918599 2
#> 6 1 -7.60 -12.40 0.08218988 2.6366516 -7.517810 -9.763348 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5400 -75050 15275
#> initial value 998.131940
#> iter 2 value 646.264074
#> iter 3 value 646.149237
#> iter 4 value 646.104097
#> iter 5 value 622.490376
#> iter 6 value 619.447308
#> iter 7 value 619.358079
#> iter 8 value 619.357503
#> iter 8 value 619.357499
#> final value 619.357499
#> converged
#> This is Run number 76
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.06544894 4.2956820 -4.2345511 -8.304318 1
#> 2 1 -0.35 -14.40 -0.30000050 -1.4079359 -0.6500005 -15.807936 1
#> 3 1 -12.20 -2.55 0.02251103 0.1351126 -12.1774890 -2.414887 2
#> 4 1 -2.30 -13.70 0.32969911 -0.6062525 -1.9703009 -14.306252 1
#> 5 1 -12.60 -7.80 0.44250001 3.8231542 -12.1575000 -3.976846 2
#> 6 1 -7.60 -12.40 0.64542874 -1.0755837 -6.9545713 -13.475584 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5180 -74250 14775
#> initial value 998.131940
#> iter 2 value 654.789753
#> iter 3 value 654.777438
#> iter 4 value 654.776436
#> iter 5 value 632.342752
#> iter 6 value 629.617407
#> iter 7 value 629.543616
#> iter 8 value 629.543185
#> iter 8 value 629.543183
#> final value 629.543183
#> converged
#> This is Run number 77
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.8257410 -0.05095656 -3.4742590 -12.650957 1
#> 2 1 -0.35 -14.40 0.7079710 0.30805584 0.3579710 -14.091944 1
#> 3 1 -12.20 -2.55 2.4179216 0.66691325 -9.7820784 -1.883087 2
#> 4 1 -2.30 -13.70 1.7208031 -1.06916605 -0.5791969 -14.769166 1
#> 5 1 -12.60 -7.80 1.8798603 -0.43184464 -10.7201397 -8.231845 2
#> 6 1 -7.60 -12.40 -0.3728693 0.93516098 -7.9728693 -11.464839 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4580 -74375 14950
#> initial value 998.131940
#> iter 2 value 653.668245
#> iter 3 value 653.471629
#> iter 4 value 653.436476
#> iter 5 value 630.650661
#> iter 6 value 627.738573
#> iter 7 value 627.651022
#> iter 8 value 627.650257
#> iter 8 value 627.650251
#> final value 627.650251
#> converged
#> This is Run number 78
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.06130088 1.6751306 -3.2386991 -10.924869 1
#> 2 1 -0.35 -14.40 -0.11802434 1.7689923 -0.4680243 -12.631008 1
#> 3 1 -12.20 -2.55 0.70851325 0.6977942 -11.4914868 -1.852206 2
#> 4 1 -2.30 -13.70 0.33867270 1.4667953 -1.9613273 -12.233205 1
#> 5 1 -12.60 -7.80 -0.17708399 1.4934748 -12.7770840 -6.306525 2
#> 6 1 -7.60 -12.40 -0.06090515 0.8371405 -7.6609051 -11.562860 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4760 -69375 10975
#> initial value 998.131940
#> iter 2 value 704.184694
#> iter 3 value 702.868478
#> iter 4 value 702.734307
#> iter 5 value 686.217133
#> iter 6 value 684.744833
#> iter 7 value 684.721303
#> iter 8 value 684.721250
#> iter 8 value 684.721250
#> final value 684.721250
#> converged
#> This is Run number 79
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.3133937 1.0010059 -3.9866063 -11.598994 1
#> 2 1 -0.35 -14.40 -0.8510258 0.8909837 -1.2010258 -13.509016 1
#> 3 1 -12.20 -2.55 0.5297319 1.1458015 -11.6702681 -1.404199 2
#> 4 1 -2.30 -13.70 2.4336733 -0.9770264 0.1336733 -14.677026 1
#> 5 1 -12.60 -7.80 1.3265574 1.2614109 -11.2734426 -6.538589 2
#> 6 1 -7.60 -12.40 0.2873698 -0.1825378 -7.3126302 -12.582538 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4940 -71025 13250
#> initial value 998.131940
#> iter 2 value 686.620085
#> iter 3 value 686.465443
#> iter 4 value 686.465225
#> iter 5 value 666.576096
#> iter 6 value 666.303787
#> iter 7 value 666.298083
#> iter 7 value 666.298074
#> iter 7 value 666.298074
#> final value 666.298074
#> converged
#> This is Run number 80
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.5205388 -1.04098975 -2.7794612 -13.640990 1
#> 2 1 -0.35 -14.40 -0.2138737 -0.05598396 -0.5638737 -14.455984 1
#> 3 1 -12.20 -2.55 0.1958772 -1.30264594 -12.0041228 -3.852646 2
#> 4 1 -2.30 -13.70 0.1594098 -0.08466912 -2.1405902 -13.784669 1
#> 5 1 -12.60 -7.80 -0.2565810 0.04074725 -12.8565810 -7.759253 2
#> 6 1 -7.60 -12.40 1.6523282 -0.86861025 -5.9476718 -13.268610 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4420 -70425 14400
#> initial value 998.131940
#> iter 2 value 690.226732
#> iter 3 value 690.185240
#> iter 4 value 690.161621
#> iter 5 value 672.058805
#> iter 6 value 670.236377
#> iter 7 value 670.199468
#> iter 8 value 670.199295
#> iter 8 value 670.199294
#> final value 670.199294
#> converged
#> This is Run number 81
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.32192994 1.00816472 -2.978070 -11.591835 1
#> 2 1 -0.35 -14.40 1.15812796 0.26979995 0.808128 -14.130200 1
#> 3 1 -12.20 -2.55 -0.27463459 0.62807382 -12.474635 -1.921926 2
#> 4 1 -2.30 -13.70 -0.07305990 -0.03440884 -2.373060 -13.734409 1
#> 5 1 -12.60 -7.80 0.07077062 -0.58292285 -12.529229 -8.382923 2
#> 6 1 -7.60 -12.40 3.85943781 -0.61316481 -3.740562 -13.013165 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4600 -73475 15025
#> initial value 998.131940
#> iter 2 value 661.793481
#> iter 3 value 661.738404
#> iter 4 value 661.697121
#> iter 5 value 639.994566
#> iter 6 value 637.364557
#> iter 7 value 637.291752
#> iter 8 value 637.291210
#> iter 8 value 637.291206
#> final value 637.291206
#> converged
#> This is Run number 82
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.6374872 0.5057596 -2.662513 -12.094240 1
#> 2 1 -0.35 -14.40 1.9844418 5.4560559 1.634442 -8.943944 1
#> 3 1 -12.20 -2.55 -0.1430002 -0.1914458 -12.343000 -2.741446 2
#> 4 1 -2.30 -13.70 0.3775050 0.7754727 -1.922495 -12.924527 1
#> 5 1 -12.60 -7.80 2.6505456 1.2731827 -9.949454 -6.526817 2
#> 6 1 -7.60 -12.40 1.9316310 -0.3145426 -5.668369 -12.714543 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4260 -70675 14700
#> initial value 998.131940
#> iter 2 value 687.583231
#> iter 3 value 687.470423
#> iter 4 value 687.374275
#> iter 5 value 668.855678
#> iter 6 value 666.925152
#> iter 7 value 666.883287
#> iter 8 value 666.883055
#> iter 8 value 666.883054
#> final value 666.883054
#> converged
#> This is Run number 83
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.24878777 -0.1336669 -4.05121223 -12.733667 1
#> 2 1 -0.35 -14.40 0.39341982 0.5089208 0.04341982 -13.891079 1
#> 3 1 -12.20 -2.55 0.03771031 -1.0309239 -12.16228969 -3.580924 2
#> 4 1 -2.30 -13.70 0.03368803 0.3081212 -2.26631197 -13.391879 1
#> 5 1 -12.60 -7.80 1.25293250 1.0025336 -11.34706750 -6.797466 2
#> 6 1 -7.60 -12.40 1.12586701 -0.1379748 -6.47413299 -12.537975 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5140 -73425 14175
#> initial value 998.131940
#> iter 2 value 663.462065
#> iter 3 value 663.409726
#> iter 4 value 663.402129
#> iter 5 value 642.141485
#> iter 6 value 639.742484
#> iter 7 value 639.683624
#> iter 8 value 639.683338
#> iter 8 value 639.683337
#> final value 639.683337
#> converged
#> This is Run number 84
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.07760881 1.6728073 -4.2223912 -10.927193 1
#> 2 1 -0.35 -14.40 -0.12308174 -0.2432710 -0.4730817 -14.643271 1
#> 3 1 -12.20 -2.55 -0.76434816 1.3396835 -12.9643482 -1.210316 2
#> 4 1 -2.30 -13.70 0.45922352 0.1094056 -1.8407765 -13.590594 1
#> 5 1 -12.60 -7.80 -0.01366645 -0.8460247 -12.6136664 -8.646025 2
#> 6 1 -7.60 -12.40 0.96934141 -0.4972624 -6.6306586 -12.897262 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4660 -70200 13075
#> initial value 998.131940
#> iter 2 value 694.265614
#> iter 3 value 694.095969
#> iter 4 value 694.051542
#> iter 5 value 676.587066
#> iter 6 value 674.920086
#> iter 7 value 674.890072
#> iter 8 value 674.889972
#> iter 8 value 674.889971
#> final value 674.889971
#> converged
#> This is Run number 85
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.1951989 0.73503100 -4.10480112 -11.864969 1
#> 2 1 -0.35 -14.40 0.2392806 1.17485328 -0.11071942 -13.225147 1
#> 3 1 -12.20 -2.55 0.9731295 1.32153278 -11.22687048 -1.228467 2
#> 4 1 -2.30 -13.70 2.3572994 -0.05578407 0.05729945 -13.755784 1
#> 5 1 -12.60 -7.80 2.6653256 0.64990949 -9.93467441 -7.150091 2
#> 6 1 -7.60 -12.40 -0.9071722 1.64724971 -8.50717223 -10.752750 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4240 -71575 14400
#> initial value 998.131940
#> iter 2 value 680.218742
#> iter 3 value 679.855423
#> iter 4 value 679.815929
#> iter 5 value 660.425576
#> iter 6 value 658.302918
#> iter 7 value 658.253344
#> iter 8 value 658.253027
#> iter 8 value 658.253025
#> final value 658.253025
#> converged
#> This is Run number 86
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.85608245 0.3882071 -5.1560824 -12.211793 1
#> 2 1 -0.35 -14.40 1.06079748 3.0886135 0.7107975 -11.311386 1
#> 3 1 -12.20 -2.55 2.07853815 2.9335360 -10.1214618 0.383536 2
#> 4 1 -2.30 -13.70 2.59750643 0.4144809 0.2975064 -13.285519 1
#> 5 1 -12.60 -7.80 -0.04829892 -1.6967200 -12.6482989 -9.496720 2
#> 6 1 -7.60 -12.40 -0.14939873 1.1398264 -7.7493987 -11.260174 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5060 -74750 15150
#> initial value 998.131940
#> iter 2 value 649.528846
#> iter 3 value 649.523578
#> iter 4 value 649.521701
#> iter 5 value 626.036695
#> iter 6 value 623.373244
#> iter 7 value 623.294229
#> iter 8 value 623.293701
#> iter 8 value 623.293697
#> final value 623.293697
#> converged
#> This is Run number 87
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.5323826 -0.004848633 -5.8323826 -12.604849 1
#> 2 1 -0.35 -14.40 0.1342492 -1.115834171 -0.2157508 -15.515834 1
#> 3 1 -12.20 -2.55 2.2908020 -0.915766951 -9.9091980 -3.465767 2
#> 4 1 -2.30 -13.70 1.5799699 -0.378282197 -0.7200301 -14.078282 1
#> 5 1 -12.60 -7.80 -0.4529208 1.054097071 -13.0529208 -6.745903 2
#> 6 1 -7.60 -12.40 -0.2585607 1.598410878 -7.8585607 -10.801589 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5420 -72725 13775
#> initial value 998.131940
#> iter 2 value 670.303946
#> iter 3 value 670.126371
#> iter 4 value 670.015098
#> iter 5 value 649.722848
#> iter 6 value 647.497843
#> iter 7 value 647.448893
#> iter 8 value 647.448717
#> iter 8 value 647.448716
#> final value 647.448716
#> converged
#> This is Run number 88
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.07997691 0.07997949 -4.2200231 -12.520021 1
#> 2 1 -0.35 -14.40 0.22983462 0.94714408 -0.1201654 -13.452856 1
#> 3 1 -12.20 -2.55 -1.10578906 0.74383374 -13.3057891 -1.806166 2
#> 4 1 -2.30 -13.70 1.10006527 -1.14588445 -1.1999347 -14.845884 1
#> 5 1 -12.60 -7.80 0.95511837 2.86634117 -11.6448816 -4.933659 2
#> 6 1 -7.60 -12.40 3.32186007 1.69658017 -4.2781399 -10.703420 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5180 -72475 14400
#> initial value 998.131940
#> iter 2 value 671.646378
#> iter 3 value 671.634398
#> iter 4 value 671.605896
#> iter 5 value 651.373387
#> iter 6 value 649.156814
#> iter 7 value 649.106218
#> iter 8 value 649.106003
#> iter 8 value 649.106002
#> final value 649.106002
#> converged
#> This is Run number 89
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.65493382 1.71327646 -1.645066 -10.88672 1
#> 2 1 -0.35 -14.40 1.11226400 -0.02594771 0.762264 -14.42595 1
#> 3 1 -12.20 -2.55 -0.64256751 -0.12508041 -12.842568 -2.67508 2
#> 4 1 -2.30 -13.70 0.38373882 -0.14182579 -1.916261 -13.84183 1
#> 5 1 -12.60 -7.80 0.01688291 1.02815983 -12.583117 -6.77184 2
#> 6 1 -7.60 -12.40 0.05817692 -0.24883536 -7.541823 -12.64884 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4600 -73800 15050
#> initial value 998.131940
#> iter 2 value 658.771247
#> iter 3 value 658.711401
#> iter 4 value 658.688276
#> iter 5 value 636.541815
#> iter 6 value 633.808290
#> iter 7 value 633.729703
#> iter 8 value 633.729081
#> iter 8 value 633.729076
#> final value 633.729076
#> converged
#> This is Run number 90
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.15864537 -0.7537298 -4.14135463 -13.3537298 1
#> 2 1 -0.35 -14.40 0.26918073 1.7203385 -0.08081927 -12.6796615 1
#> 3 1 -12.20 -2.55 1.73501450 2.0985387 -10.46498550 -0.4514613 2
#> 4 1 -2.30 -13.70 0.05156272 1.3666659 -2.24843728 -12.3333341 1
#> 5 1 -12.60 -7.80 -1.36240067 -0.2884814 -13.96240067 -8.0884814 2
#> 6 1 -7.60 -12.40 -1.07068000 1.0210922 -8.67068000 -11.3789078 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4700 -73525 16100
#> initial value 998.131940
#> iter 2 value 659.149712
#> iter 3 value 658.872504
#> iter 4 value 658.872169
#> iter 5 value 634.982544
#> iter 6 value 633.886083
#> iter 7 value 633.851398
#> iter 8 value 633.851225
#> iter 8 value 633.851224
#> final value 633.851224
#> converged
#> This is Run number 91
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.25371645 -0.73724825 -4.5537164 -13.337248 1
#> 2 1 -0.35 -14.40 -0.05449752 2.32810691 -0.4044975 -12.071893 1
#> 3 1 -12.20 -2.55 0.01678232 0.06640227 -12.1832177 -2.483598 2
#> 4 1 -2.30 -13.70 1.39032237 0.59209137 -0.9096776 -13.107909 1
#> 5 1 -12.60 -7.80 0.39776613 4.23587850 -12.2022339 -3.564122 2
#> 6 1 -7.60 -12.40 0.50806621 -0.14847029 -7.0919338 -12.548470 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4420 -70800 13700
#> initial value 998.131940
#> iter 2 value 688.162310
#> iter 3 value 688.056925
#> iter 4 value 688.002110
#> iter 5 value 669.622499
#> iter 6 value 667.765947
#> iter 7 value 667.728780
#> iter 8 value 667.728608
#> iter 8 value 667.728607
#> final value 667.728607
#> converged
#> This is Run number 92
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.25710812 -0.9562916 -5.557108 -13.556292 1
#> 2 1 -0.35 -14.40 -1.33366873 0.5930718 -1.683669 -13.806928 1
#> 3 1 -12.20 -2.55 0.01019027 0.8684292 -12.189810 -1.681571 2
#> 4 1 -2.30 -13.70 1.22091986 2.0199612 -1.079080 -11.680039 1
#> 5 1 -12.60 -7.80 -0.16053757 -1.0880936 -12.760538 -8.888094 2
#> 6 1 -7.60 -12.40 0.59779638 0.2933973 -7.002204 -12.106603 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4280 -72625 14675
#> initial value 998.131940
#> iter 2 value 670.318290
#> iter 3 value 669.977133
#> iter 4 value 669.893595
#> iter 5 value 649.199567
#> iter 6 value 646.782481
#> iter 7 value 646.719474
#> iter 8 value 646.718990
#> iter 8 value 646.718986
#> final value 646.718986
#> converged
#> This is Run number 93
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.41680972 1.1643052 -2.883190 -11.435695 1
#> 2 1 -0.35 -14.40 1.41630076 -0.3799634 1.066301 -14.779963 1
#> 3 1 -12.20 -2.55 1.63470203 -0.9650620 -10.565298 -3.515062 2
#> 4 1 -2.30 -13.70 -0.06336461 0.4509771 -2.363365 -13.249023 1
#> 5 1 -12.60 -7.80 3.22170144 1.3523762 -9.378299 -6.447624 2
#> 6 1 -7.60 -12.40 0.65432240 -0.1825463 -6.945678 -12.582546 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4420 -73900 14675
#> initial value 998.131940
#> iter 2 value 658.641284
#> iter 3 value 658.215052
#> iter 4 value 658.212306
#> iter 5 value 636.009870
#> iter 6 value 633.268631
#> iter 7 value 633.188275
#> iter 8 value 633.187595
#> iter 8 value 633.187590
#> final value 633.187590
#> converged
#> This is Run number 94
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.5433488 2.0142352 -2.7566512 -10.585765 1
#> 2 1 -0.35 -14.40 0.2133637 -0.2628284 -0.1366363 -14.662828 1
#> 3 1 -12.20 -2.55 -0.9158065 0.9348801 -13.1158065 -1.615120 2
#> 4 1 -2.30 -13.70 2.7328191 0.2726192 0.4328191 -13.427381 1
#> 5 1 -12.60 -7.80 -0.4322902 0.1231132 -13.0322902 -7.676887 2
#> 6 1 -7.60 -12.40 0.8171500 1.4607659 -6.7828500 -10.939234 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4360 -72900 13875
#> initial value 998.131940
#> iter 2 value 669.194961
#> iter 3 value 668.947512
#> iter 4 value 668.887555
#> iter 5 value 647.799035
#> iter 6 value 645.389848
#> iter 7 value 645.328372
#> iter 8 value 645.327933
#> iter 8 value 645.327929
#> final value 645.327929
#> converged
#> This is Run number 95
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.09025126 0.6749734 -5.3902513 -11.925027 1
#> 2 1 -0.35 -14.40 0.74899971 -0.3440018 0.3989997 -14.744002 1
#> 3 1 -12.20 -2.55 4.92772656 1.4098733 -7.2722734 -1.140127 2
#> 4 1 -2.30 -13.70 3.02064111 1.7546755 0.7206411 -11.945324 1
#> 5 1 -12.60 -7.80 0.92776839 2.2362037 -11.6722316 -5.563796 2
#> 6 1 -7.60 -12.40 0.03904138 -0.1802480 -7.5609586 -12.580248 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4740 -72925 13200
#> initial value 998.131940
#> iter 2 value 669.854833
#> iter 3 value 669.506902
#> iter 4 value 669.366286
#> iter 5 value 648.862181
#> iter 6 value 646.550467
#> iter 7 value 646.495510
#> iter 8 value 646.495223
#> iter 8 value 646.495221
#> final value 646.495221
#> converged
#> This is Run number 96
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.1831431 1.24134445 -4.4831431 -11.358656 1
#> 2 1 -0.35 -14.40 1.1632052 1.31522763 0.8132052 -13.084772 1
#> 3 1 -12.20 -2.55 2.9605297 0.41001834 -9.2394703 -2.139982 2
#> 4 1 -2.30 -13.70 1.4234379 -0.07907111 -0.8765621 -13.779071 1
#> 5 1 -12.60 -7.80 -0.4994702 0.70513196 -13.0994702 -7.094868 2
#> 6 1 -7.60 -12.40 1.0335398 0.84693643 -6.5664602 -11.553064 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4540 -74000 14000
#> initial value 998.131940
#> iter 2 value 658.842200
#> iter 3 value 658.618877
#> iter 4 value 658.439407
#> iter 5 value 636.259963
#> iter 6 value 633.545981
#> iter 7 value 633.470468
#> iter 8 value 633.469890
#> iter 8 value 633.469885
#> final value 633.469885
#> converged
#> This is Run number 97
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.9969201 0.484236469 -5.29692013 -12.115764 1
#> 2 1 -0.35 -14.40 0.2812222 1.032504635 -0.06877783 -13.367495 1
#> 3 1 -12.20 -2.55 0.6225513 0.649991292 -11.57744871 -1.900009 2
#> 4 1 -2.30 -13.70 0.1489545 -0.122196756 -2.15104552 -13.822197 1
#> 5 1 -12.60 -7.80 2.8521189 3.796334587 -9.74788112 -4.003665 2
#> 6 1 -7.60 -12.40 -1.2429777 0.003581328 -8.84297767 -12.396419 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5300 -70850 14175
#> initial value 998.131940
#> iter 2 value 686.379563
#> iter 3 value 686.099188
#> iter 4 value 686.043675
#> iter 5 value 667.669694
#> iter 6 value 665.837393
#> iter 7 value 665.802529
#> iter 8 value 665.802427
#> iter 8 value 665.802426
#> final value 665.802426
#> converged
#> This is Run number 98
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.4167873 1.8801166 -2.8832127 -10.719883 1
#> 2 1 -0.35 -14.40 0.8883569 0.8959816 0.5383569 -13.504018 1
#> 3 1 -12.20 -2.55 2.0278065 0.2641276 -10.1721935 -2.285872 2
#> 4 1 -2.30 -13.70 0.7598899 3.3665853 -1.5401101 -10.333415 1
#> 5 1 -12.60 -7.80 5.1800416 -0.7529518 -7.4199584 -8.552952 1
#> 6 1 -7.60 -12.40 2.0958752 -0.3899312 -5.5041248 -12.789931 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5740 -71850 15325
#> initial value 998.131940
#> iter 2 value 675.101833
#> iter 3 value 674.708691
#> iter 4 value 674.273130
#> iter 5 value 653.588585
#> iter 6 value 651.422796
#> iter 7 value 651.373252
#> iter 8 value 651.373017
#> iter 8 value 651.373014
#> final value 651.373014
#> converged
#> This is Run number 99
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.4713788 1.5017671 -4.771379 -11.098233 1
#> 2 1 -0.35 -14.40 1.5046438 1.1153738 1.154644 -13.284626 1
#> 3 1 -12.20 -2.55 0.5619061 0.9171746 -11.638094 -1.632825 2
#> 4 1 -2.30 -13.70 0.4807849 0.8247922 -1.819215 -12.875208 1
#> 5 1 -12.60 -7.80 0.4015633 -0.5795607 -12.198437 -8.379561 2
#> 6 1 -7.60 -12.40 0.8281306 -0.5611758 -6.771869 -12.961176 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5080 -73100 15350
#> initial value 998.131940
#> iter 2 value 664.298290
#> iter 3 value 664.206821
#> iter 4 value 664.146405
#> iter 5 value 642.891961
#> iter 6 value 640.399273
#> iter 7 value 640.336055
#> iter 8 value 640.335711
#> iter 8 value 640.335709
#> final value 640.335709
#> converged
#> This is Run number 100
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.2877142 4.4875013 -5.587714 -8.112499 1
#> 2 1 -0.35 -14.40 1.7312855 0.6773761 1.381286 -13.722624 1
#> 3 1 -12.20 -2.55 -0.6842469 0.5310447 -12.884247 -2.018955 2
#> 4 1 -2.30 -13.70 -0.3892328 2.2201738 -2.689233 -11.479826 1
#> 5 1 -12.60 -7.80 -0.9936139 0.6106906 -13.593614 -7.189309 2
#> 6 1 -7.60 -12.40 1.9587034 0.3703532 -5.641297 -12.029647 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3440 -71725 14975
#> initial value 998.131940
#> iter 2 value 678.153955
#> iter 3 value 677.504319
#> iter 4 value 676.874785
#> iter 5 value 655.615451
#> iter 6 value 653.218088
#> iter 7 value 653.145065
#> iter 8 value 653.144103
#> iter 9 value 653.144093
#> iter 9 value 653.144087
#> iter 9 value 653.144086
#> final value 653.144086
#> converged
#> This is Run number 101
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.6728262 1.4040107 -4.9728262 -11.195989 1
#> 2 1 -0.35 -14.40 0.6647315 0.4364536 0.3147315 -13.963546 1
#> 3 1 -12.20 -2.55 -1.2945553 0.4466363 -13.4945553 -2.103364 2
#> 4 1 -2.30 -13.70 0.7235386 1.4311475 -1.5764614 -12.268853 1
#> 5 1 -12.60 -7.80 1.1756940 0.2752915 -11.4243060 -7.524709 2
#> 6 1 -7.60 -12.40 2.9442947 -0.8371764 -4.6557053 -13.237176 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4380 -70075 14100
#> initial value 998.131940
#> iter 2 value 693.813567
#> iter 3 value 693.695183
#> iter 4 value 693.684677
#> iter 5 value 676.051172
#> iter 6 value 674.321971
#> iter 7 value 674.288720
#> iter 8 value 674.288574
#> iter 8 value 674.288573
#> final value 674.288573
#> converged
#> This is Run number 102
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.6694986 -0.4983024 -2.630501 -13.098302 1
#> 2 1 -0.35 -14.40 1.5004667 -0.2534249 1.150467 -14.653425 1
#> 3 1 -12.20 -2.55 -0.4778551 0.9121890 -12.677855 -1.637811 2
#> 4 1 -2.30 -13.70 -0.9795483 0.8166628 -3.279548 -12.883337 1
#> 5 1 -12.60 -7.80 3.7550751 0.7221944 -8.844925 -7.077806 2
#> 6 1 -7.60 -12.40 -0.2257315 -0.7528861 -7.825731 -13.152886 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5300 -71025 12600
#> initial value 998.131940
#> iter 2 value 687.370442
#> iter 3 value 686.910044
#> iter 4 value 686.867210
#> iter 5 value 668.658292
#> iter 6 value 666.882695
#> iter 7 value 666.850349
#> iter 8 value 666.850268
#> iter 8 value 666.850267
#> final value 666.850267
#> converged
#> This is Run number 103
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.39749903 0.9712735 -4.69749903 -11.628727 1
#> 2 1 -0.35 -14.40 0.30610723 2.5063121 -0.04389277 -11.893688 1
#> 3 1 -12.20 -2.55 -0.36902478 -0.7943563 -12.56902478 -3.344356 2
#> 4 1 -2.30 -13.70 1.74175623 2.1127153 -0.55824377 -11.587285 1
#> 5 1 -12.60 -7.80 0.63140237 0.7337173 -11.96859763 -7.066283 2
#> 6 1 -7.60 -12.40 -0.09024658 2.6757563 -7.69024658 -9.724244 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4700 -72200 13375
#> initial value 998.131940
#> iter 2 value 676.136483
#> iter 3 value 675.919200
#> iter 4 value 675.820124
#> iter 5 value 656.132199
#> iter 6 value 653.999742
#> iter 7 value 653.952314
#> iter 8 value 653.952086
#> iter 8 value 653.952085
#> final value 653.952085
#> converged
#> This is Run number 104
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.03359119 -0.52930492 -4.2664088 -13.129305 1
#> 2 1 -0.35 -14.40 -0.34189507 1.50888227 -0.6918951 -12.891118 1
#> 3 1 -12.20 -2.55 0.48262596 -0.69065665 -11.7173740 -3.240657 2
#> 4 1 -2.30 -13.70 -0.22357868 1.52931704 -2.5235787 -12.170683 1
#> 5 1 -12.60 -7.80 0.67798276 0.06679331 -11.9220172 -7.733207 2
#> 6 1 -7.60 -12.40 1.95566076 0.22308639 -5.6443392 -12.176914 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4400 -71800 14075
#> initial value 998.131940
#> iter 2 value 678.710627
#> iter 3 value 678.551348
#> iter 4 value 678.472417
#> iter 5 value 658.920465
#> iter 6 value 656.798674
#> iter 7 value 656.749475
#> iter 8 value 656.749192
#> iter 8 value 656.749190
#> final value 656.749190
#> converged
#> This is Run number 105
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.11641323 1.2644017 -4.416413 -11.335598 1
#> 2 1 -0.35 -14.40 2.42204919 -0.6387806 2.072049 -15.038781 1
#> 3 1 -12.20 -2.55 1.04718376 -0.1241774 -11.152816 -2.674177 2
#> 4 1 -2.30 -13.70 -0.59086782 1.7431289 -2.890868 -11.956871 1
#> 5 1 -12.60 -7.80 0.07653044 0.3547215 -12.523470 -7.445279 2
#> 6 1 -7.60 -12.40 1.71940542 3.3807394 -5.880595 -9.019261 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4600 -72325 14400
#> initial value 998.131940
#> iter 2 value 673.345553
#> iter 3 value 673.251652
#> iter 4 value 673.241555
#> iter 5 value 653.138484
#> iter 6 value 650.899058
#> iter 7 value 650.845864
#> iter 8 value 650.845561
#> iter 8 value 650.845559
#> final value 650.845559
#> converged
#> This is Run number 106
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.26656589 -0.63489233 -2.033434 -13.234892 1
#> 2 1 -0.35 -14.40 -1.40217523 0.71003799 -1.752175 -13.689962 1
#> 3 1 -12.20 -2.55 1.10462912 -0.56868747 -11.095371 -3.118687 2
#> 4 1 -2.30 -13.70 -0.03932763 -0.02206243 -2.339328 -13.722062 1
#> 5 1 -12.60 -7.80 -0.92128902 -0.20867076 -13.521289 -8.008671 2
#> 6 1 -7.60 -12.40 -0.13219471 1.23098763 -7.732195 -11.169012 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4940 -74275 14575
#> initial value 998.131940
#> iter 2 value 655.073504
#> iter 3 value 655.054880
#> iter 4 value 655.042685
#> iter 5 value 632.607797
#> iter 6 value 629.876183
#> iter 7 value 629.800350
#> iter 8 value 629.799849
#> iter 8 value 629.799845
#> final value 629.799845
#> converged
#> This is Run number 107
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.93350019 -0.1205364 -2.366500 -12.720536 1
#> 2 1 -0.35 -14.40 1.42314126 1.3030525 1.073141 -13.096947 1
#> 3 1 -12.20 -2.55 0.06665342 -0.4528119 -12.133347 -3.002812 2
#> 4 1 -2.30 -13.70 0.89909466 1.4726387 -1.400905 -12.227361 1
#> 5 1 -12.60 -7.80 -0.19910950 2.3811987 -12.799110 -5.418801 2
#> 6 1 -7.60 -12.40 0.13605950 1.1180446 -7.463941 -11.281955 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4500 -72650 13800
#> initial value 998.131940
#> iter 2 value 671.508476
#> iter 3 value 671.325537
#> iter 4 value 671.174179
#> iter 5 value 650.725836
#> iter 6 value 648.417175
#> iter 7 value 648.361430
#> iter 8 value 648.361089
#> iter 8 value 648.361087
#> final value 648.361087
#> converged
#> This is Run number 108
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.70330074 0.54435259 -5.003301 -12.055647 1
#> 2 1 -0.35 -14.40 1.64931377 -0.74298772 1.299314 -15.142988 1
#> 3 1 -12.20 -2.55 0.03333762 -0.01105715 -12.166662 -2.561057 2
#> 4 1 -2.30 -13.70 0.13419956 -0.18791217 -2.165800 -13.887912 1
#> 5 1 -12.60 -7.80 0.64571364 3.97399638 -11.954286 -3.826004 2
#> 6 1 -7.60 -12.40 -1.24027532 -0.85940458 -8.840275 -13.259405 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5020 -71225 14175
#> initial value 998.131940
#> iter 2 value 683.272320
#> iter 3 value 683.250173
#> iter 4 value 683.233698
#> iter 5 value 664.472859
#> iter 6 value 662.557781
#> iter 7 value 662.519737
#> iter 8 value 662.519603
#> iter 8 value 662.519602
#> final value 662.519602
#> converged
#> This is Run number 109
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.0734510 0.3595417 -5.37345095 -12.240458 1
#> 2 1 -0.35 -14.40 0.3911422 0.4631792 0.04114218 -13.936821 1
#> 3 1 -12.20 -2.55 1.3116707 -0.5465668 -10.88832934 -3.096567 2
#> 4 1 -2.30 -13.70 0.9152754 5.1811230 -1.38472460 -8.518877 1
#> 5 1 -12.60 -7.80 2.7475845 0.2702410 -9.85241555 -7.529759 2
#> 6 1 -7.60 -12.40 0.3369158 -0.4229681 -7.26308420 -12.822968 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4520 -73900 14300
#> initial value 998.131940
#> iter 2 value 659.257689
#> iter 3 value 659.225983
#> iter 4 value 659.111730
#> iter 5 value 636.839757
#> iter 6 value 634.131030
#> iter 7 value 634.052093
#> iter 8 value 634.051469
#> iter 8 value 634.051465
#> final value 634.051465
#> converged
#> This is Run number 110
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.5464925 -0.4169938 -3.753507 -13.016994 1
#> 2 1 -0.35 -14.40 -1.0173049 0.9580342 -1.367305 -13.441966 1
#> 3 1 -12.20 -2.55 1.2816494 1.0385037 -10.918351 -1.511496 2
#> 4 1 -2.30 -13.70 -1.0249094 0.4857702 -3.324909 -13.214230 1
#> 5 1 -12.60 -7.80 0.9851713 0.6783836 -11.614829 -7.121616 2
#> 6 1 -7.60 -12.40 -0.2341484 -0.4690074 -7.834148 -12.869007 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3880 -72750 15400
#> initial value 998.131940
#> iter 2 value 667.997826
#> iter 3 value 667.544022
#> iter 4 value 667.246644
#> iter 5 value 645.553550
#> iter 6 value 642.897918
#> iter 7 value 642.815561
#> iter 8 value 642.814707
#> iter 8 value 642.814702
#> final value 642.814702
#> converged
#> This is Run number 111
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.8140951 0.176361789 -3.4859049 -12.423638 1
#> 2 1 -0.35 -14.40 0.5429216 -0.894735661 0.1929216 -15.294736 1
#> 3 1 -12.20 -2.55 -1.4529724 -0.033090705 -13.6529724 -2.583091 2
#> 4 1 -2.30 -13.70 -0.7000616 -0.934135417 -3.0000616 -14.634135 1
#> 5 1 -12.60 -7.80 -0.4479117 0.007912471 -13.0479117 -7.792088 2
#> 6 1 -7.60 -12.40 -0.3456897 0.114721854 -7.9456897 -12.285278 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4600 -72400 13975
#> initial value 998.131940
#> iter 2 value 673.411112
#> iter 3 value 673.319464
#> iter 4 value 673.242733
#> iter 5 value 653.134269
#> iter 6 value 650.900390
#> iter 7 value 650.848294
#> iter 8 value 650.848004
#> iter 8 value 650.848002
#> final value 650.848002
#> converged
#> This is Run number 112
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.8120569 0.56024844 -3.487943 -12.039752 1
#> 2 1 -0.35 -14.40 -0.7347272 0.09514803 -1.084727 -14.304852 1
#> 3 1 -12.20 -2.55 -1.0278936 -0.59487928 -13.227894 -3.144879 2
#> 4 1 -2.30 -13.70 -0.3693207 2.62079430 -2.669321 -11.079206 1
#> 5 1 -12.60 -7.80 -1.0011511 3.19653924 -13.601151 -4.603461 2
#> 6 1 -7.60 -12.40 0.7405706 1.50438547 -6.859429 -10.895615 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5260 -75250 14300
#> initial value 998.131940
#> iter 2 value 646.268718
#> iter 3 value 646.175967
#> iter 4 value 646.174165
#> iter 5 value 622.332422
#> iter 6 value 619.642635
#> iter 7 value 619.563587
#> iter 8 value 619.563117
#> iter 8 value 619.563114
#> final value 619.563114
#> converged
#> This is Run number 113
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.3058185 0.7854495 -2.9941815 -11.814551 1
#> 2 1 -0.35 -14.40 0.6143389 -0.8003047 0.2643389 -15.200305 1
#> 3 1 -12.20 -2.55 2.2397891 -0.5771621 -9.9602109 -3.127162 2
#> 4 1 -2.30 -13.70 -1.0565293 -0.7919461 -3.3565293 -14.491946 1
#> 5 1 -12.60 -7.80 2.7160394 -1.3791478 -9.8839606 -9.179148 2
#> 6 1 -7.60 -12.40 -0.0240587 -0.6410415 -7.6240587 -13.041041 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4440 -73600 14675
#> initial value 998.131940
#> iter 2 value 661.383296
#> iter 3 value 661.028290
#> iter 4 value 661.027488
#> iter 5 value 639.132654
#> iter 6 value 636.572805
#> iter 7 value 636.500080
#> iter 8 value 636.499507
#> iter 8 value 636.499503
#> final value 636.499503
#> converged
#> This is Run number 114
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.1394618 0.5641638 -4.4394618 -12.035836 1
#> 2 1 -0.35 -14.40 0.7864419 0.4070969 0.4364419 -13.992903 1
#> 3 1 -12.20 -2.55 -1.4121582 0.0882740 -13.6121582 -2.461726 2
#> 4 1 -2.30 -13.70 -0.5849067 1.3566893 -2.8849067 -12.343311 1
#> 5 1 -12.60 -7.80 0.6323337 -0.4704774 -11.9676663 -8.270477 2
#> 6 1 -7.60 -12.40 2.8665927 2.4676598 -4.7334073 -9.932340 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4660 -72575 15775
#> initial value 998.131940
#> iter 2 value 668.449388
#> iter 3 value 668.230833
#> iter 4 value 668.230599
#> iter 5 value 645.229884
#> iter 6 value 644.827084
#> iter 7 value 644.814556
#> iter 8 value 644.814513
#> iter 8 value 644.814513
#> final value 644.814513
#> converged
#> This is Run number 115
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.2733394 -0.5129453 -2.0266606 -13.112945 1
#> 2 1 -0.35 -14.40 -0.1016089 -1.2142145 -0.4516089 -15.614214 1
#> 3 1 -12.20 -2.55 2.3199943 3.7423271 -9.8800057 1.192327 2
#> 4 1 -2.30 -13.70 0.2905330 0.5184933 -2.0094670 -13.181507 1
#> 5 1 -12.60 -7.80 -1.2706554 0.8240849 -13.8706554 -6.975915 2
#> 6 1 -7.60 -12.40 -0.2185558 0.8835981 -7.8185558 -11.516402 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4440 -72000 15100
#> initial value 998.131940
#> iter 2 value 675.047739
#> iter 3 value 674.941033
#> iter 4 value 674.874048
#> iter 5 value 654.852885
#> iter 6 value 652.596140
#> iter 7 value 652.540941
#> iter 8 value 652.540590
#> iter 8 value 652.540588
#> final value 652.540588
#> converged
#> This is Run number 116
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.2958736 1.58132221 -4.0041264 -11.018678 1
#> 2 1 -0.35 -14.40 -0.3347909 0.36117070 -0.6847909 -14.038829 1
#> 3 1 -12.20 -2.55 1.8438965 -0.22932416 -10.3561035 -2.779324 2
#> 4 1 -2.30 -13.70 -0.4977674 -0.18293054 -2.7977674 -13.882931 1
#> 5 1 -12.60 -7.80 0.1913821 -0.06163028 -12.4086179 -7.861630 2
#> 6 1 -7.60 -12.40 -0.1864274 -0.64881206 -7.7864274 -13.048812 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5460 -71950 13475
#> initial value 998.131940
#> iter 2 value 677.721090
#> iter 3 value 677.472287
#> iter 4 value 677.318396
#> iter 5 value 657.952307
#> iter 6 value 655.931482
#> iter 7 value 655.890712
#> iter 8 value 655.890590
#> iter 8 value 655.890589
#> final value 655.890589
#> converged
#> This is Run number 117
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.5958091 -0.2115411 -4.8958091 -12.8115411 1
#> 2 1 -0.35 -14.40 1.0224288 -1.3077942 0.6724288 -15.7077942 1
#> 3 1 -12.20 -2.55 1.5776627 1.7452321 -10.6223373 -0.8047679 2
#> 4 1 -2.30 -13.70 0.8425263 -0.3646225 -1.4574737 -14.0646225 1
#> 5 1 -12.60 -7.80 0.9304121 0.7217657 -11.6695879 -7.0782343 2
#> 6 1 -7.60 -12.40 3.5052583 -0.1066806 -4.0947417 -12.5066806 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4560 -72600 15325
#> initial value 998.131940
#> iter 2 value 669.174047
#> iter 3 value 669.065081
#> iter 4 value 669.033562
#> iter 5 value 648.271010
#> iter 6 value 645.858303
#> iter 7 value 645.796190
#> iter 8 value 645.795777
#> iter 8 value 645.795775
#> final value 645.795775
#> converged
#> This is Run number 118
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.01686325 1.9723953 -4.3168633 -10.627605 1
#> 2 1 -0.35 -14.40 -0.26945029 1.2631104 -0.6194503 -13.136890 1
#> 3 1 -12.20 -2.55 -0.64644081 -0.7325113 -12.8464408 -3.282511 2
#> 4 1 -2.30 -13.70 0.33764667 2.1603476 -1.9623533 -11.539652 1
#> 5 1 -12.60 -7.80 -0.24137058 0.1776701 -12.8413706 -7.622330 2
#> 6 1 -7.60 -12.40 1.64146951 1.7113289 -5.9585305 -10.688671 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5020 -72925 14050
#> initial value 998.131940
#> iter 2 value 668.300045
#> iter 3 value 668.249109
#> iter 4 value 668.248989
#> iter 5 value 649.652368
#> iter 6 value 645.404173
#> iter 7 value 645.280944
#> iter 8 value 645.279935
#> iter 8 value 645.279933
#> final value 645.279933
#> converged
#> This is Run number 119
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.02314186 3.1864357 -3.276858 -9.413564 1
#> 2 1 -0.35 -14.40 1.97827549 2.1288547 1.628275 -12.271145 1
#> 3 1 -12.20 -2.55 -0.01089579 -0.3880865 -12.210896 -2.938086 2
#> 4 1 -2.30 -13.70 -1.19276016 0.2639320 -3.492760 -13.436068 1
#> 5 1 -12.60 -7.80 -0.59933678 2.0043410 -13.199337 -5.795659 2
#> 6 1 -7.60 -12.40 3.44585848 -0.2813465 -4.154142 -12.681347 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4300 -69325 12350
#> initial value 998.131940
#> iter 2 value 703.077172
#> iter 3 value 702.592668
#> iter 4 value 702.297247
#> iter 5 value 685.684783
#> iter 6 value 684.164067
#> iter 7 value 684.138338
#> iter 8 value 684.138250
#> iter 8 value 684.138250
#> final value 684.138250
#> converged
#> This is Run number 120
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.6328050 1.1832405 -3.6671950 -11.416760 1
#> 2 1 -0.35 -14.40 1.2450412 2.4975270 0.8950412 -11.902473 1
#> 3 1 -12.20 -2.55 1.3844440 -0.4999469 -10.8155560 -3.049947 2
#> 4 1 -2.30 -13.70 1.6480942 1.5101697 -0.6519058 -12.189830 1
#> 5 1 -12.60 -7.80 2.9311414 1.5250153 -9.6688586 -6.274985 2
#> 6 1 -7.60 -12.40 0.6463803 -1.1794469 -6.9536197 -13.579447 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4840 -72700 14425
#> initial value 998.131940
#> iter 2 value 669.790036
#> iter 3 value 669.783882
#> iter 4 value 669.778729
#> iter 5 value 649.237461
#> iter 6 value 646.994391
#> iter 7 value 646.940834
#> iter 8 value 646.940556
#> iter 8 value 646.940554
#> final value 646.940554
#> converged
#> This is Run number 121
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.5876236 -0.3711555 -5.8876236 -12.9711555 1
#> 2 1 -0.35 -14.40 -0.4992206 1.8723490 -0.8492206 -12.5276510 1
#> 3 1 -12.20 -2.55 -0.1665223 2.6661831 -12.3665223 0.1161831 2
#> 4 1 -2.30 -13.70 1.1727825 1.6672619 -1.1272175 -12.0327381 1
#> 5 1 -12.60 -7.80 0.1560600 4.9228132 -12.4439400 -2.8771868 2
#> 6 1 -7.60 -12.40 3.3114794 0.1734000 -4.2885206 -12.2266000 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5060 -72250 12700
#> initial value 998.131940
#> iter 2 value 676.502858
#> iter 3 value 676.020196
#> iter 4 value 676.009060
#> iter 5 value 656.403593
#> iter 6 value 654.358986
#> iter 7 value 654.315778
#> iter 8 value 654.315623
#> iter 8 value 654.315623
#> final value 654.315623
#> converged
#> This is Run number 122
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.3527615 -0.61299491 -4.6527615 -13.212995 1
#> 2 1 -0.35 -14.40 -0.4289504 -0.31175597 -0.7789504 -14.711756 1
#> 3 1 -12.20 -2.55 2.7812069 -1.06483461 -9.4187931 -3.614835 2
#> 4 1 -2.30 -13.70 0.6262214 0.63769266 -1.6737786 -13.062307 1
#> 5 1 -12.60 -7.80 1.2493009 0.03583726 -11.3506991 -7.764163 2
#> 6 1 -7.60 -12.40 1.3995312 -0.80711241 -6.2004688 -13.207112 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5180 -71775 12600
#> initial value 998.131940
#> iter 2 value 680.815448
#> iter 3 value 680.318621
#> iter 4 value 680.317606
#> iter 5 value 660.939325
#> iter 6 value 659.343964
#> iter 7 value 659.311965
#> iter 8 value 659.311881
#> iter 8 value 659.311881
#> final value 659.311881
#> converged
#> This is Run number 123
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.8300159 0.6130601 -3.469984 -11.9869399 1
#> 2 1 -0.35 -14.40 1.9865207 -0.0271240 1.636521 -14.4271240 1
#> 3 1 -12.20 -2.55 -0.5713679 2.7838094 -12.771368 0.2338094 2
#> 4 1 -2.30 -13.70 3.6775099 1.0895166 1.377510 -12.6104834 1
#> 5 1 -12.60 -7.80 0.2419027 0.1915803 -12.358097 -7.6084197 2
#> 6 1 -7.60 -12.40 -1.0533573 -1.1461603 -8.653357 -13.5461603 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4820 -75500 14750
#> initial value 998.131940
#> iter 2 value 643.390911
#> iter 3 value 643.329266
#> iter 4 value 643.319394
#> iter 5 value 619.128293
#> iter 6 value 615.904256
#> iter 7 value 615.801559
#> iter 8 value 615.800645
#> iter 8 value 615.800638
#> final value 615.800638
#> converged
#> This is Run number 124
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.0343472 0.06696935 -2.2656528 -12.533031 1
#> 2 1 -0.35 -14.40 0.7930312 -0.14813359 0.4430312 -14.548134 1
#> 3 1 -12.20 -2.55 -1.0336850 0.38380674 -13.2336850 -2.166193 2
#> 4 1 -2.30 -13.70 4.3787394 0.82516982 2.0787394 -12.874830 1
#> 5 1 -12.60 -7.80 -0.2368961 -0.08164244 -12.8368961 -7.881642 2
#> 6 1 -7.60 -12.40 0.7670038 -0.06335781 -6.8329962 -12.463358 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4480 -71750 15125
#> initial value 998.131940
#> iter 2 value 677.204008
#> iter 3 value 677.099660
#> iter 4 value 677.060050
#> iter 5 value 657.323585
#> iter 6 value 655.139246
#> iter 7 value 655.087510
#> iter 8 value 655.087203
#> iter 8 value 655.087201
#> final value 655.087201
#> converged
#> This is Run number 125
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.9480504 0.63113886 -2.3519496 -11.968861 1
#> 2 1 -0.35 -14.40 -0.4139098 0.60639499 -0.7639098 -13.793605 1
#> 3 1 -12.20 -2.55 1.8511177 -0.72958903 -10.3488823 -3.279589 2
#> 4 1 -2.30 -13.70 0.7881451 2.75886554 -1.5118549 -10.941134 1
#> 5 1 -12.60 -7.80 1.0620940 0.01457371 -11.5379060 -7.785426 2
#> 6 1 -7.60 -12.40 0.1177052 0.09178419 -7.4822948 -12.308216 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5060 -72650 13200
#> initial value 998.131940
#> iter 2 value 672.148461
#> iter 3 value 671.865730
#> iter 4 value 671.861407
#> iter 5 value 651.674836
#> iter 6 value 649.570788
#> iter 7 value 649.523943
#> iter 8 value 649.523757
#> iter 8 value 649.523756
#> final value 649.523756
#> converged
#> This is Run number 126
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.4718394 0.8333491 -3.828161 -11.766651 1
#> 2 1 -0.35 -14.40 -1.2469715 2.7066545 -1.596972 -11.693345 1
#> 3 1 -12.20 -2.55 1.9029321 -0.6029090 -10.297068 -3.152909 2
#> 4 1 -2.30 -13.70 -0.6829532 2.3317704 -2.982953 -11.368230 1
#> 5 1 -12.60 -7.80 0.1791206 0.5239025 -12.420879 -7.276097 2
#> 6 1 -7.60 -12.40 -0.2994463 -0.6679973 -7.899446 -13.067997 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3720 -70575 13950
#> initial value 998.131940
#> iter 2 value 690.023444
#> iter 3 value 688.653984
#> iter 4 value 688.647995
#> iter 5 value 670.157514
#> iter 6 value 668.193993
#> iter 7 value 668.148600
#> iter 8 value 668.148288
#> iter 8 value 668.148286
#> final value 668.148286
#> converged
#> This is Run number 127
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.69595597 1.9761707 -4.9959560 -10.623829 1
#> 2 1 -0.35 -14.40 -0.05584658 1.0961057 -0.4058466 -13.303894 1
#> 3 1 -12.20 -2.55 1.21020401 0.1311066 -10.9897960 -2.418893 2
#> 4 1 -2.30 -13.70 -0.05634537 -0.1916744 -2.3563454 -13.891674 1
#> 5 1 -12.60 -7.80 -0.29799661 -0.1040438 -12.8979966 -7.904044 2
#> 6 1 -7.60 -12.40 1.31361220 -0.5257167 -6.2863878 -12.925717 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4320 -70250 13950
#> initial value 998.131940
#> iter 2 value 692.586657
#> iter 3 value 692.384122
#> iter 4 value 692.361330
#> iter 5 value 674.567197
#> iter 6 value 672.799311
#> iter 7 value 672.764570
#> iter 8 value 672.764412
#> iter 8 value 672.764411
#> final value 672.764411
#> converged
#> This is Run number 128
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.8078124 -0.09658125 -5.1078124 -12.696581 1
#> 2 1 -0.35 -14.40 -0.5654914 1.02919874 -0.9154914 -13.370801 1
#> 3 1 -12.20 -2.55 2.5777218 0.53584502 -9.6222782 -2.014155 2
#> 4 1 -2.30 -13.70 -0.8243144 2.48364304 -3.1243144 -11.216357 1
#> 5 1 -12.60 -7.80 0.3162301 -0.04761420 -12.2837699 -7.847614 2
#> 6 1 -7.60 -12.40 3.2187953 1.11190485 -4.3812047 -11.288095 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5240 -71200 14600
#> initial value 998.131940
#> iter 2 value 682.588288
#> iter 3 value 682.357146
#> iter 4 value 682.290200
#> iter 5 value 663.402121
#> iter 6 value 661.458719
#> iter 7 value 661.419825
#> iter 8 value 661.419690
#> iter 8 value 661.419690
#> final value 661.419690
#> converged
#> This is Run number 129
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.1946955 0.2484294 -4.1053045 -12.351571 1
#> 2 1 -0.35 -14.40 0.6161706 2.7154075 0.2661706 -11.684592 1
#> 3 1 -12.20 -2.55 1.5662154 -0.1712164 -10.6337846 -2.721216 2
#> 4 1 -2.30 -13.70 0.1828002 0.8343389 -2.1171998 -12.865661 1
#> 5 1 -12.60 -7.80 -0.6890782 2.0875693 -13.2890782 -5.712431 2
#> 6 1 -7.60 -12.40 -0.4944444 1.6751926 -8.0944444 -10.724807 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5160 -73125 14775
#> initial value 998.131940
#> iter 2 value 665.108768
#> iter 3 value 665.036934
#> iter 4 value 665.028478
#> iter 5 value 643.974565
#> iter 6 value 641.558773
#> iter 7 value 641.499842
#> iter 8 value 641.499551
#> iter 8 value 641.499549
#> final value 641.499549
#> converged
#> This is Run number 130
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.59550159 -0.2928421 -4.895502 -12.892842 1
#> 2 1 -0.35 -14.40 0.08731002 1.2809581 -0.262690 -13.119042 1
#> 3 1 -12.20 -2.55 -1.03592424 -0.6915395 -13.235924 -3.241540 2
#> 4 1 -2.30 -13.70 -0.69030870 -0.3917842 -2.990309 -14.091784 1
#> 5 1 -12.60 -7.80 -0.90165192 -0.3708763 -13.501652 -8.170876 2
#> 6 1 -7.60 -12.40 0.07552423 -1.4416450 -7.524476 -13.841645 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4960 -72625 15000
#> initial value 998.131940
#> iter 2 value 669.338905
#> iter 3 value 669.306636
#> iter 4 value 669.289685
#> iter 5 value 648.704760
#> iter 6 value 646.388186
#> iter 7 value 646.332526
#> iter 8 value 646.332240
#> iter 8 value 646.332239
#> final value 646.332239
#> converged
#> This is Run number 131
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.66671573 -0.2468050 -2.633284 -12.846805 1
#> 2 1 -0.35 -14.40 -0.45403897 0.9420127 -0.804039 -13.457987 1
#> 3 1 -12.20 -2.55 0.64346459 0.1994987 -11.556535 -2.350501 2
#> 4 1 -2.30 -13.70 0.51353321 0.7940354 -1.786467 -12.905965 1
#> 5 1 -12.60 -7.80 1.67956001 1.6793512 -10.920440 -6.120649 2
#> 6 1 -7.60 -12.40 0.02121697 2.4636044 -7.578783 -9.936396 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5280 -71850 14200
#> initial value 998.131940
#> iter 2 value 677.521347
#> iter 3 value 677.513686
#> iter 4 value 677.451844
#> iter 5 value 657.880383
#> iter 6 value 655.833098
#> iter 7 value 655.789275
#> iter 8 value 655.789119
#> iter 8 value 655.789118
#> final value 655.789118
#> converged
#> This is Run number 132
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.27195700 -0.8229435 -3.028043 -13.422944 1
#> 2 1 -0.35 -14.40 2.05083846 -0.9737533 1.700838 -15.373753 1
#> 3 1 -12.20 -2.55 1.86296647 3.1218600 -10.337034 0.571860 2
#> 4 1 -2.30 -13.70 -1.32238323 1.2468620 -3.622383 -12.453138 1
#> 5 1 -12.60 -7.80 -0.04033131 -0.1606274 -12.640331 -7.960627 2
#> 6 1 -7.60 -12.40 -0.49740266 0.1819112 -8.097403 -12.218089 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4700 -71400 15425
#> initial value 998.131940
#> iter 2 value 679.598340
#> iter 3 value 679.428531
#> iter 4 value 679.421828
#> iter 5 value 659.949195
#> iter 6 value 657.893219
#> iter 7 value 657.846942
#> iter 8 value 657.846714
#> iter 8 value 657.846713
#> final value 657.846713
#> converged
#> This is Run number 133
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.2301137 1.3813335 -2.0698863 -11.218666 1
#> 2 1 -0.35 -14.40 3.0421824 4.3859682 2.6921824 -10.014032 1
#> 3 1 -12.20 -2.55 0.3401594 0.1975197 -11.8598406 -2.352480 2
#> 4 1 -2.30 -13.70 1.3903424 -0.1889970 -0.9096576 -13.888997 1
#> 5 1 -12.60 -7.80 -0.6689277 0.5173987 -13.2689277 -7.282601 2
#> 6 1 -7.60 -12.40 1.4706244 0.5099422 -6.1293756 -11.890058 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4400 -72675 14825
#> initial value 998.131940
#> iter 2 value 669.532046
#> iter 3 value 669.501862
#> iter 4 value 669.423201
#> iter 5 value 648.535816
#> iter 6 value 646.122488
#> iter 7 value 646.060546
#> iter 8 value 646.060095
#> iter 8 value 646.060092
#> final value 646.060092
#> converged
#> This is Run number 134
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.2797024 -0.93715702 -4.579702 -13.537157 1
#> 2 1 -0.35 -14.40 1.3989375 -0.94420222 1.048937 -15.344202 1
#> 3 1 -12.20 -2.55 0.8054291 -0.51968303 -11.394571 -3.069683 2
#> 4 1 -2.30 -13.70 -0.7168739 1.03286330 -3.016874 -12.667137 1
#> 5 1 -12.60 -7.80 0.6481742 -0.02393271 -11.951826 -7.823933 2
#> 6 1 -7.60 -12.40 2.8647934 0.10867680 -4.735207 -12.291323 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4620 -71375 14125
#> initial value 998.131940
#> iter 2 value 682.275002
#> iter 3 value 682.251390
#> iter 4 value 682.233474
#> iter 5 value 663.264948
#> iter 6 value 661.280833
#> iter 7 value 661.238416
#> iter 8 value 661.238215
#> iter 8 value 661.238213
#> final value 661.238213
#> converged
#> This is Run number 135
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.5901932 1.23332184 -3.70980680 -11.3666782 1
#> 2 1 -0.35 -14.40 -0.6666257 0.62004942 -1.01662571 -13.7799506 1
#> 3 1 -12.20 -2.55 0.1371798 1.57595455 -12.06282020 -0.9740454 2
#> 4 1 -2.30 -13.70 2.2301267 0.01348591 -0.06987327 -13.6865141 1
#> 5 1 -12.60 -7.80 1.3465959 -1.10422403 -11.25340407 -8.9042240 2
#> 6 1 -7.60 -12.40 -0.5991287 1.75289318 -8.19912865 -10.6471068 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4500 -73000 15700
#> initial value 998.131940
#> iter 2 value 664.852174
#> iter 3 value 664.650069
#> iter 4 value 664.605247
#> iter 5 value 643.190348
#> iter 6 value 640.601645
#> iter 7 value 640.530148
#> iter 8 value 640.529607
#> iter 8 value 640.529604
#> final value 640.529604
#> converged
#> This is Run number 136
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.29335122 -0.7778691 -4.5933512 -13.377869 1
#> 2 1 -0.35 -14.40 1.19352672 -0.1634391 0.8435267 -14.563439 1
#> 3 1 -12.20 -2.55 0.27749259 -0.1262973 -11.9225074 -2.676297 2
#> 4 1 -2.30 -13.70 1.38655246 0.5995433 -0.9134475 -13.100457 1
#> 5 1 -12.60 -7.80 0.07778675 -0.3367341 -12.5222133 -8.136734 2
#> 6 1 -7.60 -12.40 0.33085361 2.2784307 -7.2691464 -10.121569 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3860 -70700 15975
#> initial value 998.131940
#> iter 2 value 685.044301
#> iter 3 value 684.397763
#> iter 4 value 684.123806
#> iter 5 value 664.895627
#> iter 6 value 662.738238
#> iter 7 value 662.684041
#> iter 8 value 662.683634
#> iter 8 value 662.683633
#> final value 662.683633
#> converged
#> This is Run number 137
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.27967966 -0.3290996 -4.579680 -12.929100 1
#> 2 1 -0.35 -14.40 1.76398824 -1.1529926 1.413988 -15.552993 1
#> 3 1 -12.20 -2.55 0.49693367 -0.9841467 -11.703066 -3.534147 2
#> 4 1 -2.30 -13.70 0.75477835 -0.1667406 -1.545222 -13.866741 1
#> 5 1 -12.60 -7.80 -0.08638537 -1.4111568 -12.686385 -9.211157 2
#> 6 1 -7.60 -12.40 -0.24008445 2.9252135 -7.840084 -9.474787 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4540 -72150 14975
#> initial value 998.131940
#> iter 2 value 673.892390
#> iter 3 value 673.828824
#> iter 4 value 673.787577
#> iter 5 value 653.675703
#> iter 6 value 651.414429
#> iter 7 value 651.359568
#> iter 8 value 651.359234
#> iter 8 value 651.359232
#> final value 651.359232
#> converged
#> This is Run number 138
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.31744975 -0.60899677 -3.982550 -13.208997 1
#> 2 1 -0.35 -14.40 -0.88789189 1.96731629 -1.237892 -12.432684 1
#> 3 1 -12.20 -2.55 -0.01187162 -1.45826246 -12.211872 -4.008262 2
#> 4 1 -2.30 -13.70 -0.52898896 3.34017318 -2.828989 -10.359827 1
#> 5 1 -12.60 -7.80 -0.13562281 -0.08463198 -12.735623 -7.884632 2
#> 6 1 -7.60 -12.40 1.21283234 0.66395931 -6.387168 -11.736041 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4920 -71425 14875
#> initial value 998.131940
#> iter 2 value 680.303865
#> iter 3 value 680.250992
#> iter 4 value 680.216678
#> iter 5 value 661.014880
#> iter 6 value 658.986238
#> iter 7 value 658.942891
#> iter 8 value 658.942707
#> iter 8 value 658.942706
#> final value 658.942706
#> converged
#> This is Run number 139
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.7878248 0.12788872 -5.087825 -12.4721113 1
#> 2 1 -0.35 -14.40 -0.7671122 -0.02856163 -1.117112 -14.4285616 1
#> 3 1 -12.20 -2.55 0.1304002 2.93644257 -12.069600 0.3864426 2
#> 4 1 -2.30 -13.70 -0.7773845 0.56851191 -3.077385 -13.1314881 1
#> 5 1 -12.60 -7.80 -0.8344096 0.85364481 -13.434410 -6.9463552 2
#> 6 1 -7.60 -12.40 -1.3177526 2.22243996 -8.917753 -10.1775600 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4480 -70650 14475
#> initial value 998.131940
#> iter 2 value 688.099465
#> iter 3 value 688.065668
#> iter 4 value 688.036817
#> iter 5 value 669.714281
#> iter 6 value 667.848109
#> iter 7 value 667.809793
#> iter 8 value 667.809614
#> iter 8 value 667.809613
#> final value 667.809613
#> converged
#> This is Run number 140
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.7765702 -0.1047593 -3.5234298 -12.704759 1
#> 2 1 -0.35 -14.40 -0.4351653 0.7506834 -0.7851653 -13.649317 1
#> 3 1 -12.20 -2.55 -0.3108520 -0.4376633 -12.5108520 -2.987663 2
#> 4 1 -2.30 -13.70 0.6088211 1.7222420 -1.6911789 -11.977758 1
#> 5 1 -12.60 -7.80 -0.8233494 1.8325024 -13.4233494 -5.967498 2
#> 6 1 -7.60 -12.40 1.4469732 -0.1499146 -6.1530268 -12.549915 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5140 -70725 14050
#> initial value 998.131940
#> iter 2 value 687.799344
#> iter 3 value 687.759638
#> iter 4 value 687.712750
#> iter 5 value 669.451430
#> iter 6 value 667.653832
#> iter 7 value 667.619452
#> iter 8 value 667.619346
#> iter 8 value 667.619345
#> final value 667.619345
#> converged
#> This is Run number 141
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.2631652 0.68002772 -3.0368348 -11.91997228 1
#> 2 1 -0.35 -14.40 2.0737016 -0.08883125 1.7237016 -14.48883125 1
#> 3 1 -12.20 -2.55 -0.7717540 2.61503756 -12.9717540 0.06503756 2
#> 4 1 -2.30 -13.70 2.1610654 -0.14422338 -0.1389346 -13.84422338 1
#> 5 1 -12.60 -7.80 0.5529222 -0.79062249 -12.0470778 -8.59062249 2
#> 6 1 -7.60 -12.40 0.6372235 0.80660566 -6.9627765 -11.59339434 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4620 -72400 13550
#> initial value 998.131940
#> iter 2 value 674.105598
#> iter 3 value 673.909892
#> iter 4 value 673.773670
#> iter 5 value 653.787559
#> iter 6 value 651.580921
#> iter 7 value 651.530079
#> iter 8 value 651.529809
#> iter 8 value 651.529808
#> final value 651.529808
#> converged
#> This is Run number 142
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.5149659 2.0863645 -4.81496588 -10.513635 1
#> 2 1 -0.35 -14.40 0.3863056 2.5543798 0.03630558 -11.845620 1
#> 3 1 -12.20 -2.55 0.8166794 1.4275621 -11.38332059 -1.122438 2
#> 4 1 -2.30 -13.70 2.7340861 -0.8661054 0.43408607 -14.566105 1
#> 5 1 -12.60 -7.80 -0.6792844 2.0539064 -13.27928436 -5.746094 2
#> 6 1 -7.60 -12.40 1.2217170 3.3939853 -6.37828302 -9.006015 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5120 -71000 13425
#> initial value 998.131940
#> iter 2 value 686.445726
#> iter 3 value 686.314381
#> iter 4 value 686.282576
#> iter 5 value 667.969789
#> iter 6 value 666.159432
#> iter 7 value 666.125430
#> iter 8 value 666.125329
#> iter 8 value 666.125329
#> final value 666.125329
#> converged
#> This is Run number 143
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.9654693 -0.6692138 -2.3345307 -13.269214 1
#> 2 1 -0.35 -14.40 -0.3003094 -0.6559766 -0.6503094 -15.055977 1
#> 3 1 -12.20 -2.55 1.7764987 0.7943938 -10.4235013 -1.755606 2
#> 4 1 -2.30 -13.70 1.1770899 3.2047646 -1.1229101 -10.495235 1
#> 5 1 -12.60 -7.80 0.6746840 0.8663431 -11.9253160 -6.933657 2
#> 6 1 -7.60 -12.40 2.1272159 0.6782199 -5.4727841 -11.721780 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4520 -73350 14900
#> initial value 998.131940
#> iter 2 value 663.210909
#> iter 3 value 663.165560
#> iter 4 value 663.107763
#> iter 5 value 641.501494
#> iter 6 value 638.909167
#> iter 7 value 638.839049
#> iter 8 value 638.838517
#> iter 8 value 638.838513
#> final value 638.838513
#> converged
#> This is Run number 144
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.1310684 0.6898474 -4.4310684 -11.910153 1
#> 2 1 -0.35 -14.40 0.2391455 -0.4105565 -0.1108545 -14.810556 1
#> 3 1 -12.20 -2.55 -0.2647018 0.5893263 -12.4647018 -1.960674 2
#> 4 1 -2.30 -13.70 -0.1570543 0.9994503 -2.4570543 -12.700550 1
#> 5 1 -12.60 -7.80 1.4439362 1.6199780 -11.1560638 -6.180022 2
#> 6 1 -7.60 -12.40 -1.3391717 3.8023081 -8.9391717 -8.597692 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4460 -71925 14125
#> initial value 998.131940
#> iter 2 value 677.479978
#> iter 3 value 677.366412
#> iter 4 value 677.302252
#> iter 5 value 657.624527
#> iter 6 value 655.478583
#> iter 7 value 655.428582
#> iter 8 value 655.428298
#> iter 8 value 655.428296
#> final value 655.428296
#> converged
#> This is Run number 145
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.3041292 0.3649441 -4.6041292 -12.2350559 1
#> 2 1 -0.35 -14.40 1.0422511 -0.2453480 0.6922511 -14.6453480 1
#> 3 1 -12.20 -2.55 0.5536114 2.0939022 -11.6463886 -0.4560978 2
#> 4 1 -2.30 -13.70 0.7049679 -0.1615816 -1.5950321 -13.8615816 1
#> 5 1 -12.60 -7.80 0.8245243 0.2457567 -11.7754757 -7.5542433 2
#> 6 1 -7.60 -12.40 0.5956454 -0.2427791 -7.0043546 -12.6427791 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4700 -72425 13750
#> initial value 998.131940
#> iter 2 value 673.508269
#> iter 3 value 673.388935
#> iter 4 value 673.313461
#> iter 5 value 653.292576
#> iter 6 value 651.082929
#> iter 7 value 651.032108
#> iter 8 value 651.031846
#> iter 8 value 651.031844
#> final value 651.031844
#> converged
#> This is Run number 146
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.9101469 1.6795209 -5.210147 -10.920479 1
#> 2 1 -0.35 -14.40 -0.8579039 1.0242564 -1.207904 -13.375744 1
#> 3 1 -12.20 -2.55 0.6887534 -0.7528417 -11.511247 -3.302842 2
#> 4 1 -2.30 -13.70 -0.8099787 -0.6121659 -3.109979 -14.312166 1
#> 5 1 -12.60 -7.80 -0.2361193 1.1751577 -12.836119 -6.624842 2
#> 6 1 -7.60 -12.40 1.7102441 -0.1036052 -5.889756 -12.503605 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3700 -68725 14675
#> initial value 998.131940
#> iter 2 value 704.635747
#> iter 3 value 704.263860
#> iter 4 value 703.975268
#> iter 5 value 687.055676
#> iter 6 value 685.433058
#> iter 7 value 685.400510
#> iter 8 value 685.400325
#> iter 8 value 685.400325
#> final value 685.400325
#> converged
#> This is Run number 147
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.7553834 -1.1489860 -6.0553834 -13.7489860 1
#> 2 1 -0.35 -14.40 2.1778001 -0.1842180 1.8278001 -14.5842180 1
#> 3 1 -12.20 -2.55 1.1679462 1.8345561 -11.0320538 -0.7154439 2
#> 4 1 -2.30 -13.70 1.3360072 0.3624138 -0.9639928 -13.3375862 1
#> 5 1 -12.60 -7.80 0.7760780 -1.1202545 -11.8239220 -8.9202545 2
#> 6 1 -7.60 -12.40 -0.9404525 1.0275603 -8.5404525 -11.3724397 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4880 -74400 15925
#> initial value 998.131940
#> iter 2 value 651.361779
#> iter 3 value 651.206584
#> iter 4 value 651.205201
#> iter 5 value 627.663479
#> iter 6 value 625.090314
#> iter 7 value 625.011316
#> iter 8 value 625.010743
#> iter 8 value 625.010738
#> final value 625.010738
#> converged
#> This is Run number 148
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.04289817 0.582454082 -4.3428982 -12.017546 1
#> 2 1 -0.35 -14.40 -0.23261891 2.081979148 -0.5826189 -12.318021 1
#> 3 1 -12.20 -2.55 -0.08630852 -1.067332344 -12.2863085 -3.617332 2
#> 4 1 -2.30 -13.70 -0.53131955 -0.008140184 -2.8313196 -13.708140 1
#> 5 1 -12.60 -7.80 1.28124375 -0.620085952 -11.3187562 -8.420086 2
#> 6 1 -7.60 -12.40 1.33241610 2.145865358 -6.2675839 -10.254135 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4720 -70500 13325
#> initial value 998.131940
#> iter 2 value 691.228978
#> iter 3 value 691.119049
#> iter 4 value 691.097348
#> iter 5 value 673.283978
#> iter 6 value 671.557995
#> iter 7 value 671.525923
#> iter 8 value 671.525811
#> iter 8 value 671.525810
#> final value 671.525810
#> converged
#> This is Run number 149
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.2902735 0.02694508 -4.009727 -12.5730549 1
#> 2 1 -0.35 -14.40 2.3176224 -0.10790472 1.967622 -14.5079047 1
#> 3 1 -12.20 -2.55 -0.3279915 2.12315290 -12.527992 -0.4268471 2
#> 4 1 -2.30 -13.70 -0.2716400 0.29448761 -2.571640 -13.4055124 1
#> 5 1 -12.60 -7.80 0.4602302 -0.08540876 -12.139770 -7.8854088 2
#> 6 1 -7.60 -12.40 0.9480918 2.63116077 -6.651908 -9.7688392 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5080 -70775 14150
#> initial value 998.131940
#> iter 2 value 687.228038
#> iter 3 value 687.149224
#> iter 4 value 687.121361
#> iter 5 value 668.845086
#> iter 6 value 667.027681
#> iter 7 value 666.992864
#> iter 8 value 666.992752
#> iter 8 value 666.992751
#> final value 666.992751
#> converged
#> This is Run number 150
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.65494513 -0.08476067 -3.6450549 -12.684761 1
#> 2 1 -0.35 -14.40 -0.63763722 2.81818747 -0.9876372 -11.581813 1
#> 3 1 -12.20 -2.55 1.77293861 -0.92229854 -10.4270614 -3.472299 2
#> 4 1 -2.30 -13.70 -0.09104909 -0.45126394 -2.3910491 -14.151264 1
#> 5 1 -12.60 -7.80 0.98786739 -0.80553946 -11.6121326 -8.605539 2
#> 6 1 -7.60 -12.40 0.63962847 0.14147601 -6.9603715 -12.258524 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4620 -71400 15100
#> initial value 998.131940
#> iter 2 value 680.275501
#> iter 3 value 680.188416
#> iter 4 value 680.186458
#> iter 5 value 660.696396
#> iter 6 value 658.804549
#> iter 7 value 658.762017
#> iter 8 value 658.761810
#> iter 8 value 658.761809
#> final value 658.761809
#> converged
#> This is Run number 151
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.9148443 -0.6365783 -3.385156 -13.236578 1
#> 2 1 -0.35 -14.40 1.0807910 -0.1083853 0.730791 -14.508385 1
#> 3 1 -12.20 -2.55 0.7693954 -0.7736653 -11.430605 -3.323665 2
#> 4 1 -2.30 -13.70 0.8478701 0.3665293 -1.452130 -13.333471 1
#> 5 1 -12.60 -7.80 0.4562552 1.8355623 -12.143745 -5.964438 2
#> 6 1 -7.60 -12.40 -0.5091964 2.9186368 -8.109196 -9.481363 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4220 -73225 14050
#> initial value 998.131940
#> iter 2 value 666.015403
#> iter 3 value 665.663513
#> iter 4 value 665.425616
#> iter 5 value 643.850421
#> iter 6 value 641.294885
#> iter 7 value 641.222126
#> iter 8 value 641.221530
#> iter 8 value 641.221526
#> final value 641.221526
#> converged
#> This is Run number 152
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.0026360 0.5978019 -5.3026360 -12.002198 1
#> 2 1 -0.35 -14.40 -0.4396016 0.7990781 -0.7896016 -13.600922 1
#> 3 1 -12.20 -2.55 1.3380510 0.3005834 -10.8619490 -2.249417 2
#> 4 1 -2.30 -13.70 -0.4030157 -0.3320018 -2.7030157 -14.032002 1
#> 5 1 -12.60 -7.80 1.5794629 1.3540474 -11.0205371 -6.445953 2
#> 6 1 -7.60 -12.40 -0.6492556 1.3723590 -8.2492556 -11.027641 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4640 -71775 15350
#> initial value 998.131940
#> iter 2 value 676.458922
#> iter 3 value 676.328275
#> iter 4 value 676.327740
#> iter 5 value 655.726753
#> iter 6 value 654.307704
#> iter 7 value 654.273211
#> iter 8 value 654.273058
#> iter 8 value 654.273057
#> final value 654.273057
#> converged
#> This is Run number 153
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.821861609 5.0473604 -5.1218616 -7.552640 1
#> 2 1 -0.35 -14.40 -0.086994771 2.5697198 -0.4369948 -11.830280 1
#> 3 1 -12.20 -2.55 0.008440027 0.2978715 -12.1915600 -2.252128 2
#> 4 1 -2.30 -13.70 0.856807053 1.0950574 -1.4431929 -12.604943 1
#> 5 1 -12.60 -7.80 -0.728581523 2.9070998 -13.3285815 -4.892900 2
#> 6 1 -7.60 -12.40 0.502488211 -0.2061979 -7.0975118 -12.606198 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4200 -70750 13550
#> initial value 998.131940
#> iter 2 value 688.956529
#> iter 3 value 688.729153
#> iter 4 value 688.558517
#> iter 5 value 670.089216
#> iter 6 value 668.195598
#> iter 7 value 668.154685
#> iter 8 value 668.154464
#> iter 8 value 668.154462
#> final value 668.154462
#> converged
#> This is Run number 154
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.1223675 -0.67587448 -5.422368 -13.275874 1
#> 2 1 -0.35 -14.40 -0.8926801 0.83742035 -1.242680 -13.562580 1
#> 3 1 -12.20 -2.55 -0.8467915 0.60786185 -13.046791 -1.942138 2
#> 4 1 -2.30 -13.70 -0.7761472 0.02295891 -3.076147 -13.677041 1
#> 5 1 -12.60 -7.80 -0.3397418 -0.23191003 -12.939742 -8.031910 2
#> 6 1 -7.60 -12.40 1.4265313 -0.43939890 -6.173469 -12.839399 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4500 -73200 14650
#> initial value 998.131940
#> iter 2 value 665.046924
#> iter 3 value 664.814926
#> iter 4 value 664.808282
#> iter 5 value 643.550031
#> iter 6 value 641.027749
#> iter 7 value 640.960194
#> iter 8 value 640.959704
#> iter 8 value 640.959701
#> final value 640.959701
#> converged
#> This is Run number 155
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.13865679 0.44025251 -3.1613432 -12.159747 1
#> 2 1 -0.35 -14.40 -0.04448577 -0.87251433 -0.3944858 -15.272514 1
#> 3 1 -12.20 -2.55 0.74189477 0.21784079 -11.4581052 -2.332159 2
#> 4 1 -2.30 -13.70 0.11336217 0.08224710 -2.1866378 -13.617753 1
#> 5 1 -12.60 -7.80 1.50577217 0.01996436 -11.0942278 -7.780036 2
#> 6 1 -7.60 -12.40 0.76157878 -0.24158888 -6.8384212 -12.641589 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4740 -72150 13925
#> initial value 998.131940
#> iter 2 value 675.658545
#> iter 3 value 675.599570
#> iter 4 value 675.564129
#> iter 5 value 655.829991
#> iter 6 value 653.690768
#> iter 7 value 653.642883
#> iter 8 value 653.642650
#> iter 8 value 653.642648
#> final value 653.642648
#> converged
#> This is Run number 156
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.51269529 -0.2480392 -1.7873047 -12.8480392 1
#> 2 1 -0.35 -14.40 -0.64826572 2.9491297 -0.9982657 -11.4508703 1
#> 3 1 -12.20 -2.55 -0.57112629 2.0871048 -12.7711263 -0.4628952 2
#> 4 1 -2.30 -13.70 0.17935886 1.7286640 -2.1206411 -11.9713360 1
#> 5 1 -12.60 -7.80 -0.13894136 0.5748695 -12.7389414 -7.2251305 2
#> 6 1 -7.60 -12.40 -0.08039216 2.3605043 -7.6803922 -10.0394957 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4480 -71175 15675
#> initial value 998.131940
#> iter 2 value 681.203849
#> iter 3 value 680.921110
#> iter 4 value 680.917804
#> iter 5 value 661.467890
#> iter 6 value 659.466560
#> iter 7 value 659.420323
#> iter 8 value 659.420074
#> iter 8 value 659.420072
#> final value 659.420072
#> converged
#> This is Run number 157
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 3.4840357 -0.5201030 -0.8159643 -13.1201030 1
#> 2 1 -0.35 -14.40 0.1836715 -0.5757444 -0.1663285 -14.9757444 1
#> 3 1 -12.20 -2.55 -0.3590311 1.7406949 -12.5590311 -0.8093051 2
#> 4 1 -2.30 -13.70 1.7634622 0.3244887 -0.5365378 -13.3755113 1
#> 5 1 -12.60 -7.80 3.4325241 -0.9377754 -9.1674759 -8.7377754 2
#> 6 1 -7.60 -12.40 -0.3466800 -1.0259762 -7.9466800 -13.4259762 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4560 -73275 14700
#> initial value 998.131940
#> iter 2 value 664.241485
#> iter 3 value 664.076954
#> iter 4 value 664.063122
#> iter 5 value 642.730604
#> iter 6 value 640.189107
#> iter 7 value 640.121211
#> iter 8 value 640.120726
#> iter 8 value 640.120723
#> final value 640.120723
#> converged
#> This is Run number 158
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.4874761 -0.8544178 -4.787476 -13.4544178 1
#> 2 1 -0.35 -14.40 -0.7100143 6.4017214 -1.060014 -7.9982786 1
#> 3 1 -12.20 -2.55 -0.4079120 2.5144204 -12.607912 -0.0355796 2
#> 4 1 -2.30 -13.70 0.3303804 1.8183807 -1.969620 -11.8816193 1
#> 5 1 -12.60 -7.80 1.2311948 2.5134081 -11.368805 -5.2865919 2
#> 6 1 -7.60 -12.40 0.6682557 1.9263045 -6.931744 -10.4736955 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4120 -72450 15400
#> initial value 998.131940
#> iter 2 value 670.595904
#> iter 3 value 670.305587
#> iter 4 value 670.051710
#> iter 5 value 649.186830
#> iter 6 value 646.695516
#> iter 7 value 646.626109
#> iter 8 value 646.625518
#> iter 8 value 646.625514
#> final value 646.625514
#> converged
#> This is Run number 159
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.2295024 0.7629414 -4.5295024 -11.837059 1
#> 2 1 -0.35 -14.40 -0.5216845 -0.2318673 -0.8716845 -14.631867 1
#> 3 1 -12.20 -2.55 -0.1303750 -0.2594968 -12.3303750 -2.809497 2
#> 4 1 -2.30 -13.70 -0.3253398 0.6189729 -2.6253398 -13.081027 1
#> 5 1 -12.60 -7.80 -0.8969745 -1.4024190 -13.4969745 -9.202419 2
#> 6 1 -7.60 -12.40 -0.5500227 -1.4433131 -8.1500227 -13.843313 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4880 -71575 12875
#> initial value 998.131940
#> iter 2 value 682.377070
#> iter 3 value 682.041081
#> iter 4 value 682.010264
#> iter 5 value 663.141396
#> iter 6 value 661.212238
#> iter 7 value 661.173381
#> iter 8 value 661.173239
#> iter 8 value 661.173239
#> final value 661.173239
#> converged
#> This is Run number 160
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.2435469 3.7533674 -4.54354690 -8.8466326 1
#> 2 1 -0.35 -14.40 0.3250639 -0.4465334 -0.02493607 -14.8465334 1
#> 3 1 -12.20 -2.55 0.3005122 2.8853998 -11.89948781 0.3353998 2
#> 4 1 -2.30 -13.70 -1.0353309 2.7472211 -3.33533090 -10.9527789 1
#> 5 1 -12.60 -7.80 -0.4022623 0.1709376 -13.00226229 -7.6290624 2
#> 6 1 -7.60 -12.40 -0.1255575 2.2943141 -7.72555748 -10.1056859 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4380 -72600 14525
#> initial value 998.131940
#> iter 2 value 670.765863
#> iter 3 value 670.442874
#> iter 4 value 670.435706
#> iter 5 value 649.881864
#> iter 6 value 647.514057
#> iter 7 value 647.453483
#> iter 8 value 647.453061
#> iter 8 value 647.453058
#> final value 647.453058
#> converged
#> This is Run number 161
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 5.2974319 0.4552655 0.9974319 -12.1447345 1
#> 2 1 -0.35 -14.40 -0.9151568 -0.6546598 -1.2651568 -15.0546598 1
#> 3 1 -12.20 -2.55 -0.1659654 2.0039236 -12.3659654 -0.5460764 2
#> 4 1 -2.30 -13.70 1.9411675 1.0461812 -0.3588325 -12.6538188 1
#> 5 1 -12.60 -7.80 1.5759054 2.2645080 -11.0240946 -5.5354920 2
#> 6 1 -7.60 -12.40 -0.6573767 1.1925002 -8.2573767 -11.2074998 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4260 -71925 15300
#> initial value 998.131940
#> iter 2 value 675.421304
#> iter 3 value 675.216607
#> iter 4 value 675.074020
#> iter 5 value 654.980001
#> iter 6 value 652.681705
#> iter 7 value 652.623374
#> iter 8 value 652.622959
#> iter 8 value 652.622957
#> final value 652.622957
#> converged
#> This is Run number 162
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.5485606 2.3713330 -1.751439 -10.228667 1
#> 2 1 -0.35 -14.40 -0.9752324 3.4269318 -1.325232 -10.973068 1
#> 3 1 -12.20 -2.55 -0.5274210 0.1392025 -12.727421 -2.410797 2
#> 4 1 -2.30 -13.70 -1.4777762 -1.0883913 -3.777776 -14.788391 1
#> 5 1 -12.60 -7.80 0.8014244 -1.1547255 -11.798576 -8.954726 2
#> 6 1 -7.60 -12.40 0.7533994 2.0134762 -6.846601 -10.386524 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3760 -70300 14300
#> initial value 998.131940
#> iter 2 value 691.793004
#> iter 3 value 690.972935
#> iter 4 value 690.765357
#> iter 5 value 672.469514
#> iter 6 value 670.561856
#> iter 7 value 670.519343
#> iter 8 value 670.519036
#> iter 8 value 670.519034
#> final value 670.519034
#> converged
#> This is Run number 163
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.4597021 1.2402613 -3.840298 -11.359739 1
#> 2 1 -0.35 -14.40 -1.3676653 -0.8989451 -1.717665 -15.298945 1
#> 3 1 -12.20 -2.55 -1.0878410 0.8431786 -13.287841 -1.706821 2
#> 4 1 -2.30 -13.70 0.1265327 0.1378865 -2.173467 -13.562114 1
#> 5 1 -12.60 -7.80 -0.8135969 -1.2019778 -13.413597 -9.001978 2
#> 6 1 -7.60 -12.40 -0.4602961 -0.2363082 -8.060296 -12.636308 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4660 -72325 14850
#> initial value 998.131940
#> iter 2 value 672.493514
#> iter 3 value 672.465082
#> iter 4 value 672.447353
#> iter 5 value 652.205988
#> iter 6 value 649.944219
#> iter 7 value 649.889757
#> iter 8 value 649.889444
#> iter 8 value 649.889442
#> final value 649.889442
#> converged
#> This is Run number 164
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.2348359 1.6509687 -5.5348359 -10.949031 1
#> 2 1 -0.35 -14.40 -0.1128475 -0.7947628 -0.4628475 -15.194763 1
#> 3 1 -12.20 -2.55 1.3462656 1.5071632 -10.8537344 -1.042837 2
#> 4 1 -2.30 -13.70 -0.4561760 0.5365100 -2.7561760 -13.163490 1
#> 5 1 -12.60 -7.80 0.7002899 1.6520872 -11.8997101 -6.147913 2
#> 6 1 -7.60 -12.40 0.4383317 -0.2556391 -7.1616683 -12.655639 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4620 -71000 13825
#> initial value 998.131940
#> iter 2 value 686.091336
#> iter 3 value 686.046073
#> iter 4 value 686.009215
#> iter 5 value 667.537234
#> iter 6 value 665.658996
#> iter 7 value 665.621254
#> iter 8 value 665.621093
#> iter 8 value 665.621092
#> final value 665.621092
#> converged
#> This is Run number 165
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.8175715 0.6533270 -3.48242854 -11.946673 1
#> 2 1 -0.35 -14.40 0.4219446 0.6725856 0.07194459 -13.727414 1
#> 3 1 -12.20 -2.55 0.2460381 0.7385864 -11.95396193 -1.811414 2
#> 4 1 -2.30 -13.70 0.4072737 -1.3041778 -1.89272631 -15.004178 1
#> 5 1 -12.60 -7.80 0.7770256 -0.8187950 -11.82297440 -8.618795 2
#> 6 1 -7.60 -12.40 1.3113565 1.0973385 -6.28864351 -11.302661 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4520 -71925 14000
#> initial value 998.131940
#> iter 2 value 677.663077
#> iter 3 value 677.578797
#> iter 4 value 677.557553
#> iter 5 value 657.887583
#> iter 6 value 655.761983
#> iter 7 value 655.714357
#> iter 8 value 655.714099
#> iter 8 value 655.714097
#> final value 655.714097
#> converged
#> This is Run number 166
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.4452365 -0.564918016 -3.854763 -13.164918 1
#> 2 1 -0.35 -14.40 1.3299940 -0.458718858 0.979994 -14.858719 1
#> 3 1 -12.20 -2.55 0.3326553 -0.339802038 -11.867345 -2.889802 2
#> 4 1 -2.30 -13.70 -0.6755814 -0.119068367 -2.975581 -13.819068 1
#> 5 1 -12.60 -7.80 1.2631513 -0.002986249 -11.336849 -7.802986 2
#> 6 1 -7.60 -12.40 0.1578207 -0.215374304 -7.442179 -12.615374 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4540 -71100 14375
#> initial value 998.131940
#> iter 2 value 684.303517
#> iter 3 value 684.277306
#> iter 4 value 684.259542
#> iter 5 value 665.492578
#> iter 6 value 663.544876
#> iter 7 value 663.504041
#> iter 8 value 663.503844
#> iter 8 value 663.503842
#> final value 663.503842
#> converged
#> This is Run number 167
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.33702985 0.08161181 -3.962970 -12.518388 1
#> 2 1 -0.35 -14.40 2.76420299 -0.23664615 2.414203 -14.636646 1
#> 3 1 -12.20 -2.55 1.05472728 0.41738433 -11.145273 -2.132616 2
#> 4 1 -2.30 -13.70 -0.09981151 1.97483352 -2.399812 -11.725166 1
#> 5 1 -12.60 -7.80 1.04327900 1.08478203 -11.556721 -6.715218 2
#> 6 1 -7.60 -12.40 3.22683735 0.93740441 -4.373163 -11.462596 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5240 -71975 14675
#> initial value 998.131940
#> iter 2 value 675.585355
#> iter 3 value 675.391502
#> iter 4 value 675.351973
#> iter 5 value 655.629710
#> iter 6 value 653.505527
#> iter 7 value 653.459620
#> iter 8 value 653.459440
#> iter 8 value 653.459439
#> final value 653.459439
#> converged
#> This is Run number 168
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.3281997 -0.49019446 -2.9718003 -13.090194 1
#> 2 1 -0.35 -14.40 0.7256436 -1.09597421 0.3756436 -15.495974 1
#> 3 1 -12.20 -2.55 1.4115340 0.87407192 -10.7884660 -1.675928 2
#> 4 1 -2.30 -13.70 -0.2659431 0.09060749 -2.5659431 -13.609393 1
#> 5 1 -12.60 -7.80 0.4342076 0.77153565 -12.1657924 -7.028464 2
#> 6 1 -7.60 -12.40 -0.9953813 0.11850567 -8.5953813 -12.281494 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5240 -71175 14225
#> initial value 998.131940
#> iter 2 value 683.479791
#> iter 3 value 683.295933
#> iter 4 value 683.249194
#> iter 5 value 664.527198
#> iter 6 value 662.623059
#> iter 7 value 662.585458
#> iter 8 value 662.585337
#> iter 8 value 662.585337
#> final value 662.585337
#> converged
#> This is Run number 169
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.8429311 0.2084134 -2.4570689 -12.391587 1
#> 2 1 -0.35 -14.40 -0.3761201 0.2004885 -0.7261201 -14.199512 1
#> 3 1 -12.20 -2.55 -0.9279235 0.1594229 -13.1279235 -2.390577 2
#> 4 1 -2.30 -13.70 1.0642054 0.7053981 -1.2357946 -12.994602 1
#> 5 1 -12.60 -7.80 2.8589646 -0.7925651 -9.7410354 -8.592565 2
#> 6 1 -7.60 -12.40 0.4572408 -1.7414903 -7.1427592 -14.141490 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4800 -73275 14125
#> initial value 998.131940
#> iter 2 value 665.126207
#> iter 3 value 665.061457
#> iter 4 value 665.017996
#> iter 5 value 643.932004
#> iter 6 value 641.485130
#> iter 7 value 641.423754
#> iter 8 value 641.423397
#> iter 8 value 641.423394
#> final value 641.423394
#> converged
#> This is Run number 170
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.3614052 -1.0454146 -4.66140518 -13.645415 1
#> 2 1 -0.35 -14.40 0.3223096 0.4866570 -0.02769045 -13.913343 1
#> 3 1 -12.20 -2.55 1.0165134 0.4122403 -11.18348661 -2.137760 2
#> 4 1 -2.30 -13.70 3.4910452 1.6543241 1.19104520 -12.045676 1
#> 5 1 -12.60 -7.80 -0.6799073 3.8709823 -13.27990726 -3.929018 2
#> 6 1 -7.60 -12.40 -0.2897774 1.8086352 -7.88977740 -10.591365 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4060 -72425 14750
#> initial value 998.131940
#> iter 2 value 672.082404
#> iter 3 value 671.601913
#> iter 4 value 671.413582
#> iter 5 value 650.708368
#> iter 6 value 648.290722
#> iter 7 value 648.226183
#> iter 8 value 648.225618
#> iter 8 value 648.225614
#> final value 648.225614
#> converged
#> This is Run number 171
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.9283484 2.4941883 -3.371652 -10.105812 1
#> 2 1 -0.35 -14.40 -0.9516003 -0.4211836 -1.301600 -14.821184 1
#> 3 1 -12.20 -2.55 -0.6193483 -0.2284467 -12.819348 -2.778447 2
#> 4 1 -2.30 -13.70 1.0881934 0.5153753 -1.211807 -13.184625 1
#> 5 1 -12.60 -7.80 1.2078207 0.5453656 -11.392179 -7.254634 2
#> 6 1 -7.60 -12.40 3.4553326 -0.4327057 -4.144667 -12.832706 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4460 -72875 13825
#> initial value 998.131940
#> iter 2 value 669.454174
#> iter 3 value 669.242871
#> iter 4 value 669.085258
#> iter 5 value 648.291673
#> iter 6 value 645.911378
#> iter 7 value 645.852125
#> iter 8 value 645.851737
#> iter 8 value 645.851734
#> final value 645.851734
#> converged
#> This is Run number 172
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.4380081 2.5579731 -3.861992 -10.042027 1
#> 2 1 -0.35 -14.40 1.4385517 -0.4677201 1.088552 -14.867720 1
#> 3 1 -12.20 -2.55 2.3440536 0.5655840 -9.855946 -1.984416 2
#> 4 1 -2.30 -13.70 -0.3798884 1.8856666 -2.679888 -11.814333 1
#> 5 1 -12.60 -7.80 -0.4209000 1.2172323 -13.020900 -6.582768 2
#> 6 1 -7.60 -12.40 -0.1687302 3.2458947 -7.768730 -9.154105 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4220 -70725 14825
#> initial value 998.131940
#> iter 2 value 686.933835
#> iter 3 value 686.791147
#> iter 4 value 686.669429
#> iter 5 value 668.047829
#> iter 6 value 666.087206
#> iter 7 value 666.043922
#> iter 8 value 666.043672
#> iter 8 value 666.043671
#> final value 666.043671
#> converged
#> This is Run number 173
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.3698790 -1.00197488 -3.9301210 -13.601975 1
#> 2 1 -0.35 -14.40 1.2888287 -0.89792293 0.9388287 -15.297923 1
#> 3 1 -12.20 -2.55 0.7671839 1.51365202 -11.4328161 -1.036348 2
#> 4 1 -2.30 -13.70 1.0929633 1.02563537 -1.2070367 -12.674365 1
#> 5 1 -12.60 -7.80 -1.5396368 0.28486715 -14.1396368 -7.515133 2
#> 6 1 -7.60 -12.40 2.4313707 0.06493235 -5.1686293 -12.335068 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5060 -74050 13975
#> initial value 998.131940
#> iter 2 value 658.121526
#> iter 3 value 658.008689
#> iter 4 value 658.002734
#> iter 5 value 635.995748
#> iter 6 value 633.444708
#> iter 7 value 633.377819
#> iter 8 value 633.377448
#> iter 8 value 633.377446
#> final value 633.377446
#> converged
#> This is Run number 174
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.0738348 -0.4832298 -4.3738348 -13.083230 1
#> 2 1 -0.35 -14.40 -0.1450632 -1.0931309 -0.4950632 -15.493131 1
#> 3 1 -12.20 -2.55 -0.5989270 -0.6010766 -12.7989270 -3.151077 2
#> 4 1 -2.30 -13.70 2.4668510 1.3890932 0.1668510 -12.310907 1
#> 5 1 -12.60 -7.80 0.6138884 -0.2477561 -11.9861116 -8.047756 2
#> 6 1 -7.60 -12.40 1.2929868 1.4813674 -6.3070132 -10.918633 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4500 -69900 14750
#> initial value 998.131940
#> iter 2 value 694.091043
#> iter 3 value 694.017458
#> iter 4 value 694.013313
#> iter 5 value 676.318001
#> iter 6 value 674.652764
#> iter 7 value 674.620761
#> iter 8 value 674.620632
#> iter 8 value 674.620631
#> final value 674.620631
#> converged
#> This is Run number 175
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.1240418 -0.43566497 -3.175958 -13.035665 1
#> 2 1 -0.35 -14.40 5.5288426 -0.19438872 5.178843 -14.594389 1
#> 3 1 -12.20 -2.55 0.5795129 -0.18231886 -11.620487 -2.732319 2
#> 4 1 -2.30 -13.70 1.4069420 -0.09548331 -0.893058 -13.795483 1
#> 5 1 -12.60 -7.80 0.1577814 2.28395018 -12.442219 -5.516050 2
#> 6 1 -7.60 -12.40 1.7066830 -1.12353553 -5.893317 -13.523536 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4640 -71950 15925
#> initial value 998.131940
#> iter 2 value 673.747294
#> iter 3 value 673.428578
#> iter 4 value 673.425546
#> iter 5 value 653.018309
#> iter 6 value 650.839522
#> iter 7 value 650.785603
#> iter 8 value 650.785296
#> iter 8 value 650.785294
#> final value 650.785294
#> converged
#> This is Run number 176
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.5344707 2.893220278 -3.7655293 -9.7067797 1
#> 2 1 -0.35 -14.40 -0.1001746 0.002601313 -0.4501746 -14.3973987 1
#> 3 1 -12.20 -2.55 3.3116481 3.219763768 -8.8883519 0.6697638 2
#> 4 1 -2.30 -13.70 0.2867954 0.071779453 -2.0132046 -13.6282205 1
#> 5 1 -12.60 -7.80 -0.8689551 2.093878204 -13.4689551 -5.7061218 2
#> 6 1 -7.60 -12.40 0.1123852 -0.965635679 -7.4876148 -13.3656357 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4660 -73125 13575
#> initial value 998.131940
#> iter 2 value 667.489516
#> iter 3 value 667.251216
#> iter 4 value 667.091586
#> iter 5 value 646.250927
#> iter 6 value 643.850964
#> iter 7 value 643.791585
#> iter 8 value 643.791235
#> iter 8 value 643.791233
#> final value 643.791233
#> converged
#> This is Run number 177
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 6.0495728806 -0.75325216 1.7495729 -13.353252 1
#> 2 1 -0.35 -14.40 0.0006020643 -0.74820965 -0.3493979 -15.148210 1
#> 3 1 -12.20 -2.55 -0.3408721982 -1.08943176 -12.5408722 -3.639432 2
#> 4 1 -2.30 -13.70 0.8855251633 3.21105486 -1.4144748 -10.488945 1
#> 5 1 -12.60 -7.80 0.8419394891 0.75396633 -11.7580605 -7.046034 2
#> 6 1 -7.60 -12.40 -0.3503741924 0.01516449 -7.9503742 -12.384836 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4860 -72600 14425
#> initial value 998.131940
#> iter 2 value 670.679595
#> iter 3 value 670.675703
#> iter 4 value 670.673368
#> iter 5 value 650.147010
#> iter 6 value 648.036215
#> iter 7 value 647.986212
#> iter 8 value 647.985966
#> iter 8 value 647.985964
#> final value 647.985964
#> converged
#> This is Run number 178
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.9641491 0.5281901 -2.3358509 -12.071810 1
#> 2 1 -0.35 -14.40 0.4897146 -1.6326573 0.1397146 -16.032657 1
#> 3 1 -12.20 -2.55 -0.2257871 -0.9102459 -12.4257871 -3.460246 2
#> 4 1 -2.30 -13.70 -0.5541478 0.1980266 -2.8541478 -13.501973 1
#> 5 1 -12.60 -7.80 2.6080685 1.5473935 -9.9919315 -6.252606 2
#> 6 1 -7.60 -12.40 2.1890443 -0.2296479 -5.4109557 -12.629648 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5480 -72750 13025
#> initial value 998.131940
#> iter 2 value 671.229481
#> iter 3 value 670.790578
#> iter 4 value 670.715645
#> iter 5 value 650.539239
#> iter 6 value 648.354194
#> iter 7 value 648.307072
#> iter 8 value 648.306918
#> iter 8 value 648.306918
#> final value 648.306918
#> converged
#> This is Run number 179
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.90047215 1.39495942 -1.3995279 -11.205041 1
#> 2 1 -0.35 -14.40 0.97550486 0.60101798 0.6255049 -13.798982 1
#> 3 1 -12.20 -2.55 1.73101428 -0.28785871 -10.4689857 -2.837859 2
#> 4 1 -2.30 -13.70 0.88587653 -0.37628206 -1.4141235 -14.076282 1
#> 5 1 -12.60 -7.80 -0.05308007 2.61023398 -12.6530801 -5.189766 2
#> 6 1 -7.60 -12.40 0.17176256 0.05533729 -7.4282374 -12.344663 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5180 -74475 14650
#> initial value 998.131940
#> iter 2 value 652.934116
#> iter 3 value 652.916463
#> iter 4 value 652.906944
#> iter 5 value 630.227043
#> iter 6 value 627.471942
#> iter 7 value 627.395911
#> iter 8 value 627.395455
#> iter 8 value 627.395453
#> final value 627.395453
#> converged
#> This is Run number 180
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.05214318 -0.11964450 -4.2478568 -12.719644 1
#> 2 1 -0.35 -14.40 0.99769139 0.07999073 0.6476914 -14.320009 1
#> 3 1 -12.20 -2.55 -1.16275431 0.03438260 -13.3627543 -2.515617 2
#> 4 1 -2.30 -13.70 0.16491537 -0.41033874 -2.1350846 -14.110339 1
#> 5 1 -12.60 -7.80 3.05647388 1.50520642 -9.5435261 -6.294794 2
#> 6 1 -7.60 -12.40 0.66459145 0.76814280 -6.9354085 -11.631857 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4880 -73425 14800
#> initial value 998.131940
#> iter 2 value 662.508614
#> iter 3 value 662.506260
#> iter 4 value 662.504107
#> iter 5 value 640.874028
#> iter 6 value 638.516589
#> iter 7 value 638.454985
#> iter 8 value 638.454625
#> iter 8 value 638.454623
#> final value 638.454623
#> converged
#> This is Run number 181
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.749991884 0.1716860 -5.0499919 -12.428314 1
#> 2 1 -0.35 -14.40 -0.003151649 0.9543391 -0.3531516 -13.445661 1
#> 3 1 -12.20 -2.55 -0.463808893 -0.5969612 -12.6638089 -3.146961 2
#> 4 1 -2.30 -13.70 0.977843027 -0.5675054 -1.3221570 -14.267505 1
#> 5 1 -12.60 -7.80 -0.122266975 0.5696840 -12.7222670 -7.230316 2
#> 6 1 -7.60 -12.40 -0.195137021 3.5229751 -7.7951370 -8.877025 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3860 -71250 13750
#> initial value 998.131940
#> iter 2 value 684.382103
#> iter 3 value 683.394276
#> iter 4 value 683.140283
#> iter 5 value 663.957798
#> iter 6 value 661.877383
#> iter 7 value 661.827510
#> iter 8 value 661.827162
#> iter 8 value 661.827161
#> final value 661.827161
#> converged
#> This is Run number 182
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.2738517 -1.31784171 -3.026148 -13.917842 1
#> 2 1 -0.35 -14.40 -0.4704680 3.68567596 -0.820468 -10.714324 1
#> 3 1 -12.20 -2.55 -0.3124323 0.41598403 -12.512432 -2.134016 2
#> 4 1 -2.30 -13.70 -0.0735760 -0.06761426 -2.373576 -13.767614 1
#> 5 1 -12.60 -7.80 0.9054589 -0.90747055 -11.694541 -8.707471 2
#> 6 1 -7.60 -12.40 1.7348010 -1.68827831 -5.865199 -14.088278 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4140 -72300 14325
#> initial value 998.131940
#> iter 2 value 673.934233
#> iter 3 value 673.230535
#> iter 4 value 673.223485
#> iter 5 value 652.946130
#> iter 6 value 650.618900
#> iter 7 value 650.558949
#> iter 8 value 650.558504
#> iter 8 value 650.558501
#> final value 650.558501
#> converged
#> This is Run number 183
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.5808940 0.6124367 -2.719106 -11.987563 1
#> 2 1 -0.35 -14.40 3.7815482 0.4584488 3.431548 -13.941551 1
#> 3 1 -12.20 -2.55 -0.8661325 0.9268250 -13.066132 -1.623175 2
#> 4 1 -2.30 -13.70 0.2307138 1.6081313 -2.069286 -12.091869 1
#> 5 1 -12.60 -7.80 1.4005868 1.1805376 -11.199413 -6.619462 2
#> 6 1 -7.60 -12.40 2.3352601 0.7636837 -5.264740 -11.636316 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5160 -73850 14150
#> initial value 998.131940
#> iter 2 value 659.599848
#> iter 3 value 659.530718
#> iter 4 value 659.526977
#> iter 5 value 637.690469
#> iter 6 value 635.244301
#> iter 7 value 635.181745
#> iter 8 value 635.181428
#> iter 8 value 635.181426
#> final value 635.181426
#> converged
#> This is Run number 184
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.2297476 0.25701787 -4.0702524 -12.34298213 1
#> 2 1 -0.35 -14.40 1.6718183 2.55123179 1.3218183 -11.84876821 1
#> 3 1 -12.20 -2.55 1.4093526 2.49976412 -10.7906474 -0.05023588 2
#> 4 1 -2.30 -13.70 1.9546575 -0.09858141 -0.3453425 -13.79858141 1
#> 5 1 -12.60 -7.80 -0.9685755 1.33644981 -13.5685755 -6.46355019 2
#> 6 1 -7.60 -12.40 -0.9918344 -0.24274777 -8.5918344 -12.64274777 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5240 -72575 14850
#> initial value 998.131940
#> iter 2 value 669.888161
#> iter 3 value 669.777076
#> iter 4 value 669.722056
#> iter 5 value 649.232005
#> iter 6 value 646.945146
#> iter 7 value 646.892518
#> iter 8 value 646.892285
#> iter 8 value 646.892283
#> final value 646.892283
#> converged
#> This is Run number 185
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.5988771 2.81305283 -4.8988771 -9.786947 1
#> 2 1 -0.35 -14.40 -0.6040073 0.10800937 -0.9540073 -14.291991 1
#> 3 1 -12.20 -2.55 0.2491819 -0.04906888 -11.9508181 -2.599069 2
#> 4 1 -2.30 -13.70 0.3214610 1.23787339 -1.9785390 -12.462127 1
#> 5 1 -12.60 -7.80 -1.3457159 -0.36002373 -13.9457159 -8.160024 2
#> 6 1 -7.60 -12.40 0.6380026 0.23291966 -6.9619974 -12.167080 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4540 -69000 14425
#> initial value 998.131940
#> iter 2 value 702.367378
#> iter 3 value 702.326555
#> iter 4 value 702.326449
#> iter 5 value 686.326736
#> iter 6 value 684.182564
#> iter 7 value 684.141652
#> iter 8 value 684.141516
#> iter 8 value 684.141515
#> final value 684.141515
#> converged
#> This is Run number 186
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.9272793 2.276843670 -3.3727207 -10.323156 1
#> 2 1 -0.35 -14.40 -0.2243103 1.649060645 -0.5743103 -12.750939 1
#> 3 1 -12.20 -2.55 0.8018977 -0.410342961 -11.3981023 -2.960343 2
#> 4 1 -2.30 -13.70 -1.4351246 0.006288613 -3.7351246 -13.693711 1
#> 5 1 -12.60 -7.80 0.6503819 2.326113804 -11.9496181 -5.473886 2
#> 6 1 -7.60 -12.40 1.5584328 -1.602242403 -6.0415672 -14.002242 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4820 -72225 15500
#> initial value 998.131940
#> iter 2 value 672.047673
#> iter 3 value 671.899134
#> iter 4 value 671.883881
#> iter 5 value 651.519515
#> iter 6 value 649.235278
#> iter 7 value 649.180201
#> iter 8 value 649.179904
#> iter 8 value 649.179902
#> final value 649.179902
#> converged
#> This is Run number 187
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.5423909 0.005875801 -1.7576091 -12.594124 1
#> 2 1 -0.35 -14.40 -0.2936793 -1.169667656 -0.6436793 -15.569668 1
#> 3 1 -12.20 -2.55 1.1612433 0.457876061 -11.0387567 -2.092124 2
#> 4 1 -2.30 -13.70 0.6786031 0.392409445 -1.6213969 -13.307591 1
#> 5 1 -12.60 -7.80 3.1700242 -1.536989522 -9.4299758 -9.336990 2
#> 6 1 -7.60 -12.40 4.0281846 2.716171772 -3.5718154 -9.683828 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4980 -73200 13875
#> initial value 998.131940
#> iter 2 value 666.124897
#> iter 3 value 666.027299
#> iter 4 value 666.020224
#> iter 5 value 645.078002
#> iter 6 value 642.748855
#> iter 7 value 642.692496
#> iter 8 value 642.692215
#> iter 8 value 642.692213
#> final value 642.692213
#> converged
#> This is Run number 188
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.22839345 1.7004098 -2.07160655 -10.8995902 1
#> 2 1 -0.35 -14.40 0.37287216 -1.0303412 0.02287216 -15.4303412 1
#> 3 1 -12.20 -2.55 -0.58745591 1.9151942 -12.78745591 -0.6348058 2
#> 4 1 -2.30 -13.70 0.69827971 -0.5765911 -1.60172029 -14.2765911 1
#> 5 1 -12.60 -7.80 0.12104353 0.7520911 -12.47895647 -7.0479089 2
#> 6 1 -7.60 -12.40 0.07076168 0.6134449 -7.52923832 -11.7865551 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5680 -73950 14800
#> initial value 998.131940
#> iter 2 value 657.155368
#> iter 3 value 656.612118
#> iter 4 value 656.554184
#> iter 5 value 634.471254
#> iter 6 value 631.825587
#> iter 7 value 631.757845
#> iter 8 value 631.757536
#> iter 8 value 631.757534
#> final value 631.757534
#> converged
#> This is Run number 189
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.7727978 0.6175198 -3.5272022 -11.982480 1
#> 2 1 -0.35 -14.40 -0.2806579 1.0294581 -0.6306579 -13.370542 1
#> 3 1 -12.20 -2.55 0.3435759 -0.7410388 -11.8564241 -3.291039 2
#> 4 1 -2.30 -13.70 1.4601184 -0.7228377 -0.8398816 -14.422838 1
#> 5 1 -12.60 -7.80 2.6726286 1.3894906 -9.9273714 -6.410509 2
#> 6 1 -7.60 -12.40 1.4117293 -0.2026631 -6.1882707 -12.602663 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4100 -73075 16200
#> initial value 998.131940
#> iter 2 value 663.339869
#> iter 3 value 662.812692
#> iter 4 value 662.560776
#> iter 5 value 640.614485
#> iter 6 value 637.819222
#> iter 7 value 637.732614
#> iter 8 value 637.731753
#> iter 8 value 637.731748
#> final value 637.731748
#> converged
#> This is Run number 190
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 3.0653474 1.1185379 -1.2346526 -11.481462 1
#> 2 1 -0.35 -14.40 1.2831299 0.4215797 0.9331299 -13.978420 1
#> 3 1 -12.20 -2.55 2.3688387 -0.6182880 -9.8311613 -3.168288 2
#> 4 1 -2.30 -13.70 0.6372503 0.7208550 -1.6627497 -12.979145 1
#> 5 1 -12.60 -7.80 -0.7765725 -1.2153358 -13.3765725 -9.015336 2
#> 6 1 -7.60 -12.40 0.6714277 -1.3280204 -6.9285723 -13.728020 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4900 -70400 15150
#> initial value 998.131940
#> iter 2 value 688.773229
#> iter 3 value 688.598418
#> iter 4 value 688.503060
#> iter 5 value 670.255493
#> iter 6 value 668.410390
#> iter 7 value 668.373936
#> iter 8 value 668.373801
#> iter 8 value 668.373800
#> final value 668.373800
#> converged
#> This is Run number 191
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.6664173 0.4445357 -4.9664173 -12.155464 1
#> 2 1 -0.35 -14.40 0.1716838 -0.2625808 -0.1783162 -14.662581 1
#> 3 1 -12.20 -2.55 0.0446696 1.8145580 -12.1553304 -0.735442 2
#> 4 1 -2.30 -13.70 -0.2891879 1.5228773 -2.5891879 -12.177123 1
#> 5 1 -12.60 -7.80 2.6119965 -0.5238110 -9.9880035 -8.323811 2
#> 6 1 -7.60 -12.40 2.6802119 -1.1392455 -4.9197881 -13.539246 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4280 -71475 13150
#> initial value 998.131940
#> iter 2 value 683.171092
#> iter 3 value 682.779328
#> iter 4 value 682.448197
#> iter 5 value 663.336608
#> iter 6 value 661.323898
#> iter 7 value 661.280156
#> iter 8 value 661.279918
#> iter 8 value 661.279916
#> final value 661.279916
#> converged
#> This is Run number 192
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.8070341 -0.23921061 -3.4929659 -12.839211 1
#> 2 1 -0.35 -14.40 0.9510729 0.80663126 0.6010729 -13.593369 1
#> 3 1 -12.20 -2.55 -1.1806149 0.02460263 -13.3806149 -2.525397 2
#> 4 1 -2.30 -13.70 0.5717958 -0.15409589 -1.7282042 -13.854096 1
#> 5 1 -12.60 -7.80 -1.4479273 0.19828094 -14.0479273 -7.601719 2
#> 6 1 -7.60 -12.40 0.2456012 0.34832708 -7.3543988 -12.051673 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4040 -68950 13475
#> initial value 998.131940
#> iter 2 value 704.678673
#> iter 3 value 704.338867
#> iter 4 value 704.217211
#> iter 5 value 687.669358
#> iter 6 value 686.145667
#> iter 7 value 686.118492
#> iter 8 value 686.118378
#> iter 8 value 686.118377
#> final value 686.118377
#> converged
#> This is Run number 193
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.08687984 4.75376298 -4.2131202 -7.846237 1
#> 2 1 -0.35 -14.40 -0.47240503 -0.92852738 -0.8224050 -15.328527 1
#> 3 1 -12.20 -2.55 -1.04552283 -0.01956414 -13.2455228 -2.569564 2
#> 4 1 -2.30 -13.70 2.43387908 1.24608988 0.1338791 -12.453910 1
#> 5 1 -12.60 -7.80 -0.02253653 1.34992089 -12.6225365 -6.450079 2
#> 6 1 -7.60 -12.40 2.84442334 1.30233007 -4.7555767 -11.097670 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4900 -71275 14175
#> initial value 998.131940
#> iter 2 value 682.906700
#> iter 3 value 682.900053
#> iter 4 value 682.894949
#> iter 5 value 664.036754
#> iter 6 value 662.156518
#> iter 7 value 662.118273
#> iter 8 value 662.118128
#> iter 8 value 662.118127
#> final value 662.118127
#> converged
#> This is Run number 194
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.1008262 -0.59816807 -3.199174 -13.198168 1
#> 2 1 -0.35 -14.40 -0.2493610 0.30000123 -0.599361 -14.099999 1
#> 3 1 -12.20 -2.55 -1.2930344 -0.13859337 -13.493034 -2.688593 2
#> 4 1 -2.30 -13.70 1.0292510 0.07981703 -1.270749 -13.620183 1
#> 5 1 -12.60 -7.80 0.7871580 1.37637612 -11.812842 -6.423624 2
#> 6 1 -7.60 -12.40 0.4084587 0.56285141 -7.191541 -11.837149 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4820 -73225 14525
#> initial value 998.131940
#> iter 2 value 664.866693
#> iter 3 value 664.855726
#> iter 4 value 664.851660
#> iter 5 value 643.689661
#> iter 6 value 641.246087
#> iter 7 value 641.184528
#> iter 8 value 641.184166
#> iter 8 value 641.184164
#> final value 641.184164
#> converged
#> This is Run number 195
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.6658113 1.4229452 -4.9658113 -11.177055 1
#> 2 1 -0.35 -14.40 -0.4637719 -0.1472360 -0.8137719 -14.547236 1
#> 3 1 -12.20 -2.55 0.3779511 1.1461568 -11.8220489 -1.403843 2
#> 4 1 -2.30 -13.70 -0.8866720 0.1594267 -3.1866720 -13.540573 1
#> 5 1 -12.60 -7.80 0.1204160 -0.2908744 -12.4795840 -8.090874 2
#> 6 1 -7.60 -12.40 0.9446559 0.8799280 -6.6553441 -11.520072 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4800 -72775 12750
#> initial value 998.131940
#> iter 2 value 671.858854
#> iter 3 value 671.311244
#> iter 4 value 671.168605
#> iter 5 value 650.910971
#> iter 6 value 648.665044
#> iter 7 value 648.613319
#> iter 8 value 648.613077
#> iter 8 value 648.613075
#> final value 648.613075
#> converged
#> This is Run number 196
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.58875431 1.28544279 -3.7112457 -11.314557 1
#> 2 1 -0.35 -14.40 0.80078711 0.01549220 0.4507871 -14.384508 1
#> 3 1 -12.20 -2.55 0.02457712 -0.02993479 -12.1754229 -2.579935 2
#> 4 1 -2.30 -13.70 0.13103673 0.10606528 -2.1689633 -13.593935 1
#> 5 1 -12.60 -7.80 -0.43410497 -0.75293624 -13.0341050 -8.552936 2
#> 6 1 -7.60 -12.40 0.66511623 1.18740469 -6.9348838 -11.212595 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5120 -71200 14825
#> initial value 998.131940
#> iter 2 value 682.253703
#> iter 3 value 682.151908
#> iter 4 value 682.101552
#> iter 5 value 663.064998
#> iter 6 value 661.095354
#> iter 7 value 661.054006
#> iter 8 value 661.053851
#> iter 8 value 661.053850
#> final value 661.053850
#> converged
#> This is Run number 197
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.17032708 -0.5124597 -4.47032708 -13.1124597 1
#> 2 1 -0.35 -14.40 0.44648396 0.1228685 0.09648396 -14.2771315 1
#> 3 1 -12.20 -2.55 0.95445513 1.8022269 -11.24554487 -0.7477731 2
#> 4 1 -2.30 -13.70 0.09959401 0.5022768 -2.20040599 -13.1977232 1
#> 5 1 -12.60 -7.80 1.81090499 0.8045566 -10.78909501 -6.9954434 2
#> 6 1 -7.60 -12.40 0.99314539 2.1727164 -6.60685461 -10.2272836 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4160 -71250 14500
#> initial value 998.131940
#> iter 2 value 682.950472
#> iter 3 value 682.696861
#> iter 4 value 682.580423
#> iter 5 value 663.395933
#> iter 6 value 661.334655
#> iter 7 value 661.287648
#> iter 8 value 661.287339
#> iter 8 value 661.287337
#> final value 661.287337
#> converged
#> This is Run number 198
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.6215791 -0.1276530 -2.6784209 -12.727653 1
#> 2 1 -0.35 -14.40 -0.9207813 -0.1717138 -1.2707813 -14.571714 1
#> 3 1 -12.20 -2.55 2.8176708 -0.6738826 -9.3823292 -3.223883 2
#> 4 1 -2.30 -13.70 2.1437773 3.0294392 -0.1562227 -10.670561 1
#> 5 1 -12.60 -7.80 1.1977671 4.4790664 -11.4022329 -3.320934 2
#> 6 1 -7.60 -12.40 1.5136273 0.7145941 -6.0863727 -11.685406 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5140 -70425 13675
#> initial value 998.131940
#> iter 2 value 691.050855
#> iter 3 value 690.964128
#> iter 4 value 690.892901
#> iter 5 value 673.106967
#> iter 6 value 671.392798
#> iter 7 value 671.362181
#> iter 8 value 671.362097
#> iter 8 value 671.362097
#> final value 671.362097
#> converged
#> This is Run number 199
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.84072660 2.2178128 -2.459273 -10.382187 1
#> 2 1 -0.35 -14.40 2.56287558 1.2463816 2.212876 -13.153618 1
#> 3 1 -12.20 -2.55 1.63120060 -0.8677938 -10.568799 -3.417794 2
#> 4 1 -2.30 -13.70 -0.05994531 0.6547891 -2.359945 -13.045211 1
#> 5 1 -12.60 -7.80 1.88421058 -0.8857753 -10.715789 -8.685775 2
#> 6 1 -7.60 -12.40 -0.62605689 6.6021507 -8.226057 -5.797849 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3960 -71950 15375
#> initial value 998.131940
#> iter 2 value 675.188793
#> iter 3 value 674.812103
#> iter 4 value 674.480584
#> iter 5 value 654.069617
#> iter 6 value 651.679035
#> iter 7 value 651.613451
#> iter 8 value 651.612887
#> iter 8 value 651.612884
#> final value 651.612884
#> converged
#> This is Run number 200
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.53855203 -0.76477965 -2.7614480 -13.364780 1
#> 2 1 -0.35 -14.40 0.52459547 -0.64620197 0.1745955 -15.046202 1
#> 3 1 -12.20 -2.55 -0.02207552 -0.04124527 -12.2220755 -2.591245 2
#> 4 1 -2.30 -13.70 2.17982732 1.67403003 -0.1201727 -12.025970 1
#> 5 1 -12.60 -7.80 3.28322635 0.72438855 -9.3167737 -7.075611 2
#> 6 1 -7.60 -12.40 -0.44599894 -0.12824351 -8.0459989 -12.528244 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4960 -73425 14125
#> initial value 998.131940
#> iter 2 value 663.662406
#> iter 3 value 663.607756
#> iter 4 value 663.600646
#> iter 5 value 642.321835
#> iter 6 value 639.910750
#> iter 7 value 639.850397
#> iter 8 value 639.850073
#> iter 8 value 639.850071
#> final value 639.850071
#> converged
#> This is Run number 201
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.0596831 -0.18767828 -4.359683 -12.787678 1
#> 2 1 -0.35 -14.40 -0.7250887 1.39971703 -1.075089 -13.000283 1
#> 3 1 -12.20 -2.55 -0.4133225 0.47235758 -12.613322 -2.077642 2
#> 4 1 -2.30 -13.70 -0.7517572 1.24624598 -3.051757 -12.453754 1
#> 5 1 -12.60 -7.80 -0.6151390 3.18169585 -13.215139 -4.618304 2
#> 6 1 -7.60 -12.40 0.4696055 0.03273382 -7.130394 -12.367266 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4660 -72850 14700
#> initial value 998.131940
#> iter 2 value 668.042920
#> iter 3 value 668.009915
#> iter 4 value 667.991234
#> iter 5 value 647.183839
#> iter 6 value 644.786487
#> iter 7 value 644.726550
#> iter 8 value 644.726176
#> iter 8 value 644.726173
#> final value 644.726173
#> converged
#> This is Run number 202
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.29736286 -0.6299921 -3.0026371 -13.229992 1
#> 2 1 -0.35 -14.40 -0.23355858 -1.1477957 -0.5835586 -15.547796 1
#> 3 1 -12.20 -2.55 -0.34427981 -0.2344537 -12.5442798 -2.784454 2
#> 4 1 -2.30 -13.70 -0.09578502 -0.1184093 -2.3957850 -13.818409 1
#> 5 1 -12.60 -7.80 -0.43998751 -1.0312880 -13.0399875 -8.831288 2
#> 6 1 -7.60 -12.40 -0.19308153 0.4505557 -7.7930815 -11.949444 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4260 -71700 14325
#> initial value 998.131940
#> iter 2 value 679.233113
#> iter 3 value 678.828373
#> iter 4 value 678.825734
#> iter 5 value 659.299331
#> iter 6 value 657.177857
#> iter 7 value 657.127729
#> iter 8 value 657.127413
#> iter 8 value 657.127411
#> final value 657.127411
#> converged
#> This is Run number 203
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.13793783 -0.35606659 -4.162062 -12.956067 1
#> 2 1 -0.35 -14.40 -1.14764064 -0.40649968 -1.497641 -14.806500 1
#> 3 1 -12.20 -2.55 -0.21054561 -0.01245938 -12.410546 -2.562459 2
#> 4 1 -2.30 -13.70 0.28877404 -0.37882443 -2.011226 -14.078824 1
#> 5 1 -12.60 -7.80 0.98917566 1.99490247 -11.610824 -5.805098 2
#> 6 1 -7.60 -12.40 0.06270742 1.55078974 -7.537293 -10.849210 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4940 -71600 13725
#> initial value 998.131940
#> iter 2 value 680.773786
#> iter 3 value 680.709216
#> iter 4 value 680.709068
#> iter 5 value 659.788336
#> iter 6 value 659.667040
#> iter 7 value 659.664412
#> iter 7 value 659.664411
#> iter 7 value 659.664411
#> final value 659.664411
#> converged
#> This is Run number 204
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.3062643 0.4947037 -4.6062643 -12.105296 1
#> 2 1 -0.35 -14.40 0.7343582 0.9295404 0.3843582 -13.470460 1
#> 3 1 -12.20 -2.55 0.5566848 -0.8234551 -11.6433152 -3.373455 2
#> 4 1 -2.30 -13.70 -0.6107494 4.4576496 -2.9107494 -9.242350 1
#> 5 1 -12.60 -7.80 2.2874388 -0.2154954 -10.3125612 -8.015495 2
#> 6 1 -7.60 -12.40 -1.1865860 0.8653285 -8.7865860 -11.534672 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4280 -71775 15025
#> initial value 998.131940
#> iter 2 value 677.274427
#> iter 3 value 677.124289
#> iter 4 value 676.993820
#> iter 5 value 657.164621
#> iter 6 value 654.939537
#> iter 7 value 654.884785
#> iter 8 value 654.884416
#> iter 8 value 654.884413
#> final value 654.884413
#> converged
#> This is Run number 205
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.40746525 -0.3931615 -3.892535 -12.993161 1
#> 2 1 -0.35 -14.40 -0.81702245 2.6196655 -1.167022 -11.780334 1
#> 3 1 -12.20 -2.55 -0.38568737 0.4259127 -12.585687 -2.124087 2
#> 4 1 -2.30 -13.70 -0.11013328 0.6253486 -2.410133 -13.074651 1
#> 5 1 -12.60 -7.80 0.05079399 1.6898015 -12.549206 -6.110199 2
#> 6 1 -7.60 -12.40 0.89131968 -0.1825928 -6.708680 -12.582593 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4940 -71875 14475
#> initial value 998.131940
#> iter 2 value 677.034080
#> iter 3 value 677.019460
#> iter 4 value 677.018391
#> iter 5 value 657.387642
#> iter 6 value 655.380406
#> iter 7 value 655.336585
#> iter 8 value 655.336399
#> iter 8 value 655.336398
#> final value 655.336398
#> converged
#> This is Run number 206
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.8846972 -0.7283093 -3.415303 -13.328309 1
#> 2 1 -0.35 -14.40 2.6422589 3.7416076 2.292259 -10.658392 1
#> 3 1 -12.20 -2.55 2.4734481 1.0429687 -9.726552 -1.507031 2
#> 4 1 -2.30 -13.70 -0.0764173 1.4328368 -2.376417 -12.267163 1
#> 5 1 -12.60 -7.80 -0.4041859 -0.1851443 -13.004186 -7.985144 2
#> 6 1 -7.60 -12.40 1.8889250 2.1538612 -5.711075 -10.246139 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4900 -71600 13275
#> initial value 998.131940
#> iter 2 value 681.526820
#> iter 3 value 681.346135
#> iter 4 value 681.336481
#> iter 5 value 662.361345
#> iter 6 value 660.437211
#> iter 7 value 660.398044
#> iter 8 value 660.397898
#> iter 8 value 660.397898
#> final value 660.397898
#> converged
#> This is Run number 207
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.3042683 1.07318679 -5.60426827 -11.526813 1
#> 2 1 -0.35 -14.40 2.2898563 -0.39690136 1.93985633 -14.796901 1
#> 3 1 -12.20 -2.55 0.3530294 0.06341537 -11.84697059 -2.486585 2
#> 4 1 -2.30 -13.70 2.2536467 -0.08567996 -0.04635328 -13.785680 1
#> 5 1 -12.60 -7.80 1.8052657 1.28591229 -10.79473428 -6.514088 2
#> 6 1 -7.60 -12.40 0.5635644 -0.38773786 -7.03643557 -12.787738 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4680 -72400 15450
#> initial value 998.131940
#> iter 2 value 670.660136
#> iter 3 value 670.532902
#> iter 4 value 670.531962
#> iter 5 value 649.508108
#> iter 6 value 647.616068
#> iter 7 value 647.568015
#> iter 8 value 647.567757
#> iter 8 value 647.567756
#> final value 647.567756
#> converged
#> This is Run number 208
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.83069138 -0.7802231 -1.4693086 -13.380223 1
#> 2 1 -0.35 -14.40 -0.01133359 2.0556088 -0.3613336 -12.344391 1
#> 3 1 -12.20 -2.55 0.02917024 -0.2163050 -12.1708298 -2.766305 2
#> 4 1 -2.30 -13.70 -0.51799206 1.1058976 -2.8179921 -12.594102 1
#> 5 1 -12.60 -7.80 -1.02780124 -0.7731193 -13.6278012 -8.573119 2
#> 6 1 -7.60 -12.40 0.56168063 1.4885609 -7.0383194 -10.911439 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4900 -72050 15225
#> initial value 998.131940
#> iter 2 value 674.100929
#> iter 3 value 674.009264
#> iter 4 value 673.981042
#> iter 5 value 653.954578
#> iter 6 value 651.741914
#> iter 7 value 651.690717
#> iter 8 value 651.690465
#> iter 8 value 651.690464
#> final value 651.690464
#> converged
#> This is Run number 209
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.7855647 1.1738563 -5.0855647 -11.426144 1
#> 2 1 -0.35 -14.40 2.1540235 -0.6338797 1.8040235 -15.033880 1
#> 3 1 -12.20 -2.55 1.4190958 0.8414405 -10.7809042 -1.708559 2
#> 4 1 -2.30 -13.70 1.7357615 -1.3819674 -0.5642385 -15.081967 1
#> 5 1 -12.60 -7.80 -1.1346901 -0.1019976 -13.7346901 -7.901998 2
#> 6 1 -7.60 -12.40 2.4563881 2.5928734 -5.1436119 -9.807127 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4740 -72475 14025
#> initial value 998.131940
#> iter 2 value 672.573054
#> iter 3 value 672.517240
#> iter 4 value 672.477165
#> iter 5 value 652.344675
#> iter 6 value 650.114171
#> iter 7 value 650.062408
#> iter 8 value 650.062139
#> iter 8 value 650.062137
#> final value 650.062137
#> converged
#> This is Run number 210
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.41423455 -0.4480742 -4.7142346 -13.048074 1
#> 2 1 -0.35 -14.40 -0.58588887 1.5423921 -0.9358889 -12.857608 1
#> 3 1 -12.20 -2.55 6.22778410 0.4173160 -5.9722159 -2.132684 2
#> 4 1 -2.30 -13.70 -0.41197662 -0.4476559 -2.7119766 -14.147656 1
#> 5 1 -12.60 -7.80 -0.08270579 3.9419816 -12.6827058 -3.858018 2
#> 6 1 -7.60 -12.40 0.34959317 1.3786441 -7.2504068 -11.021356 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4980 -69925 14825
#> initial value 998.131940
#> iter 2 value 693.452152
#> iter 3 value 693.313383
#> iter 4 value 693.195798
#> iter 5 value 675.528621
#> iter 6 value 673.812544
#> iter 7 value 673.780671
#> iter 8 value 673.780568
#> iter 8 value 673.780568
#> final value 673.780568
#> converged
#> This is Run number 211
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.6969418 4.1620861 -3.603058 -8.4379139 1
#> 2 1 -0.35 -14.40 -1.4331345 1.5690663 -1.783134 -12.8309337 1
#> 3 1 -12.20 -2.55 -0.2071550 2.6961943 -12.407155 0.1461943 2
#> 4 1 -2.30 -13.70 0.8816855 -0.4753513 -1.418314 -14.1753513 1
#> 5 1 -12.60 -7.80 1.2571484 -0.4587100 -11.342852 -8.2587100 2
#> 6 1 -7.60 -12.40 1.0433969 -0.9075017 -6.556603 -13.3075017 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4800 -73450 13775
#> initial value 998.131940
#> iter 2 value 664.120443
#> iter 3 value 663.958546
#> iter 4 value 663.878979
#> iter 5 value 642.663229
#> iter 6 value 640.185735
#> iter 7 value 640.123134
#> iter 8 value 640.122769
#> iter 8 value 640.122766
#> final value 640.122766
#> converged
#> This is Run number 212
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.1943588 0.2127449 -5.494359 -12.387255 1
#> 2 1 -0.35 -14.40 0.6044610 1.0335488 0.254461 -13.366451 1
#> 3 1 -12.20 -2.55 0.7858770 1.1328748 -11.414123 -1.417125 2
#> 4 1 -2.30 -13.70 -0.1184470 -0.9707907 -2.418447 -14.670791 1
#> 5 1 -12.60 -7.80 0.3387109 1.1019865 -12.261289 -6.698013 2
#> 6 1 -7.60 -12.40 -0.2927548 1.6842839 -7.892755 -10.715716 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4760 -74150 13750
#> initial value 998.131940
#> iter 2 value 657.754125
#> iter 3 value 657.516043
#> iter 4 value 657.368590
#> iter 5 value 635.261609
#> iter 6 value 632.562711
#> iter 7 value 632.489063
#> iter 8 value 632.488568
#> iter 8 value 632.488564
#> final value 632.488564
#> converged
#> This is Run number 213
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.4201675 0.9120092 -2.8798325 -11.687991 1
#> 2 1 -0.35 -14.40 0.6504184 1.5665899 0.3004184 -12.833410 1
#> 3 1 -12.20 -2.55 2.1364559 -0.1519089 -10.0635441 -2.701909 2
#> 4 1 -2.30 -13.70 0.8410003 0.3083113 -1.4589997 -13.391689 1
#> 5 1 -12.60 -7.80 -0.1055378 0.2956779 -12.7055378 -7.504322 2
#> 6 1 -7.60 -12.40 0.1973436 1.2651566 -7.4026564 -11.134843 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4940 -70850 13050
#> initial value 998.131940
#> iter 2 value 688.468420
#> iter 3 value 688.260063
#> iter 4 value 688.259270
#> iter 5 value 669.754473
#> iter 6 value 668.385024
#> iter 7 value 668.359147
#> iter 8 value 668.359079
#> iter 8 value 668.359078
#> final value 668.359078
#> converged
#> This is Run number 214
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.0020171 0.26821322 -5.3020171 -12.331787 1
#> 2 1 -0.35 -14.40 1.3767104 0.75212462 1.0267104 -13.647875 1
#> 3 1 -12.20 -2.55 -0.3874249 -0.05220671 -12.5874249 -2.602207 2
#> 4 1 -2.30 -13.70 1.5254476 3.63472803 -0.7745524 -10.065272 1
#> 5 1 -12.60 -7.80 0.7563432 0.37392482 -11.8436568 -7.426075 2
#> 6 1 -7.60 -12.40 0.4281651 -0.04655107 -7.1718349 -12.446551 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5220 -74000 14175
#> initial value 998.131940
#> iter 2 value 658.137233
#> iter 3 value 658.061931
#> iter 4 value 658.050955
#> iter 5 value 636.117299
#> iter 6 value 633.545204
#> iter 7 value 633.478987
#> iter 8 value 633.478646
#> iter 8 value 633.478644
#> final value 633.478644
#> converged
#> This is Run number 215
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.0679286 1.8521983 -3.2320714 -10.747802 1
#> 2 1 -0.35 -14.40 0.2375315 1.0770952 -0.1124685 -13.322905 1
#> 3 1 -12.20 -2.55 0.8133212 -0.4724136 -11.3866788 -3.022414 2
#> 4 1 -2.30 -13.70 0.9558676 1.6102285 -1.3441324 -12.089772 1
#> 5 1 -12.60 -7.80 0.9210562 0.6462786 -11.6789438 -7.153721 2
#> 6 1 -7.60 -12.40 0.1136982 2.1639505 -7.4863018 -10.236050 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4820 -71425 13950
#> initial value 998.131940
#> iter 2 value 682.018341
#> iter 3 value 681.994729
#> iter 4 value 681.992406
#> iter 5 value 662.932128
#> iter 6 value 661.117770
#> iter 7 value 661.080145
#> iter 8 value 661.079997
#> iter 8 value 661.079996
#> final value 661.079996
#> converged
#> This is Run number 216
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.8892901 -0.2527873 -5.189290107 -12.852787 1
#> 2 1 -0.35 -14.40 0.5885275 2.0376836 0.238527479 -12.362316 1
#> 3 1 -12.20 -2.55 -0.8196091 1.2386206 -13.019609079 -1.311379 2
#> 4 1 -2.30 -13.70 2.3089790 -0.5090988 0.008978986 -14.209099 1
#> 5 1 -12.60 -7.80 2.3384871 0.1575339 -10.261512950 -7.642466 2
#> 6 1 -7.60 -12.40 0.3962135 0.1659088 -7.203786471 -12.234091 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4320 -73425 15000
#> initial value 998.131940
#> iter 2 value 662.441855
#> iter 3 value 662.329846
#> iter 4 value 662.201439
#> iter 5 value 640.254054
#> iter 6 value 637.583525
#> iter 7 value 637.507603
#> iter 8 value 637.506928
#> iter 8 value 637.506921
#> final value 637.506921
#> converged
#> This is Run number 217
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.29491502 0.00267883 -4.0050850 -12.597321 1
#> 2 1 -0.35 -14.40 0.03595913 -0.51592685 -0.3140409 -14.915927 1
#> 3 1 -12.20 -2.55 0.17639901 -0.37834947 -12.0236010 -2.928349 2
#> 4 1 -2.30 -13.70 1.80963710 2.04380379 -0.4903629 -11.656196 1
#> 5 1 -12.60 -7.80 0.51797647 -0.64680695 -12.0820235 -8.446807 2
#> 6 1 -7.60 -12.40 -0.88434528 1.10320032 -8.4843453 -11.296800 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5060 -74425 15200
#> initial value 998.131940
#> iter 2 value 652.452426
#> iter 3 value 652.437905
#> iter 4 value 652.431238
#> iter 5 value 629.570023
#> iter 6 value 626.778472
#> iter 7 value 626.698595
#> iter 8 value 626.698063
#> iter 8 value 626.698060
#> final value 626.698060
#> converged
#> This is Run number 218
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.7641665 -0.04677795 -2.535834 -12.6467780 1
#> 2 1 -0.35 -14.40 1.4075321 -0.82038328 1.057532 -15.2203833 1
#> 3 1 -12.20 -2.55 2.6359242 2.41385121 -9.564076 -0.1361488 2
#> 4 1 -2.30 -13.70 0.1055531 -0.43750130 -2.194447 -14.1375013 1
#> 5 1 -12.60 -7.80 -0.8050391 0.80721627 -13.405039 -6.9927837 2
#> 6 1 -7.60 -12.40 0.2383495 -1.08784033 -7.361651 -13.4878403 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4280 -70850 14400
#> initial value 998.131940
#> iter 2 value 686.587885
#> iter 3 value 686.463052
#> iter 4 value 686.392630
#> iter 5 value 667.753495
#> iter 6 value 665.816800
#> iter 7 value 665.775590
#> iter 8 value 665.775360
#> iter 8 value 665.775358
#> final value 665.775358
#> converged
#> This is Run number 219
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.08928858 -0.4570340 -4.2107114 -13.057034 1
#> 2 1 -0.35 -14.40 -0.42951763 1.4523938 -0.7795176 -12.947606 1
#> 3 1 -12.20 -2.55 1.62172625 -1.1370329 -10.5782738 -3.687033 2
#> 4 1 -2.30 -13.70 1.52100787 0.9336309 -0.7789921 -12.766369 1
#> 5 1 -12.60 -7.80 -0.26708947 4.1203693 -12.8670895 -3.679631 2
#> 6 1 -7.60 -12.40 2.17621119 0.3689724 -5.4237888 -12.031028 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4820 -74050 15000
#> initial value 998.131940
#> iter 2 value 656.442043
#> iter 3 value 656.428101
#> iter 4 value 656.416124
#> iter 5 value 634.093622
#> iter 6 value 631.355784
#> iter 7 value 631.278544
#> iter 8 value 631.277992
#> iter 8 value 631.277988
#> final value 631.277988
#> converged
#> This is Run number 220
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.69830227 4.634559 -4.998302 -7.965441 1
#> 2 1 -0.35 -14.40 -0.69786333 1.107616 -1.047863 -13.292384 1
#> 3 1 -12.20 -2.55 -0.41293377 1.699451 -12.612934 -0.850549 2
#> 4 1 -2.30 -13.70 -0.16701315 1.403318 -2.467013 -12.296682 1
#> 5 1 -12.60 -7.80 -0.06069131 4.234473 -12.660691 -3.565527 2
#> 6 1 -7.60 -12.40 0.58830773 -1.261409 -7.011692 -13.661409 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4360 -72475 15175
#> initial value 998.131940
#> iter 2 value 670.692696
#> iter 3 value 670.550627
#> iter 4 value 670.430653
#> iter 5 value 649.785776
#> iter 6 value 647.374035
#> iter 7 value 647.310784
#> iter 8 value 647.310322
#> iter 8 value 647.310319
#> final value 647.310319
#> converged
#> This is Run number 221
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.007939536 0.04380036 -4.307940 -12.556200 1
#> 2 1 -0.35 -14.40 1.914303577 -1.43697479 1.564304 -15.836975 1
#> 3 1 -12.20 -2.55 0.006985356 2.03885097 -12.193015 -0.511149 2
#> 4 1 -2.30 -13.70 0.572527823 0.50315254 -1.727472 -13.196847 1
#> 5 1 -12.60 -7.80 -0.438306781 -1.32755633 -13.038307 -9.127556 2
#> 6 1 -7.60 -12.40 2.801312182 2.16585975 -4.798688 -10.234140 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4520 -71075 14000
#> initial value 998.131940
#> iter 2 value 685.189820
#> iter 3 value 685.182542
#> iter 4 value 685.147240
#> iter 5 value 666.450888
#> iter 6 value 664.528973
#> iter 7 value 664.488390
#> iter 8 value 664.488199
#> iter 8 value 664.488198
#> final value 664.488198
#> converged
#> This is Run number 222
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.74311046 1.13617435 -2.5568895 -11.463826 1
#> 2 1 -0.35 -14.40 0.70438278 0.05681071 0.3543828 -14.343189 1
#> 3 1 -12.20 -2.55 1.17996018 0.20517106 -11.0200398 -2.344829 2
#> 4 1 -2.30 -13.70 0.01894471 1.28758300 -2.2810553 -12.412417 1
#> 5 1 -12.60 -7.80 0.14846457 0.05722016 -12.4515354 -7.742780 2
#> 6 1 -7.60 -12.40 0.07227273 -1.45917823 -7.5277273 -13.859178 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4780 -70625 13100
#> initial value 998.131940
#> iter 2 value 690.457206
#> iter 3 value 690.278360
#> iter 4 value 690.258551
#> iter 5 value 672.362759
#> iter 6 value 670.628464
#> iter 7 value 670.596266
#> iter 8 value 670.596159
#> iter 8 value 670.596158
#> final value 670.596158
#> converged
#> This is Run number 223
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.01431477 0.7419670 -4.2856852 -11.858033 1
#> 2 1 -0.35 -14.40 1.25283968 2.4273559 0.9028397 -11.972644 1
#> 3 1 -12.20 -2.55 -1.13109055 -0.1812293 -13.3310905 -2.731229 2
#> 4 1 -2.30 -13.70 0.55394788 -0.8984794 -1.7460521 -14.598479 1
#> 5 1 -12.60 -7.80 0.55835353 0.5036373 -12.0416465 -7.296363 2
#> 6 1 -7.60 -12.40 0.30677822 -0.8845258 -7.2932218 -13.284526 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5100 -73400 15025
#> initial value 998.131940
#> iter 2 value 662.179881
#> iter 3 value 662.151641
#> iter 4 value 662.127582
#> iter 5 value 640.644942
#> iter 6 value 638.117754
#> iter 7 value 638.052816
#> iter 8 value 638.052459
#> iter 8 value 638.052457
#> final value 638.052457
#> converged
#> This is Run number 224
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.2177403 0.2031342 -4.5177403 -12.396866 1
#> 2 1 -0.35 -14.40 2.0731325 -1.0454440 1.7231325 -15.445444 1
#> 3 1 -12.20 -2.55 0.1678727 0.9588104 -12.0321273 -1.591190 2
#> 4 1 -2.30 -13.70 3.0690418 -0.8859942 0.7690418 -14.585994 1
#> 5 1 -12.60 -7.80 0.7341547 1.1218574 -11.8658453 -6.678143 2
#> 6 1 -7.60 -12.40 1.2071615 0.5046626 -6.3928385 -11.895337 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5840 -72600 13725
#> initial value 998.131940
#> iter 2 value 671.197942
#> iter 3 value 670.785852
#> iter 4 value 670.456038
#> iter 5 value 650.024738
#> iter 6 value 647.826890
#> iter 7 value 647.779419
#> iter 8 value 647.779272
#> iter 8 value 647.779272
#> final value 647.779272
#> converged
#> This is Run number 225
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.4187726 -1.73282511 -4.7187726 -14.3328251 1
#> 2 1 -0.35 -14.40 -0.4325254 -0.19037474 -0.7825254 -14.5903747 1
#> 3 1 -12.20 -2.55 2.5465865 2.44540911 -9.6534135 -0.1045909 2
#> 4 1 -2.30 -13.70 -0.8775882 5.12996652 -3.1775882 -8.5700335 1
#> 5 1 -12.60 -7.80 -0.8626537 3.02513079 -13.4626537 -4.7748692 2
#> 6 1 -7.60 -12.40 0.9065440 -0.07628279 -6.6934560 -12.4762828 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5200 -72650 15300
#> initial value 998.131940
#> iter 2 value 668.384383
#> iter 3 value 668.246235
#> iter 4 value 668.123962
#> iter 5 value 647.373563
#> iter 6 value 645.009503
#> iter 7 value 644.952169
#> iter 8 value 644.951894
#> iter 8 value 644.951892
#> final value 644.951892
#> converged
#> This is Run number 226
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.303376382 1.0443231 -4.603376 -11.555677 1
#> 2 1 -0.35 -14.40 -0.373875025 0.5131312 -0.723875 -13.886869 1
#> 3 1 -12.20 -2.55 -0.708846546 -0.3186525 -12.908847 -2.868652 2
#> 4 1 -2.30 -13.70 -0.002996524 -0.2623868 -2.302997 -13.962387 1
#> 5 1 -12.60 -7.80 -0.774473793 -0.1037000 -13.374474 -7.903700 2
#> 6 1 -7.60 -12.40 1.616132214 0.7133395 -5.983868 -11.686660 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4160 -70825 15275
#> initial value 998.131940
#> iter 2 value 685.229126
#> iter 3 value 684.976066
#> iter 4 value 684.838153
#> iter 5 value 665.935618
#> iter 6 value 663.896073
#> iter 7 value 663.849113
#> iter 8 value 663.848821
#> iter 8 value 663.848820
#> final value 663.848820
#> converged
#> This is Run number 227
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.1377068 0.2652492 -3.1622932 -12.3347508 1
#> 2 1 -0.35 -14.40 0.1604769 0.2168712 -0.1895231 -14.1831288 1
#> 3 1 -12.20 -2.55 -0.3869732 2.9054032 -12.5869732 0.3554032 2
#> 4 1 -2.30 -13.70 1.0895612 -0.5330454 -1.2104388 -14.2330454 1
#> 5 1 -12.60 -7.80 1.3532845 0.4809421 -11.2467155 -7.3190579 2
#> 6 1 -7.60 -12.40 -0.3246704 0.6157894 -7.9246704 -11.7842106 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4620 -71025 14750
#> initial value 998.131940
#> iter 2 value 684.236843
#> iter 3 value 684.199655
#> iter 4 value 684.195602
#> iter 5 value 665.349474
#> iter 6 value 663.471853
#> iter 7 value 663.432105
#> iter 8 value 663.431924
#> iter 8 value 663.431923
#> final value 663.431923
#> converged
#> This is Run number 228
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.04845498 0.9150086 -4.2515450 -11.684991 1
#> 2 1 -0.35 -14.40 1.17451958 -0.6630735 0.8245196 -15.063074 1
#> 3 1 -12.20 -2.55 -0.91207616 1.3940453 -13.1120762 -1.155955 2
#> 4 1 -2.30 -13.70 0.62193826 0.4031335 -1.6780617 -13.296867 1
#> 5 1 -12.60 -7.80 4.85527384 -0.1992367 -7.7447262 -7.999237 1
#> 6 1 -7.60 -12.40 0.88509677 -1.2950023 -6.7149032 -13.695002 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4800 -74925 14775
#> initial value 998.131940
#> iter 2 value 648.752516
#> iter 3 value 648.703669
#> iter 4 value 648.671976
#> iter 5 value 625.289234
#> iter 6 value 622.264446
#> iter 7 value 622.171440
#> iter 8 value 622.170676
#> iter 8 value 622.170670
#> final value 622.170670
#> converged
#> This is Run number 229
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.07712247 1.7013183 -4.222878 -10.898682 1
#> 2 1 -0.35 -14.40 -1.65634892 -0.2479495 -2.006349 -14.647950 1
#> 3 1 -12.20 -2.55 -0.85750384 0.7802696 -13.057504 -1.769730 2
#> 4 1 -2.30 -13.70 0.34872976 0.6854227 -1.951270 -13.014577 1
#> 5 1 -12.60 -7.80 -0.79164380 1.2130278 -13.391644 -6.586972 2
#> 6 1 -7.60 -12.40 1.85739747 1.2268456 -5.742603 -11.173154 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5200 -73750 16175
#> initial value 998.131940
#> iter 2 value 656.626967
#> iter 3 value 656.281522
#> iter 4 value 656.097714
#> iter 5 value 633.662861
#> iter 6 value 630.863809
#> iter 7 value 630.785182
#> iter 8 value 630.784692
#> iter 8 value 630.784689
#> final value 630.784689
#> converged
#> This is Run number 230
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.2735139 -0.1403669 -4.5735139 -12.740367 1
#> 2 1 -0.35 -14.40 -0.5165112 -0.3164245 -0.8665112 -14.716424 1
#> 3 1 -12.20 -2.55 -0.2368220 0.2116994 -12.4368220 -2.338301 2
#> 4 1 -2.30 -13.70 0.5504173 -0.6571167 -1.7495827 -14.357117 1
#> 5 1 -12.60 -7.80 -1.1355221 -0.4068305 -13.7355221 -8.206831 2
#> 6 1 -7.60 -12.40 1.2913993 -0.8049417 -6.3086007 -13.204942 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5560 -70000 12375
#> initial value 998.131940
#> iter 2 value 696.447559
#> iter 3 value 695.836644
#> iter 4 value 695.595505
#> iter 5 value 678.423533
#> iter 6 value 676.848030
#> iter 7 value 676.822445
#> iter 8 value 676.822396
#> iter 8 value 676.822396
#> final value 676.822396
#> converged
#> This is Run number 231
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.5545065 1.27794033 -4.8545065 -11.322060 1
#> 2 1 -0.35 -14.40 4.8694314 1.48549572 4.5194314 -12.914504 1
#> 3 1 -12.20 -2.55 -0.8379278 1.54993186 -13.0379278 -1.000068 2
#> 4 1 -2.30 -13.70 1.7313063 1.69219890 -0.5686937 -12.007801 1
#> 5 1 -12.60 -7.80 1.8908371 -0.05996545 -10.7091629 -7.859965 2
#> 6 1 -7.60 -12.40 3.3426218 -0.60987910 -4.2573782 -13.009879 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4580 -71575 15675
#> initial value 998.131940
#> iter 2 value 677.619981
#> iter 3 value 677.371676
#> iter 4 value 677.371499
#> iter 5 value 662.168531
#> iter 6 value 655.519379
#> iter 7 value 655.379934
#> iter 8 value 655.378358
#> iter 8 value 655.378353
#> final value 655.378353
#> converged
#> This is Run number 232
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.8599167 0.1937629 -2.44008328 -12.4062371 1
#> 2 1 -0.35 -14.40 0.2608588 4.2465129 -0.08914121 -10.1534871 1
#> 3 1 -12.20 -2.55 5.0470038 2.3215696 -7.15299619 -0.2284304 2
#> 4 1 -2.30 -13.70 -0.2015842 0.9537678 -2.50158425 -12.7462322 1
#> 5 1 -12.60 -7.80 -1.1201836 1.7023686 -13.72018362 -6.0976314 2
#> 6 1 -7.60 -12.40 -0.9033292 0.5122896 -8.50332919 -11.8877104 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5160 -74375 15400
#> initial value 998.131940
#> iter 2 value 652.465293
#> iter 3 value 652.412301
#> iter 4 value 652.371362
#> iter 5 value 629.565140
#> iter 6 value 626.705263
#> iter 7 value 626.623804
#> iter 8 value 626.623274
#> iter 8 value 626.623271
#> final value 626.623271
#> converged
#> This is Run number 233
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.6723535 0.51077303 -3.6276465 -12.089227 1
#> 2 1 -0.35 -14.40 1.1967871 2.46753708 0.8467871 -11.932463 1
#> 3 1 -12.20 -2.55 0.1341029 -0.82070440 -12.0658971 -3.370704 2
#> 4 1 -2.30 -13.70 1.0318393 0.68360468 -1.2681607 -13.016395 1
#> 5 1 -12.60 -7.80 0.4068778 -0.06935076 -12.1931222 -7.869351 2
#> 6 1 -7.60 -12.40 0.3362510 3.25514815 -7.2637490 -9.144852 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5300 -72825 14150
#> initial value 998.131940
#> iter 2 value 668.848568
#> iter 3 value 668.767449
#> iter 4 value 668.698691
#> iter 5 value 648.192325
#> iter 6 value 645.911202
#> iter 7 value 645.859407
#> iter 8 value 645.859198
#> iter 8 value 645.859197
#> final value 645.859197
#> converged
#> This is Run number 234
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.0871011 0.28376700 -3.2128989 -12.3162330 1
#> 2 1 -0.35 -14.40 1.2168958 -0.02260377 0.8668958 -14.4226038 1
#> 3 1 -12.20 -2.55 -0.6075307 1.77144258 -12.8075307 -0.7785574 2
#> 4 1 -2.30 -13.70 4.1537316 -1.99326188 1.8537316 -15.6932619 1
#> 5 1 -12.60 -7.80 0.7005238 1.64218901 -11.8994762 -6.1578110 2
#> 6 1 -7.60 -12.40 0.5130011 0.13423623 -7.0869989 -12.2657638 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4760 -73700 14750
#> initial value 998.131940
#> iter 2 value 660.156461
#> iter 3 value 660.100619
#> iter 4 value 660.100050
#> iter 5 value 638.137669
#> iter 6 value 635.667332
#> iter 7 value 635.599976
#> iter 8 value 635.599533
#> iter 8 value 635.599529
#> final value 635.599529
#> converged
#> This is Run number 235
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.41003511 0.07428161 -3.889965 -12.525718 1
#> 2 1 -0.35 -14.40 0.05884201 0.65680239 -0.291158 -13.743198 1
#> 3 1 -12.20 -2.55 1.33873639 0.94137409 -10.861264 -1.608626 2
#> 4 1 -2.30 -13.70 -0.54614729 -0.82423194 -2.846147 -14.524232 1
#> 5 1 -12.60 -7.80 -1.15367967 -0.10263258 -13.753680 -7.902633 2
#> 6 1 -7.60 -12.40 0.51565637 -0.59821492 -7.084344 -12.998215 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4620 -72650 15650
#> initial value 998.131940
#> iter 2 value 668.048833
#> iter 3 value 667.870321
#> iter 4 value 667.864434
#> iter 5 value 646.855855
#> iter 6 value 644.462421
#> iter 7 value 644.399925
#> iter 8 value 644.399518
#> iter 8 value 644.399516
#> final value 644.399516
#> converged
#> This is Run number 236
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.3180397 -0.6162804 -2.981960 -13.2162804 1
#> 2 1 -0.35 -14.40 -0.4354380 3.4132135 -0.785438 -10.9867865 1
#> 3 1 -12.20 -2.55 0.5064067 3.4183579 -11.693593 0.8683579 2
#> 4 1 -2.30 -13.70 1.1438317 -0.1394733 -1.156168 -13.8394733 1
#> 5 1 -12.60 -7.80 0.8733053 3.0393825 -11.726695 -4.7606175 2
#> 6 1 -7.60 -12.40 1.9734926 1.1184412 -5.626507 -11.2815588 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4720 -73275 14025
#> initial value 998.131940
#> iter 2 value 665.343423
#> iter 3 value 665.241961
#> iter 4 value 665.160438
#> iter 5 value 644.068413
#> iter 6 value 641.610803
#> iter 7 value 641.548800
#> iter 8 value 641.548424
#> iter 8 value 641.548422
#> final value 641.548422
#> converged
#> This is Run number 237
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.7169320 0.5416463 -1.5830680 -12.0583537 1
#> 2 1 -0.35 -14.40 -0.1423354 0.9069586 -0.4923354 -13.4930414 1
#> 3 1 -12.20 -2.55 0.4041101 3.4467995 -11.7958899 0.8967995 2
#> 4 1 -2.30 -13.70 1.2835762 -0.8237264 -1.0164238 -14.5237264 1
#> 5 1 -12.60 -7.80 0.2076986 1.1633483 -12.3923014 -6.6366517 2
#> 6 1 -7.60 -12.40 0.6476212 -0.3686278 -6.9523788 -12.7686278 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4180 -68900 13725
#> initial value 998.131940
#> iter 2 value 704.623824
#> iter 3 value 704.370558
#> iter 4 value 704.360512
#> iter 5 value 687.933690
#> iter 6 value 686.427210
#> iter 7 value 686.401145
#> iter 8 value 686.401044
#> iter 8 value 686.401044
#> final value 686.401044
#> converged
#> This is Run number 238
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.6875786 -0.054681060 -3.612421 -12.654681 1
#> 2 1 -0.35 -14.40 2.6596129 0.401996101 2.309613 -13.998004 1
#> 3 1 -12.20 -2.55 0.1131563 -1.383613507 -12.086844 -3.933614 2
#> 4 1 -2.30 -13.70 0.9912293 2.505838599 -1.308771 -11.194161 1
#> 5 1 -12.60 -7.80 2.8951506 1.012511000 -9.704849 -6.787489 2
#> 6 1 -7.60 -12.40 -0.5000533 0.005955794 -8.100053 -12.394044 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4980 -73250 14625
#> initial value 998.131940
#> iter 2 value 664.361941
#> iter 3 value 664.360683
#> iter 4 value 664.359734
#> iter 5 value 642.714829
#> iter 6 value 640.733177
#> iter 7 value 640.682852
#> iter 8 value 640.682610
#> iter 8 value 640.682608
#> final value 640.682608
#> converged
#> This is Run number 239
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 5.0638453 -0.92318491 0.7638453 -13.523185 1
#> 2 1 -0.35 -14.40 1.3690990 0.29198789 1.0190990 -14.108012 1
#> 3 1 -12.20 -2.55 -1.2328442 -0.05225802 -13.4328442 -2.602258 2
#> 4 1 -2.30 -13.70 0.3436255 1.26566302 -1.9563745 -12.434337 1
#> 5 1 -12.60 -7.80 -0.5067772 -0.45688954 -13.1067772 -8.256890 2
#> 6 1 -7.60 -12.40 0.6261307 0.03865350 -6.9738693 -12.361347 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5260 -69175 13425
#> initial value 998.131940
#> iter 2 value 702.145803
#> iter 3 value 701.978629
#> iter 4 value 701.873927
#> iter 5 value 685.248031
#> iter 6 value 683.775980
#> iter 7 value 683.752970
#> iter 8 value 683.752923
#> iter 8 value 683.752923
#> final value 683.752923
#> converged
#> This is Run number 240
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.2493319 -1.01362787 -4.5493319 -13.6136279 1
#> 2 1 -0.35 -14.40 0.9121884 0.99736291 0.5621884 -13.4026371 1
#> 3 1 -12.20 -2.55 -0.9382138 2.14744644 -13.1382138 -0.4025536 2
#> 4 1 -2.30 -13.70 0.3737832 -0.09114801 -1.9262168 -13.7911480 1
#> 5 1 -12.60 -7.80 0.2010661 1.62164789 -12.3989339 -6.1783521 2
#> 6 1 -7.60 -12.40 0.6242573 2.12375730 -6.9757427 -10.2762427 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5440 -74300 14550
#> initial value 998.131940
#> iter 2 value 654.557648
#> iter 3 value 654.476850
#> iter 4 value 654.420095
#> iter 5 value 631.987816
#> iter 6 value 629.267288
#> iter 7 value 629.195710
#> iter 8 value 629.195349
#> iter 8 value 629.195347
#> final value 629.195347
#> converged
#> This is Run number 241
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.69388333 1.99415856 -4.993883 -10.605841 1
#> 2 1 -0.35 -14.40 1.60077297 0.68771398 1.250773 -13.712286 1
#> 3 1 -12.20 -2.55 0.90398327 0.25455252 -11.296017 -2.295447 2
#> 4 1 -2.30 -13.70 -0.41308901 -1.13498262 -2.713089 -14.834983 1
#> 5 1 -12.60 -7.80 3.03786132 -0.03984072 -9.562139 -7.839841 2
#> 6 1 -7.60 -12.40 -0.05331178 -0.62975939 -7.653312 -13.029759 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4380 -72450 14750
#> initial value 998.131940
#> iter 2 value 671.706156
#> iter 3 value 671.625643
#> iter 4 value 671.546153
#> iter 5 value 650.985031
#> iter 6 value 648.636203
#> iter 7 value 648.577297
#> iter 8 value 648.576882
#> iter 8 value 648.576878
#> final value 648.576878
#> converged
#> This is Run number 242
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.2141262 0.82540150 -4.0858738 -11.774599 1
#> 2 1 -0.35 -14.40 0.1960637 1.05455884 -0.1539363 -13.345441 1
#> 3 1 -12.20 -2.55 -0.7988749 -0.54679363 -12.9988749 -3.096794 2
#> 4 1 -2.30 -13.70 1.7388924 -0.42118783 -0.5611076 -14.121188 1
#> 5 1 -12.60 -7.80 0.1142897 -0.09491187 -12.4857103 -7.894912 2
#> 6 1 -7.60 -12.40 2.4237886 0.37181359 -5.1762114 -12.028186 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4100 -71650 13975
#> initial value 998.131940
#> iter 2 value 680.359644
#> iter 3 value 679.747649
#> iter 4 value 679.608480
#> iter 5 value 660.128987
#> iter 6 value 657.988873
#> iter 7 value 657.937754
#> iter 8 value 657.937417
#> iter 8 value 657.937415
#> final value 657.937415
#> converged
#> This is Run number 243
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.4898983 1.0305800 -1.810102 -11.569420 1
#> 2 1 -0.35 -14.40 -0.9414847 0.1142303 -1.291485 -14.285770 1
#> 3 1 -12.20 -2.55 1.7655694 0.8974659 -10.434431 -1.652534 2
#> 4 1 -2.30 -13.70 0.1818143 2.3845766 -2.118186 -11.315423 1
#> 5 1 -12.60 -7.80 0.2344902 0.5543272 -12.365510 -7.245673 2
#> 6 1 -7.60 -12.40 0.2084198 -0.1850590 -7.391580 -12.585059 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4480 -73025 14300
#> initial value 998.131940
#> iter 2 value 667.271804
#> iter 3 value 667.100143
#> iter 4 value 667.017933
#> iter 5 value 646.006114
#> iter 6 value 643.552466
#> iter 7 value 643.488129
#> iter 8 value 643.487687
#> iter 8 value 643.487684
#> final value 643.487684
#> converged
#> This is Run number 244
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.5991997 -1.7118739 -3.7008003 -14.311874 1
#> 2 1 -0.35 -14.40 1.5993120 -0.1928885 1.2493120 -14.592888 1
#> 3 1 -12.20 -2.55 1.6065010 -0.5739311 -10.5934990 -3.123931 2
#> 4 1 -2.30 -13.70 1.8412577 -0.7225232 -0.4587423 -14.422523 1
#> 5 1 -12.60 -7.80 -0.3096537 3.8905829 -12.9096537 -3.909417 2
#> 6 1 -7.60 -12.40 0.4379676 1.4106537 -7.1620324 -10.989346 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4540 -72275 13775
#> initial value 998.131940
#> iter 2 value 674.901863
#> iter 3 value 674.755410
#> iter 4 value 674.629528
#> iter 5 value 654.682499
#> iter 6 value 652.482974
#> iter 7 value 652.432209
#> iter 8 value 652.431927
#> iter 8 value 652.431925
#> final value 652.431925
#> converged
#> This is Run number 245
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.49413719 -1.07849876 -1.8058628 -13.678499 1
#> 2 1 -0.35 -14.40 1.19314580 1.09534495 0.8431458 -13.304655 1
#> 3 1 -12.20 -2.55 2.05655798 0.08472238 -10.1434420 -2.465278 2
#> 4 1 -2.30 -13.70 -0.06092358 1.43708713 -2.3609236 -12.262913 1
#> 5 1 -12.60 -7.80 -0.36416829 2.15735989 -12.9641683 -5.642640 2
#> 6 1 -7.60 -12.40 -0.96179709 0.60680096 -8.5617971 -11.793199 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4560 -74000 14750
#> initial value 998.131940
#> iter 2 value 657.511465
#> iter 3 value 657.265751
#> iter 4 value 656.510609
#> iter 5 value 634.454977
#> iter 6 value 632.231998
#> iter 7 value 632.163602
#> iter 8 value 632.163095
#> iter 8 value 632.163092
#> final value 632.163092
#> converged
#> This is Run number 246
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.4194564 -1.3365626 -1.8805436 -13.936563 1
#> 2 1 -0.35 -14.40 0.8445475 1.1789884 0.4945475 -13.221012 1
#> 3 1 -12.20 -2.55 -0.7627074 -0.2007129 -12.9627074 -2.750713 2
#> 4 1 -2.30 -13.70 -0.0630102 0.1958599 -2.3630102 -13.504140 1
#> 5 1 -12.60 -7.80 -0.7366070 -0.1578939 -13.3366070 -7.957894 2
#> 6 1 -7.60 -12.40 0.1448710 0.9695566 -7.4551290 -11.430443 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4620 -74525 15400
#> initial value 998.131940
#> iter 2 value 651.399071
#> iter 3 value 651.312817
#> iter 4 value 651.236713
#> iter 5 value 628.098556
#> iter 6 value 625.089659
#> iter 7 value 624.995768
#> iter 8 value 624.994919
#> iter 8 value 624.994913
#> final value 624.994913
#> converged
#> This is Run number 247
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.2782877 2.242634e+00 -4.021712 -10.357366 1
#> 2 1 -0.35 -14.40 1.6291951 -6.570767e-01 1.279195 -15.057077 1
#> 3 1 -12.20 -2.55 -0.7247141 -6.742459e-02 -12.924714 -2.617425 2
#> 4 1 -2.30 -13.70 -0.2456888 9.858906e-02 -2.545689 -13.601411 1
#> 5 1 -12.60 -7.80 2.3260106 2.979349e-05 -10.273989 -7.799970 2
#> 6 1 -7.60 -12.40 0.8492539 -2.162265e-02 -6.750746 -12.421623 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4400 -72975 14950
#> initial value 998.131940
#> iter 2 value 666.587445
#> iter 3 value 666.477279
#> iter 4 value 666.395333
#> iter 5 value 645.191388
#> iter 6 value 642.660698
#> iter 7 value 642.590592
#> iter 8 value 642.590044
#> iter 8 value 642.590040
#> final value 642.590040
#> converged
#> This is Run number 248
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.4943540 -1.1463729 -4.794354 -13.746373 1
#> 2 1 -0.35 -14.40 -1.3065593 2.2232067 -1.656559 -12.176793 1
#> 3 1 -12.20 -2.55 -1.4821164 0.7615525 -13.682116 -1.788447 2
#> 4 1 -2.30 -13.70 -0.2439689 0.9613769 -2.543969 -12.738623 1
#> 5 1 -12.60 -7.80 1.3840864 1.4553541 -11.215914 -6.344646 2
#> 6 1 -7.60 -12.40 0.4757364 1.4375666 -7.124264 -10.962433 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4480 -74150 14200
#> initial value 998.131940
#> iter 2 value 657.148044
#> iter 3 value 656.938474
#> iter 4 value 656.929530
#> iter 5 value 634.260340
#> iter 6 value 631.471782
#> iter 7 value 631.391495
#> iter 8 value 631.390821
#> iter 8 value 631.390815
#> final value 631.390815
#> converged
#> This is Run number 249
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.2978765 0.5201540 -4.597877 -12.079846 1
#> 2 1 -0.35 -14.40 2.4170190 -0.4937921 2.067019 -14.893792 1
#> 3 1 -12.20 -2.55 -1.3450062 -0.9561250 -13.545006 -3.506125 2
#> 4 1 -2.30 -13.70 0.4264001 -0.8668838 -1.873600 -14.566884 1
#> 5 1 -12.60 -7.80 -0.4774402 1.4111303 -13.077440 -6.388870 2
#> 6 1 -7.60 -12.40 0.1326592 3.7352657 -7.467341 -8.664734 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4580 -73825 15475
#> initial value 998.131940
#> iter 2 value 657.734469
#> iter 3 value 657.622879
#> iter 4 value 657.559679
#> iter 5 value 635.271430
#> iter 6 value 632.475337
#> iter 7 value 632.393376
#> iter 8 value 632.392702
#> iter 8 value 632.392697
#> final value 632.392697
#> converged
#> This is Run number 250
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 5.8109132 -0.34646643 1.5109132 -12.946466 1
#> 2 1 -0.35 -14.40 -0.5081534 -0.09223055 -0.8581534 -14.492231 1
#> 3 1 -12.20 -2.55 1.9591842 0.61101000 -10.2408158 -1.938990 2
#> 4 1 -2.30 -13.70 0.9006891 -0.24049724 -1.3993109 -13.940497 1
#> 5 1 -12.60 -7.80 3.3110069 -0.64110409 -9.2889931 -8.441104 2
#> 6 1 -7.60 -12.40 0.2260068 0.18424259 -7.3739932 -12.215757 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4660 -70950 14800
#> initial value 998.131940
#> iter 2 value 684.779500
#> iter 3 value 684.736154
#> iter 4 value 684.735939
#> iter 5 value 664.337672
#> iter 6 value 664.065848
#> iter 7 value 664.059169
#> iter 8 value 664.059152
#> iter 8 value 664.059152
#> final value 664.059152
#> converged
#> This is Run number 251
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.8023739 1.7292773 -3.49762607 -10.870723 1
#> 2 1 -0.35 -14.40 0.4300765 0.1895780 0.08007646 -14.210422 1
#> 3 1 -12.20 -2.55 0.1191241 0.7641694 -12.08087594 -1.785831 2
#> 4 1 -2.30 -13.70 -1.0390929 -1.0112443 -3.33909291 -14.711244 1
#> 5 1 -12.60 -7.80 4.6068466 0.2991724 -7.99315340 -7.500828 2
#> 6 1 -7.60 -12.40 0.1432808 1.6690425 -7.45671923 -10.730958 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4260 -72750 14950
#> initial value 998.131940
#> iter 2 value 668.691598
#> iter 3 value 668.524138
#> iter 4 value 668.395596
#> iter 5 value 647.341442
#> iter 6 value 644.836112
#> iter 7 value 644.765765
#> iter 8 value 644.765187
#> iter 8 value 644.765184
#> final value 644.765184
#> converged
#> This is Run number 252
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.50388820 -0.4028524 -3.7961118 -13.002852 1
#> 2 1 -0.35 -14.40 -0.21906694 -0.1557592 -0.5690669 -14.555759 1
#> 3 1 -12.20 -2.55 0.50125599 -0.8706831 -11.6987440 -3.420683 2
#> 4 1 -2.30 -13.70 -0.05900488 0.2624220 -2.3590049 -13.437578 1
#> 5 1 -12.60 -7.80 0.23414361 1.2177371 -12.3658564 -6.582263 2
#> 6 1 -7.60 -12.40 -1.47637949 -0.8964383 -9.0763795 -13.296438 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4380 -71200 15150
#> initial value 998.131940
#> iter 2 value 682.071740
#> iter 3 value 681.927793
#> iter 4 value 681.873783
#> iter 5 value 662.702269
#> iter 6 value 660.630559
#> iter 7 value 660.583317
#> iter 8 value 660.583046
#> iter 8 value 660.583044
#> final value 660.583044
#> converged
#> This is Run number 253
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.2910900 1.29005725 -4.59109003 -11.309943 1
#> 2 1 -0.35 -14.40 -0.3346351 -0.86627805 -0.68463513 -15.266278 1
#> 3 1 -12.20 -2.55 -0.0787150 -0.44544542 -12.27871500 -2.995445 2
#> 4 1 -2.30 -13.70 2.2285504 1.67456708 -0.07144958 -12.025433 1
#> 5 1 -12.60 -7.80 -0.7243755 -0.07653843 -13.32437553 -7.876538 2
#> 6 1 -7.60 -12.40 -0.2244782 -0.39709480 -7.82447817 -12.797095 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4960 -70150 14425
#> initial value 998.131940
#> iter 2 value 692.256323
#> iter 3 value 692.208675
#> iter 4 value 692.173057
#> iter 5 value 674.420500
#> iter 6 value 672.695798
#> iter 7 value 672.664234
#> iter 8 value 672.664136
#> iter 8 value 672.664135
#> final value 672.664135
#> converged
#> This is Run number 254
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.3882172 1.3688034 -3.911783 -11.23120 1
#> 2 1 -0.35 -14.40 2.4125825 -0.6657654 2.062582 -15.06577 1
#> 3 1 -12.20 -2.55 0.4919590 -0.3049703 -11.708041 -2.85497 2
#> 4 1 -2.30 -13.70 1.0084794 -0.2434229 -1.291521 -13.94342 1
#> 5 1 -12.60 -7.80 3.4904474 0.4240802 -9.109553 -7.37592 2
#> 6 1 -7.60 -12.40 -0.4902945 -0.7751962 -8.090294 -13.17520 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5060 -71975 13625
#> initial value 998.131940
#> iter 2 value 677.526869
#> iter 3 value 677.419141
#> iter 4 value 677.414836
#> iter 5 value 657.925255
#> iter 6 value 655.958874
#> iter 7 value 655.917540
#> iter 8 value 655.917389
#> iter 8 value 655.917388
#> final value 655.917388
#> converged
#> This is Run number 255
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 4.3797202 1.1296942 0.07972018 -11.470306 1
#> 2 1 -0.35 -14.40 -0.4408294 -0.2565228 -0.79082938 -14.656523 1
#> 3 1 -12.20 -2.55 0.2127612 1.3335998 -11.98723882 -1.216400 2
#> 4 1 -2.30 -13.70 1.0382818 2.2958964 -1.26171817 -11.404104 1
#> 5 1 -12.60 -7.80 -0.6107146 -1.0314119 -13.21071458 -8.831412 2
#> 6 1 -7.60 -12.40 1.2315694 2.5718509 -6.36843063 -9.828149 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5380 -75425 15100
#> initial value 998.131940
#> iter 2 value 643.092871
#> iter 3 value 642.995217
#> iter 4 value 642.988146
#> iter 5 value 618.975182
#> iter 6 value 615.843478
#> iter 7 value 615.748726
#> iter 8 value 615.748092
#> iter 8 value 615.748088
#> final value 615.748088
#> converged
#> This is Run number 256
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.3175928 -0.2059716 -4.6175928 -12.805972 1
#> 2 1 -0.35 -14.40 -0.5734087 0.9278054 -0.9234087 -13.472195 1
#> 3 1 -12.20 -2.55 -0.1883754 0.7886399 -12.3883754 -1.761360 2
#> 4 1 -2.30 -13.70 -0.2664034 1.7676157 -2.5664034 -11.932384 1
#> 5 1 -12.60 -7.80 0.1346265 0.9253432 -12.4653735 -6.874657 2
#> 6 1 -7.60 -12.40 0.6019409 1.1591923 -6.9980591 -11.240808 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5240 -73725 13875
#> initial value 998.131940
#> iter 2 value 661.161001
#> iter 3 value 661.025778
#> iter 4 value 661.015471
#> iter 5 value 639.493021
#> iter 6 value 637.026696
#> iter 7 value 636.965641
#> iter 8 value 636.965354
#> iter 8 value 636.965352
#> final value 636.965352
#> converged
#> This is Run number 257
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.9039800 0.295634991 -2.39602005 -12.304365 1
#> 2 1 -0.35 -14.40 0.4353358 -0.216174645 0.08533583 -14.616175 1
#> 3 1 -12.20 -2.55 0.6446138 0.508093094 -11.55538620 -2.041907 2
#> 4 1 -2.30 -13.70 0.8338218 -0.008682991 -1.46617825 -13.708683 1
#> 5 1 -12.60 -7.80 1.0899152 0.103162600 -11.51008477 -7.696837 2
#> 6 1 -7.60 -12.40 -0.2507391 -0.218180489 -7.85073915 -12.618180 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4520 -71275 15150
#> initial value 998.131940
#> iter 2 value 681.337384
#> iter 3 value 681.223948
#> iter 4 value 681.210880
#> iter 5 value 661.980330
#> iter 6 value 659.934020
#> iter 7 value 659.888088
#> iter 8 value 659.887844
#> iter 8 value 659.887843
#> final value 659.887843
#> converged
#> This is Run number 258
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.08364950 1.7516630 -4.383650 -10.848337 1
#> 2 1 -0.35 -14.40 2.23379762 -1.2462269 1.883798 -15.646227 1
#> 3 1 -12.20 -2.55 0.27218528 -0.4246065 -11.927815 -2.974607 2
#> 4 1 -2.30 -13.70 0.36910237 0.5865543 -1.930898 -13.113446 1
#> 5 1 -12.60 -7.80 -0.13950776 -1.0409098 -12.739508 -8.840910 2
#> 6 1 -7.60 -12.40 -0.07492401 0.4557141 -7.674924 -11.944286 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4820 -72500 14475
#> initial value 998.131940
#> iter 2 value 671.514248
#> iter 3 value 671.511423
#> iter 4 value 671.509290
#> iter 5 value 651.153515
#> iter 6 value 648.979637
#> iter 7 value 648.928299
#> iter 8 value 648.928037
#> iter 8 value 648.928035
#> final value 648.928035
#> converged
#> This is Run number 259
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.0737602 1.3998991 -5.3737602 -11.200101 1
#> 2 1 -0.35 -14.40 0.7869265 1.6182955 0.4369265 -12.781705 1
#> 3 1 -12.20 -2.55 -0.2572079 -1.2243382 -12.4572079 -3.774338 2
#> 4 1 -2.30 -13.70 -0.8434311 5.8115425 -3.1434311 -7.888458 1
#> 5 1 -12.60 -7.80 1.7918776 -0.5610717 -10.8081224 -8.361072 2
#> 6 1 -7.60 -12.40 1.5860982 1.0751731 -6.0139018 -11.324827 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5060 -71425 14575
#> initial value 998.131940
#> iter 2 value 680.768920
#> iter 3 value 680.721226
#> iter 4 value 680.689947
#> iter 5 value 661.573029
#> iter 6 value 659.579545
#> iter 7 value 659.538438
#> iter 8 value 659.538279
#> iter 8 value 659.538278
#> final value 659.538278
#> converged
#> This is Run number 260
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.2193901 0.6928522 -3.080610 -11.907148 1
#> 2 1 -0.35 -14.40 2.3913218 1.0517306 2.041322 -13.348269 1
#> 3 1 -12.20 -2.55 3.0583352 1.0536619 -9.141665 -1.496338 2
#> 4 1 -2.30 -13.70 -1.1216490 0.5965204 -3.421649 -13.103480 1
#> 5 1 -12.60 -7.80 0.6357287 1.4983778 -11.964271 -6.301622 2
#> 6 1 -7.60 -12.40 1.3326192 2.2022614 -6.267381 -10.197739 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4600 -72850 14025
#> initial value 998.131940
#> iter 2 value 669.268752
#> iter 3 value 669.160545
#> iter 4 value 669.072244
#> iter 5 value 648.407020
#> iter 6 value 646.047697
#> iter 7 value 645.989982
#> iter 8 value 645.989633
#> iter 8 value 645.989630
#> final value 645.989630
#> converged
#> This is Run number 261
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.3842800 -0.012724684 -4.68427997 -12.612725 1
#> 2 1 -0.35 -14.40 0.2782466 1.163155964 -0.07175339 -13.236844 1
#> 3 1 -12.20 -2.55 0.2931424 0.161703118 -11.90685761 -2.388297 2
#> 4 1 -2.30 -13.70 -0.3273053 1.337986232 -2.62730532 -12.362014 1
#> 5 1 -12.60 -7.80 0.6117565 -0.270787146 -11.98824348 -8.070787 2
#> 6 1 -7.60 -12.40 -0.9253262 -0.005815198 -8.52532623 -12.405815 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3780 -71525 14525
#> initial value 998.131940
#> iter 2 value 680.637801
#> iter 3 value 679.650150
#> iter 4 value 679.423236
#> iter 5 value 659.706983
#> iter 6 value 657.478497
#> iter 7 value 657.421415
#> iter 8 value 657.420914
#> iter 8 value 657.420910
#> final value 657.420910
#> converged
#> This is Run number 262
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.43849884 1.1763611 -3.861501 -11.423639 1
#> 2 1 -0.35 -14.40 -1.34277878 0.7703847 -1.692779 -13.629615 1
#> 3 1 -12.20 -2.55 -0.13760955 0.1690382 -12.337610 -2.380962 2
#> 4 1 -2.30 -13.70 0.85370230 2.8795591 -1.446298 -10.820441 1
#> 5 1 -12.60 -7.80 0.05762832 0.3626571 -12.542372 -7.437343 2
#> 6 1 -7.60 -12.40 1.82030301 -0.8254381 -5.779697 -13.225438 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3620 -69225 14025
#> initial value 998.131940
#> iter 2 value 701.583345
#> iter 3 value 700.520173
#> iter 4 value 700.354120
#> iter 5 value 683.217936
#> iter 6 value 681.530297
#> iter 7 value 681.496057
#> iter 8 value 681.495839
#> iter 8 value 681.495838
#> final value 681.495838
#> converged
#> This is Run number 263
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.3637780 -0.03215196 -4.663778e+00 -12.632152 1
#> 2 1 -0.35 -14.40 0.3508978 2.56540694 8.977669e-04 -11.834593 1
#> 3 1 -12.20 -2.55 1.1134895 0.94527828 -1.108651e+01 -1.604722 2
#> 4 1 -2.30 -13.70 -1.1505684 -0.33645425 -3.450568e+00 -14.036454 1
#> 5 1 -12.60 -7.80 -0.1901549 -0.68724217 -1.279015e+01 -8.487242 2
#> 6 1 -7.60 -12.40 -1.5333198 -0.17870652 -9.133320e+00 -12.578707 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5060 -73275 14925
#> initial value 998.131940
#> iter 2 value 663.531887
#> iter 3 value 663.515125
#> iter 4 value 663.501585
#> iter 5 value 642.197223
#> iter 6 value 639.720766
#> iter 7 value 639.658004
#> iter 8 value 639.657663
#> iter 8 value 639.657661
#> final value 639.657661
#> converged
#> This is Run number 264
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.4375650 3.00906201 -4.737565 -9.590938 1
#> 2 1 -0.35 -14.40 -0.7648377 2.95318253 -1.114838 -11.446817 1
#> 3 1 -12.20 -2.55 2.4691229 -0.05659151 -9.730877 -2.606592 2
#> 4 1 -2.30 -13.70 1.2828906 1.46179488 -1.017109 -12.238205 1
#> 5 1 -12.60 -7.80 -0.9133777 -0.16303995 -13.513378 -7.963040 2
#> 6 1 -7.60 -12.40 1.2292176 0.47010570 -6.370782 -11.929894 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4980 -71175 14525
#> initial value 998.131940
#> iter 2 value 683.115653
#> iter 3 value 683.115471
#> iter 4 value 683.094299
#> iter 5 value 664.239112
#> iter 6 value 662.303576
#> iter 7 value 662.264502
#> iter 8 value 662.264352
#> iter 8 value 662.264351
#> final value 662.264351
#> converged
#> This is Run number 265
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.1805004 3.8161900 -4.11949956 -8.7838100 1
#> 2 1 -0.35 -14.40 0.4151072 -0.1470447 0.06510724 -14.5470447 1
#> 3 1 -12.20 -2.55 -0.8201787 3.0933944 -13.02017870 0.5433944 2
#> 4 1 -2.30 -13.70 -1.3388539 -0.9002916 -3.63885387 -14.6002916 1
#> 5 1 -12.60 -7.80 0.8215684 0.4450172 -11.77843156 -7.3549828 2
#> 6 1 -7.60 -12.40 0.6640270 -0.2127937 -6.93597301 -12.6127937 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4420 -70500 14525
#> initial value 998.131940
#> iter 2 value 689.348530
#> iter 3 value 689.299137
#> iter 4 value 689.256937
#> iter 5 value 671.060223
#> iter 6 value 669.212002
#> iter 7 value 669.174179
#> iter 8 value 669.173999
#> iter 8 value 669.173998
#> final value 669.173998
#> converged
#> This is Run number 266
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.1782527 -0.06434555 -4.1217473 -12.6643456 1
#> 2 1 -0.35 -14.40 0.6392256 0.78821687 0.2892256 -13.6117831 1
#> 3 1 -12.20 -2.55 1.1371821 2.83023877 -11.0628179 0.2802388 2
#> 4 1 -2.30 -13.70 1.3063360 -1.00055442 -0.9936640 -14.7005544 1
#> 5 1 -12.60 -7.80 0.5928216 1.15531873 -12.0071784 -6.6446813 2
#> 6 1 -7.60 -12.40 1.2590661 -0.47811621 -6.3409339 -12.8781162 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4700 -70900 14150
#> initial value 998.131940
#> iter 2 value 686.366809
#> iter 3 value 686.362977
#> iter 4 value 686.361005
#> iter 5 value 667.875904
#> iter 6 value 666.061726
#> iter 7 value 666.025465
#> iter 8 value 666.025319
#> iter 8 value 666.025319
#> final value 666.025319
#> converged
#> This is Run number 267
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.1724730 0.3729927 -3.1275270 -12.227007 1
#> 2 1 -0.35 -14.40 -0.2916247 0.6395709 -0.6416247 -13.760429 1
#> 3 1 -12.20 -2.55 0.1521656 -0.2337892 -12.0478344 -2.783789 2
#> 4 1 -2.30 -13.70 0.8249650 0.5374955 -1.4750350 -13.162504 1
#> 5 1 -12.60 -7.80 -0.7557490 -0.8397867 -13.3557490 -8.639787 2
#> 6 1 -7.60 -12.40 2.7695437 2.2498342 -4.8304563 -10.150166 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4200 -73600 15650
#> initial value 998.131940
#> iter 2 value 659.640656
#> iter 3 value 659.339599
#> iter 4 value 659.076949
#> iter 5 value 636.756868
#> iter 6 value 633.901464
#> iter 7 value 633.812165
#> iter 8 value 633.811270
#> iter 8 value 633.811264
#> final value 633.811264
#> converged
#> This is Run number 268
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.4258114 0.2420306 -5.7258114 -12.357969 1
#> 2 1 -0.35 -14.40 1.1736004 1.4957275 0.8236004 -12.904273 1
#> 3 1 -12.20 -2.55 1.4940269 2.7380940 -10.7059731 0.188094 2
#> 4 1 -2.30 -13.70 6.2257400 -0.3583972 3.9257400 -14.058397 1
#> 5 1 -12.60 -7.80 -0.4211050 -1.3393225 -13.0211050 -9.139323 2
#> 6 1 -7.60 -12.40 -0.1417345 -0.3313833 -7.7417345 -12.731383 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4560 -74850 15325
#> initial value 998.131940
#> iter 2 value 648.552896
#> iter 3 value 648.449736
#> iter 4 value 648.407531
#> iter 5 value 624.743284
#> iter 6 value 621.612664
#> iter 7 value 621.510008
#> iter 8 value 621.508991
#> iter 8 value 621.508983
#> final value 621.508983
#> converged
#> This is Run number 269
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.3319042 -0.5991675 -5.6319042 -13.199167 1
#> 2 1 -0.35 -14.40 0.9718041 0.7466109 0.6218041 -13.653389 1
#> 3 1 -12.20 -2.55 2.3204149 -1.3231488 -9.8795851 -3.873149 2
#> 4 1 -2.30 -13.70 -0.2922158 -0.1861512 -2.5922158 -13.886151 1
#> 5 1 -12.60 -7.80 0.2096322 0.7658057 -12.3903678 -7.034194 2
#> 6 1 -7.60 -12.40 2.1816560 0.8214174 -5.4183440 -11.578583 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5000 -73075 14400
#> initial value 998.131940
#> iter 2 value 666.343210
#> iter 3 value 666.332235
#> iter 4 value 666.331303
#> iter 5 value 644.960342
#> iter 6 value 643.057460
#> iter 7 value 643.010531
#> iter 8 value 643.010320
#> iter 8 value 643.010319
#> final value 643.010319
#> converged
#> This is Run number 270
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.34734086 4.3744350 -5.6473409 -8.225565 1
#> 2 1 -0.35 -14.40 -0.16405849 0.6448403 -0.5140585 -13.755160 1
#> 3 1 -12.20 -2.55 1.82352439 -0.6770915 -10.3764756 -3.227091 2
#> 4 1 -2.30 -13.70 -0.65989920 3.1410387 -2.9598992 -10.558961 1
#> 5 1 -12.60 -7.80 1.58815190 -0.7950016 -11.0118481 -8.595002 2
#> 6 1 -7.60 -12.40 -0.06239161 -0.2509470 -7.6623916 -12.650947 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4660 -71325 13375
#> initial value 998.131940
#> iter 2 value 683.943861
#> iter 3 value 683.786697
#> iter 4 value 683.714834
#> iter 5 value 665.000868
#> iter 6 value 663.075814
#> iter 7 value 663.036525
#> iter 8 value 663.036359
#> iter 8 value 663.036358
#> final value 663.036358
#> converged
#> This is Run number 271
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.7220915 1.12296004 -2.577909 -11.477040 1
#> 2 1 -0.35 -14.40 -0.8458574 1.44977201 -1.195857 -12.950228 1
#> 3 1 -12.20 -2.55 2.0146100 -0.01906604 -10.185390 -2.569066 2
#> 4 1 -2.30 -13.70 1.0031233 0.46721508 -1.296877 -13.232785 1
#> 5 1 -12.60 -7.80 2.3412462 1.47285925 -10.258754 -6.327141 2
#> 6 1 -7.60 -12.40 -0.7906379 1.49530756 -8.390638 -10.904692 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4340 -72225 15875
#> initial value 998.131940
#> iter 2 value 671.555390
#> iter 3 value 671.221988
#> iter 4 value 671.157254
#> iter 5 value 650.507975
#> iter 6 value 648.079038
#> iter 7 value 648.014652
#> iter 8 value 648.014179
#> iter 8 value 648.014176
#> final value 648.014176
#> converged
#> This is Run number 272
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.51489169 0.62718161 -3.7851083 -11.9728184 1
#> 2 1 -0.35 -14.40 -0.13704729 0.55694088 -0.4870473 -13.8430591 1
#> 3 1 -12.20 -2.55 -0.98608828 2.89161643 -13.1860883 0.3416164 2
#> 4 1 -2.30 -13.70 -0.31700042 0.01811957 -2.6170004 -13.6818804 1
#> 5 1 -12.60 -7.80 -0.04978131 1.67566248 -12.6497813 -6.1243375 2
#> 6 1 -7.60 -12.40 1.50218693 -1.55645409 -6.0978131 -13.9564541 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4580 -72925 16050
#> initial value 998.131940
#> iter 2 value 664.772461
#> iter 3 value 664.463169
#> iter 4 value 664.457414
#> iter 5 value 642.914414
#> iter 6 value 640.386874
#> iter 7 value 640.317046
#> iter 8 value 640.316545
#> iter 8 value 640.316542
#> final value 640.316542
#> converged
#> This is Run number 273
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.266364025 1.7574417 -3.0336360 -10.8425583 1
#> 2 1 -0.35 -14.40 0.565854396 -0.9494555 0.2158544 -15.3494555 1
#> 3 1 -12.20 -2.55 0.051793577 2.2452226 -12.1482064 -0.3047774 2
#> 4 1 -2.30 -13.70 -0.001593889 -0.1693477 -2.3015939 -13.8693477 1
#> 5 1 -12.60 -7.80 3.544786050 -0.5566539 -9.0552139 -8.3566539 2
#> 6 1 -7.60 -12.40 0.890662874 -0.2882854 -6.7093371 -12.6882854 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5120 -70700 14750
#> initial value 998.131940
#> iter 2 value 686.776850
#> iter 3 value 686.659374
#> iter 4 value 686.622076
#> iter 5 value 668.088003
#> iter 6 value 666.231179
#> iter 7 value 666.193876
#> iter 8 value 666.193747
#> iter 8 value 666.193747
#> final value 666.193747
#> converged
#> This is Run number 274
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.4810309 0.5512813 -3.8189691 -12.0487187 1
#> 2 1 -0.35 -14.40 1.1783659 -0.6304206 0.8283659 -15.0304206 1
#> 3 1 -12.20 -2.55 5.2020307 2.0753902 -6.9979693 -0.4746098 2
#> 4 1 -2.30 -13.70 0.2929851 1.5897270 -2.0070149 -12.1102730 1
#> 5 1 -12.60 -7.80 -0.5086263 1.7165158 -13.1086263 -6.0834842 2
#> 6 1 -7.60 -12.40 0.2433714 1.7247688 -7.3566286 -10.6752312 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4660 -73875 15200
#> initial value 998.131940
#> iter 2 value 657.764614
#> iter 3 value 657.709562
#> iter 4 value 657.662867
#> iter 5 value 635.448873
#> iter 6 value 632.690865
#> iter 7 value 632.611726
#> iter 8 value 632.611111
#> iter 8 value 632.611107
#> final value 632.611107
#> converged
#> This is Run number 275
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.11993393 0.0739470 -2.1800661 -12.5260530 1
#> 2 1 -0.35 -14.40 0.71857050 -0.4373191 0.3685705 -14.8373191 1
#> 3 1 -12.20 -2.55 6.23539922 2.7988565 -5.9646008 0.2488565 2
#> 4 1 -2.30 -13.70 -0.33447449 5.2625241 -2.6344745 -8.4374759 1
#> 5 1 -12.60 -7.80 0.00926264 0.4349388 -12.5907374 -7.3650612 2
#> 6 1 -7.60 -12.40 0.11882900 -0.9574319 -7.4811710 -13.3574319 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4800 -71200 14775
#> initial value 998.131940
#> iter 2 value 682.547704
#> iter 3 value 682.514088
#> iter 4 value 682.506503
#> iter 5 value 663.536070
#> iter 6 value 661.595465
#> iter 7 value 661.554646
#> iter 8 value 661.554472
#> iter 8 value 661.554471
#> final value 661.554471
#> converged
#> This is Run number 276
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.1599026 1.2794038 -4.1400974 -11.320596 1
#> 2 1 -0.35 -14.40 1.1628253 -0.3183784 0.8128253 -14.718378 1
#> 3 1 -12.20 -2.55 3.7186281 0.7386172 -8.4813719 -1.811383 2
#> 4 1 -2.30 -13.70 -0.5182213 0.8308306 -2.8182213 -12.869169 1
#> 5 1 -12.60 -7.80 -0.1598604 0.2802477 -12.7598604 -7.519752 2
#> 6 1 -7.60 -12.40 -0.7336827 -1.0123048 -8.3336827 -13.412305 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4480 -73250 14850
#> initial value 998.131940
#> iter 2 value 664.235538
#> iter 3 value 664.126354
#> iter 4 value 664.061619
#> iter 5 value 642.611134
#> iter 6 value 640.043872
#> iter 7 value 639.974750
#> iter 8 value 639.974222
#> iter 8 value 639.974218
#> final value 639.974218
#> converged
#> This is Run number 277
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.5854151 0.6096903 -4.8854151 -11.9903097 1
#> 2 1 -0.35 -14.40 -0.1031683 -0.4326693 -0.4531683 -14.8326693 1
#> 3 1 -12.20 -2.55 1.3682331 2.4296566 -10.8317669 -0.1203434 2
#> 4 1 -2.30 -13.70 0.5600730 0.3876254 -1.7399270 -13.3123746 1
#> 5 1 -12.60 -7.80 -0.3843244 -1.4238849 -12.9843244 -9.2238849 2
#> 6 1 -7.60 -12.40 -0.8349271 -1.3040315 -8.4349271 -13.7040315 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3940 -73675 13550
#> initial value 998.131940
#> iter 2 value 662.854470
#> iter 3 value 662.079991
#> iter 4 value 661.498228
#> iter 5 value 638.875432
#> iter 6 value 636.043047
#> iter 7 value 635.950598
#> iter 8 value 635.949661
#> iter 8 value 635.949653
#> final value 635.949653
#> converged
#> This is Run number 278
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.2874524 0.07298737 -3.0125476 -12.527013 1
#> 2 1 -0.35 -14.40 -0.2947635 0.36574374 -0.6447635 -14.034256 1
#> 3 1 -12.20 -2.55 -1.7322384 -0.54529405 -13.9322384 -3.095294 2
#> 4 1 -2.30 -13.70 -1.0373738 -0.31151032 -3.3373738 -14.011510 1
#> 5 1 -12.60 -7.80 0.1953451 1.55102231 -12.4046549 -6.248978 2
#> 6 1 -7.60 -12.40 2.1078125 0.73187458 -5.4921875 -11.668125 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5700 -72350 12675
#> initial value 998.131940
#> iter 2 value 675.192404
#> iter 3 value 674.519822
#> iter 4 value 674.317451
#> iter 5 value 654.605555
#> iter 6 value 652.527859
#> iter 7 value 652.485371
#> iter 8 value 652.485253
#> iter 8 value 652.485253
#> final value 652.485253
#> converged
#> This is Run number 279
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.7711257 -0.7257621 -3.5288743 -13.325762 1
#> 2 1 -0.35 -14.40 -0.2361099 1.0367443 -0.5861099 -13.363256 1
#> 3 1 -12.20 -2.55 -0.2068277 -0.2183102 -12.4068277 -2.768310 2
#> 4 1 -2.30 -13.70 3.3639521 -0.1209189 1.0639521 -13.820919 1
#> 5 1 -12.60 -7.80 -0.2006175 0.8881665 -12.8006175 -6.911833 2
#> 6 1 -7.60 -12.40 0.9436148 0.7057107 -6.6563852 -11.694289 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4160 -72275 15800
#> initial value 998.131940
#> iter 2 value 671.348018
#> iter 3 value 670.972810
#> iter 4 value 670.786842
#> iter 5 value 650.028152
#> iter 6 value 647.548510
#> iter 7 value 647.480220
#> iter 8 value 647.479659
#> iter 8 value 647.479656
#> final value 647.479656
#> converged
#> This is Run number 280
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.7531815 0.06541917 -3.5468185 -12.534581 1
#> 2 1 -0.35 -14.40 -0.1040301 -0.30354638 -0.4540301 -14.703546 1
#> 3 1 -12.20 -2.55 -0.8992754 0.70701856 -13.0992754 -1.842981 2
#> 4 1 -2.30 -13.70 -0.5216838 0.31449146 -2.8216838 -13.385509 1
#> 5 1 -12.60 -7.80 -0.1410658 -0.25747473 -12.7410658 -8.057475 2
#> 6 1 -7.60 -12.40 0.7322901 0.04819527 -6.8677099 -12.351805 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4800 -72025 12900
#> initial value 998.131940
#> iter 2 value 678.379802
#> iter 3 value 678.000501
#> iter 4 value 677.919457
#> iter 5 value 658.527514
#> iter 6 value 656.473300
#> iter 7 value 656.429485
#> iter 8 value 656.429302
#> iter 8 value 656.429301
#> final value 656.429301
#> converged
#> This is Run number 281
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.7531084 -0.7387696 -5.0531084 -13.338770 1
#> 2 1 -0.35 -14.40 0.9118968 -0.1381466 0.5618968 -14.538147 1
#> 3 1 -12.20 -2.55 -0.3000412 0.5125528 -12.5000412 -2.037447 2
#> 4 1 -2.30 -13.70 1.0282911 0.9980335 -1.2717089 -12.701966 1
#> 5 1 -12.60 -7.80 1.8660079 0.1950132 -10.7339921 -7.604987 2
#> 6 1 -7.60 -12.40 1.5507427 -0.4256016 -6.0492573 -12.825602 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3640 -71900 14575
#> initial value 998.131940
#> iter 2 value 677.267983
#> iter 3 value 675.833057
#> iter 4 value 675.570565
#> iter 5 value 655.295247
#> iter 6 value 652.911559
#> iter 7 value 652.845497
#> iter 8 value 652.844832
#> iter 8 value 652.844827
#> final value 652.844827
#> converged
#> This is Run number 282
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.06495321 -0.1751453 -4.2350468 -12.775145 1
#> 2 1 -0.35 -14.40 1.13237727 1.4858216 0.7823773 -12.914178 1
#> 3 1 -12.20 -2.55 2.66002438 -1.2861553 -9.5399756 -3.836155 2
#> 4 1 -2.30 -13.70 1.06456744 0.2069944 -1.2354326 -13.493006 1
#> 5 1 -12.60 -7.80 -0.78240638 1.3020703 -13.3824064 -6.497930 2
#> 6 1 -7.60 -12.40 1.73404027 -0.7008166 -5.8659597 -13.100817 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4760 -75850 14750
#> initial value 998.131940
#> iter 2 value 640.117374
#> iter 3 value 640.115346
#> iter 4 value 640.041938
#> iter 5 value 615.249419
#> iter 6 value 611.875873
#> iter 7 value 611.759299
#> iter 8 value 611.758144
#> iter 8 value 611.758135
#> final value 611.758135
#> converged
#> This is Run number 283
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.05352599 -1.12600489 -4.353526 -13.726005 1
#> 2 1 -0.35 -14.40 -0.87363666 -1.58536451 -1.223637 -15.985365 1
#> 3 1 -12.20 -2.55 0.92403265 -0.32728271 -11.275967 -2.877283 2
#> 4 1 -2.30 -13.70 -0.74758387 -0.08369261 -3.047584 -13.783693 1
#> 5 1 -12.60 -7.80 1.89591693 -1.48781215 -10.704083 -9.287812 2
#> 6 1 -7.60 -12.40 -0.41579377 -0.48254878 -8.015794 -12.882549 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4480 -71025 14300
#> initial value 998.131940
#> iter 2 value 685.128201
#> iter 3 value 685.039580
#> iter 4 value 685.025571
#> iter 5 value 666.364817
#> iter 6 value 664.429519
#> iter 7 value 664.388809
#> iter 8 value 664.388609
#> iter 8 value 664.388607
#> final value 664.388607
#> converged
#> This is Run number 284
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.80470723 0.9424057 -3.4952928 -11.65759430 1
#> 2 1 -0.35 -14.40 -0.34502633 2.6109096 -0.6950263 -11.78909039 1
#> 3 1 -12.20 -2.55 1.55110680 2.4735387 -10.6488932 -0.07646133 2
#> 4 1 -2.30 -13.70 1.68063222 -0.9687130 -0.6193678 -14.66871296 1
#> 5 1 -12.60 -7.80 -0.03716031 0.5920450 -12.6371603 -7.20795501 2
#> 6 1 -7.60 -12.40 -0.56446010 0.6098909 -8.1644601 -11.79010911 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4480 -73250 14250
#> initial value 998.131940
#> iter 2 value 665.314325
#> iter 3 value 665.207228
#> iter 4 value 665.103952
#> iter 5 value 643.737221
#> iter 6 value 641.222263
#> iter 7 value 641.154120
#> iter 8 value 641.153631
#> iter 8 value 641.153628
#> final value 641.153628
#> converged
#> This is Run number 285
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.4339867 1.0080523 -3.8660133 -11.591948 1
#> 2 1 -0.35 -14.40 0.9550196 -0.5618812 0.6050196 -14.961881 1
#> 3 1 -12.20 -2.55 1.6875461 -0.2632363 -10.5124539 -2.813236 2
#> 4 1 -2.30 -13.70 1.7073922 -0.3459365 -0.5926078 -14.045936 1
#> 5 1 -12.60 -7.80 0.6109411 0.4237952 -11.9890589 -7.376205 2
#> 6 1 -7.60 -12.40 0.0735879 -0.6706889 -7.5264121 -13.070689 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4420 -70825 15725
#> initial value 998.131940
#> iter 2 value 684.203876
#> iter 3 value 683.871390
#> iter 4 value 683.866481
#> iter 5 value 664.791937
#> iter 6 value 662.817281
#> iter 7 value 662.772766
#> iter 8 value 662.772529
#> iter 8 value 662.772527
#> final value 662.772527
#> converged
#> This is Run number 286
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.4108506 -0.04796711 -2.8891494 -12.647967 1
#> 2 1 -0.35 -14.40 0.8448845 -0.49030561 0.4948845 -14.890306 1
#> 3 1 -12.20 -2.55 -0.8990255 -0.53810028 -13.0990255 -3.088100 2
#> 4 1 -2.30 -13.70 0.3811940 0.97678719 -1.9188060 -12.723213 1
#> 5 1 -12.60 -7.80 -1.4286323 -0.48368908 -14.0286323 -8.283689 2
#> 6 1 -7.60 -12.40 0.6867442 -0.07935774 -6.9132558 -12.479358 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4960 -72525 13125
#> initial value 998.131940
#> iter 2 value 673.454349
#> iter 3 value 673.148267
#> iter 4 value 673.124308
#> iter 5 value 653.155150
#> iter 6 value 650.998344
#> iter 7 value 650.950581
#> iter 8 value 650.950380
#> iter 8 value 650.950379
#> final value 650.950379
#> converged
#> This is Run number 287
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.8123434 -0.09564205 -5.1123434 -12.695642 1
#> 2 1 -0.35 -14.40 0.3637601 6.43872560 0.0137601 -7.961274 1
#> 3 1 -12.20 -2.55 -0.5731078 0.14453673 -12.7731078 -2.405463 2
#> 4 1 -2.30 -13.70 0.5825636 0.04525889 -1.7174364 -13.654741 1
#> 5 1 -12.60 -7.80 -0.1935624 2.40698526 -12.7935624 -5.393015 2
#> 6 1 -7.60 -12.40 -0.3552843 -0.81826349 -7.9552843 -13.218263 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4900 -70000 12900
#> initial value 998.131940
#> iter 2 value 696.124496
#> iter 3 value 695.920043
#> iter 4 value 695.919932
#> iter 5 value 678.973689
#> iter 6 value 677.134302
#> iter 7 value 677.097432
#> iter 8 value 677.097325
#> iter 8 value 677.097325
#> final value 677.097325
#> converged
#> This is Run number 288
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.6818337 3.3017248 -3.618166 -9.298275 1
#> 2 1 -0.35 -14.40 -0.8736021 2.1277578 -1.223602 -12.272242 1
#> 3 1 -12.20 -2.55 0.9594359 0.1672122 -11.240564 -2.382788 2
#> 4 1 -2.30 -13.70 -0.3948726 0.7192182 -2.694873 -12.980782 1
#> 5 1 -12.60 -7.80 -0.1395584 0.5057452 -12.739558 -7.294255 2
#> 6 1 -7.60 -12.40 1.1671638 0.4146611 -6.432836 -11.985339 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4180 -69525 13975
#> initial value 998.131940
#> iter 2 value 698.866446
#> iter 3 value 698.590236
#> iter 4 value 698.575867
#> iter 5 value 681.467699
#> iter 6 value 679.825909
#> iter 7 value 679.795202
#> iter 8 value 679.795064
#> iter 8 value 679.795063
#> final value 679.795063
#> converged
#> This is Run number 289
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.6523996 -0.8070482310 -4.952400 -13.407048 1
#> 2 1 -0.35 -14.40 1.7830951 1.1633497333 1.433095 -13.236650 1
#> 3 1 -12.20 -2.55 3.1607307 0.2438554325 -9.039269 -2.306145 2
#> 4 1 -2.30 -13.70 0.7770706 -0.9651747228 -1.522929 -14.665175 1
#> 5 1 -12.60 -7.80 2.4988776 1.2722879362 -10.101122 -6.527712 2
#> 6 1 -7.60 -12.40 -0.6902810 -0.0002681709 -8.290281 -12.400268 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4680 -72425 15375
#> initial value 998.131940
#> iter 2 value 670.583050
#> iter 3 value 670.475421
#> iter 4 value 670.473429
#> iter 5 value 649.715388
#> iter 6 value 647.570031
#> iter 7 value 647.516247
#> iter 8 value 647.515939
#> iter 8 value 647.515937
#> final value 647.515937
#> converged
#> This is Run number 290
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.01051607 -0.85868110 -4.2894839 -13.458681 1
#> 2 1 -0.35 -14.40 -0.10988724 -0.00734228 -0.4598872 -14.407342 1
#> 3 1 -12.20 -2.55 2.26392773 4.69180185 -9.9360723 2.141802 2
#> 4 1 -2.30 -13.70 -0.81615202 2.13435578 -3.1161520 -11.565644 1
#> 5 1 -12.60 -7.80 -0.30736309 0.91599566 -12.9073631 -6.884004 2
#> 6 1 -7.60 -12.40 -1.11188355 -0.97286578 -8.7118835 -13.372866 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4860 -71625 13075
#> initial value 998.131940
#> iter 2 value 681.640937
#> iter 3 value 681.383743
#> iter 4 value 681.355802
#> iter 5 value 662.400626
#> iter 6 value 660.451393
#> iter 7 value 660.411657
#> iter 8 value 660.411506
#> iter 8 value 660.411505
#> final value 660.411505
#> converged
#> This is Run number 291
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.1933689 -0.57434943 -4.106631 -13.174349 1
#> 2 1 -0.35 -14.40 2.2167765 -0.01055748 1.866777 -14.410557 1
#> 3 1 -12.20 -2.55 0.2060452 -0.65607835 -11.993955 -3.206078 2
#> 4 1 -2.30 -13.70 0.7605050 2.44407207 -1.539495 -11.255928 1
#> 5 1 -12.60 -7.80 0.1992783 -0.85678876 -12.400722 -8.656789 2
#> 6 1 -7.60 -12.40 1.1503664 -0.66965274 -6.449634 -13.069653 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5040 -72850 14150
#> initial value 998.131940
#> iter 2 value 668.794317
#> iter 3 value 668.759120
#> iter 4 value 668.756820
#> iter 5 value 648.039079
#> iter 6 value 645.915955
#> iter 7 value 645.866050
#> iter 8 value 645.865827
#> iter 8 value 645.865826
#> final value 645.865826
#> converged
#> This is Run number 292
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.6236511 -0.4909132 -4.923651 -13.090913 1
#> 2 1 -0.35 -14.40 -0.7465997 1.7108412 -1.096600 -12.689159 1
#> 3 1 -12.20 -2.55 -0.2539277 -0.3036221 -12.453928 -2.853622 2
#> 4 1 -2.30 -13.70 -0.5192938 0.4007640 -2.819294 -13.299236 1
#> 5 1 -12.60 -7.80 2.1714952 1.3358818 -10.428505 -6.464118 2
#> 6 1 -7.60 -12.40 1.2859352 0.4560767 -6.314065 -11.943923 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4620 -73750 15350
#> initial value 998.131940
#> iter 2 value 658.644771
#> iter 3 value 658.562224
#> iter 4 value 658.510867
#> iter 5 value 636.381836
#> iter 6 value 633.635808
#> iter 7 value 633.556968
#> iter 8 value 633.556348
#> iter 8 value 633.556344
#> final value 633.556344
#> converged
#> This is Run number 293
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.07347183 0.05379745 -4.226528 -12.546203 1
#> 2 1 -0.35 -14.40 1.88632045 -0.55675752 1.536320 -14.956758 1
#> 3 1 -12.20 -2.55 1.91515640 -0.35523243 -10.284844 -2.905232 2
#> 4 1 -2.30 -13.70 -0.05138902 1.67101570 -2.351389 -12.028984 1
#> 5 1 -12.60 -7.80 0.17659562 1.90858311 -12.423404 -5.891417 2
#> 6 1 -7.60 -12.40 -1.02745296 1.29195559 -8.627453 -11.108044 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5220 -72575 15300
#> initial value 998.131940
#> iter 2 value 669.046038
#> iter 3 value 668.896014
#> iter 4 value 668.764267
#> iter 5 value 648.084782
#> iter 6 value 645.740444
#> iter 7 value 645.683923
#> iter 8 value 645.683656
#> iter 8 value 645.683655
#> final value 645.683655
#> converged
#> This is Run number 294
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.1403499 -0.7278523 -4.159650 -13.327852 1
#> 2 1 -0.35 -14.40 1.7421703 -0.8877580 1.392170 -15.287758 1
#> 3 1 -12.20 -2.55 6.1624024 0.2730996 -6.037598 -2.276900 2
#> 4 1 -2.30 -13.70 0.2202458 -0.4716666 -2.079754 -14.171667 1
#> 5 1 -12.60 -7.80 0.7610779 -0.1209669 -11.838922 -7.920967 2
#> 6 1 -7.60 -12.40 0.9884097 1.0984078 -6.611590 -11.301592 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4640 -72425 14050
#> initial value 998.131940
#> iter 2 value 673.036440
#> iter 3 value 672.967330
#> iter 4 value 672.908940
#> iter 5 value 652.777237
#> iter 6 value 650.539067
#> iter 7 value 650.486862
#> iter 8 value 650.486575
#> iter 8 value 650.486573
#> final value 650.486573
#> converged
#> This is Run number 295
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.5809731 -0.3470691 -4.8809731 -12.947069 1
#> 2 1 -0.35 -14.40 0.4703875 -0.6932733 0.1203875 -15.093273 1
#> 3 1 -12.20 -2.55 0.1035624 0.2567375 -12.0964376 -2.293263 2
#> 4 1 -2.30 -13.70 2.8191424 -0.6737533 0.5191424 -14.373753 1
#> 5 1 -12.60 -7.80 5.9862286 0.4138527 -6.6137714 -7.386147 1
#> 6 1 -7.60 -12.40 1.9995250 2.8791753 -5.6004750 -9.520825 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4320 -70375 15225
#> initial value 998.131940
#> iter 2 value 689.171396
#> iter 3 value 688.971179
#> iter 4 value 688.932583
#> iter 5 value 670.587366
#> iter 6 value 668.689634
#> iter 7 value 668.649325
#> iter 8 value 668.649117
#> iter 8 value 668.649116
#> final value 668.649116
#> converged
#> This is Run number 296
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.14941998 -1.4109570 -2.1505800 -14.010957 1
#> 2 1 -0.35 -14.40 0.84274033 1.2553873 0.4927403 -13.144613 1
#> 3 1 -12.20 -2.55 0.03514083 -0.5065633 -12.1648592 -3.056563 2
#> 4 1 -2.30 -13.70 -0.53665175 -0.6429948 -2.8366518 -14.342995 1
#> 5 1 -12.60 -7.80 0.97011317 1.3382197 -11.6298868 -6.461780 2
#> 6 1 -7.60 -12.40 -0.16359687 1.9057232 -7.7635969 -10.494277 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3920 -74075 14950
#> initial value 998.131940
#> iter 2 value 656.752081
#> iter 3 value 655.538436
#> iter 4 value 655.340706
#> iter 5 value 632.471043
#> iter 6 value 629.445805
#> iter 7 value 629.344822
#> iter 8 value 629.343580
#> iter 9 value 629.343569
#> iter 9 value 629.343563
#> iter 9 value 629.343562
#> final value 629.343562
#> converged
#> This is Run number 297
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.3027967 3.31667806 -1.9972033 -9.283322 1
#> 2 1 -0.35 -14.40 1.3589812 1.03198277 1.0089812 -13.368017 1
#> 3 1 -12.20 -2.55 -0.4213476 0.50974597 -12.6213476 -2.040254 2
#> 4 1 -2.30 -13.70 2.0519173 0.42777525 -0.2480827 -13.272225 1
#> 5 1 -12.60 -7.80 -1.0774034 0.03062301 -13.6774034 -7.769377 2
#> 6 1 -7.60 -12.40 0.3297298 1.17572915 -7.2702702 -11.224271 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4060 -70025 15275
#> initial value 998.131940
#> iter 2 value 692.229907
#> iter 3 value 691.919822
#> iter 4 value 691.771069
#> iter 5 value 673.672275
#> iter 6 value 671.796176
#> iter 7 value 671.755667
#> iter 8 value 671.755434
#> iter 8 value 671.755433
#> final value 671.755433
#> converged
#> This is Run number 298
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.07944056 0.1700376 -3.220559 -12.429962 1
#> 2 1 -0.35 -14.40 2.12263257 1.8253591 1.772633 -12.574641 1
#> 3 1 -12.20 -2.55 -0.73764848 -0.5523033 -12.937648 -3.102303 2
#> 4 1 -2.30 -13.70 0.09198204 0.3061669 -2.208018 -13.393833 1
#> 5 1 -12.60 -7.80 0.87970844 1.7418949 -11.720292 -6.058105 2
#> 6 1 -7.60 -12.40 1.36695994 -0.6965812 -6.233040 -13.096581 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4880 -72500 14475
#> initial value 998.131940
#> iter 2 value 671.478304
#> iter 3 value 671.477403
#> iter 4 value 671.477157
#> iter 5 value 649.363206
#> iter 6 value 648.929363
#> iter 7 value 648.917959
#> iter 8 value 648.917928
#> iter 8 value 648.917928
#> final value 648.917928
#> converged
#> This is Run number 299
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.2962504 -1.0781846 -4.5962504 -13.678185 1
#> 2 1 -0.35 -14.40 0.2316828 0.1394582 -0.1183172 -14.260542 1
#> 3 1 -12.20 -2.55 0.7702702 0.6782994 -11.4297298 -1.871701 2
#> 4 1 -2.30 -13.70 -1.3193476 1.5223739 -3.6193476 -12.177626 1
#> 5 1 -12.60 -7.80 0.5496931 0.6788034 -12.0503069 -7.121197 2
#> 6 1 -7.60 -12.40 1.2475794 -0.9063145 -6.3524206 -13.306314 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4140 -72175 14075
#> initial value 998.131940
#> iter 2 value 675.489537
#> iter 3 value 674.877440
#> iter 4 value 674.738612
#> iter 5 value 654.648246
#> iter 6 value 652.370845
#> iter 7 value 652.313538
#> iter 8 value 652.313132
#> iter 8 value 652.313129
#> final value 652.313129
#> converged
#> This is Run number 300
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.8808303 -0.5285871 -3.4191697 -13.128587 1
#> 2 1 -0.35 -14.40 -0.3985891 -1.8113881 -0.7485891 -16.211388 1
#> 3 1 -12.20 -2.55 0.6553991 -0.9020090 -11.5446009 -3.452009 2
#> 4 1 -2.30 -13.70 -0.5189558 -0.3455928 -2.8189558 -14.045593 1
#> 5 1 -12.60 -7.80 0.1555583 -0.1231413 -12.4444417 -7.923141 2
#> 6 1 -7.60 -12.40 -0.6373460 0.5756532 -8.2373460 -11.824347 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4820 -70300 14825
#> initial value 998.131940
#> iter 2 value 690.308443
#> iter 3 value 690.227769
#> iter 4 value 690.189213
#> iter 5 value 672.171264
#> iter 6 value 670.380076
#> iter 7 value 670.345519
#> iter 8 value 670.345392
#> iter 8 value 670.345391
#> final value 670.345391
#> converged
#> This is Run number 301
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.1350804 0.8851343 -3.1649196 -11.714866 1
#> 2 1 -0.35 -14.40 0.2057545 0.9146092 -0.1442455 -13.485391 1
#> 3 1 -12.20 -2.55 0.4476733 0.7531223 -11.7523267 -1.796878 2
#> 4 1 -2.30 -13.70 1.3711976 -0.3743289 -0.9288024 -14.074329 1
#> 5 1 -12.60 -7.80 0.6039798 -0.1632154 -11.9960202 -7.963215 2
#> 6 1 -7.60 -12.40 1.2243944 -0.3061152 -6.3756056 -12.706115 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5420 -73750 15125
#> initial value 998.131940
#> iter 2 value 658.574115
#> iter 3 value 658.375113
#> iter 4 value 658.291743
#> iter 5 value 636.309800
#> iter 6 value 633.682991
#> iter 7 value 633.615344
#> iter 8 value 633.614995
#> iter 8 value 633.614993
#> final value 633.614993
#> converged
#> This is Run number 302
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.1338614 -1.50229759 -4.4338614 -14.102298 1
#> 2 1 -0.35 -14.40 0.5993725 -0.94663355 0.2493725 -15.346634 1
#> 3 1 -12.20 -2.55 2.2087921 -0.18945096 -9.9912079 -2.739451 2
#> 4 1 -2.30 -13.70 -0.6579997 0.58975987 -2.9579997 -13.110240 1
#> 5 1 -12.60 -7.80 -0.4929623 0.66136612 -13.0929623 -7.138634 2
#> 6 1 -7.60 -12.40 1.2533308 0.06969474 -6.3466692 -12.330305 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4940 -72075 13125
#> initial value 998.131940
#> iter 2 value 677.505305
#> iter 3 value 677.236273
#> iter 4 value 677.219273
#> iter 5 value 657.757783
#> iter 6 value 655.716999
#> iter 7 value 655.673757
#> iter 8 value 655.673587
#> iter 8 value 655.673587
#> final value 655.673587
#> converged
#> This is Run number 303
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.4497438 1.6854381 -1.8502562 -10.914562 1
#> 2 1 -0.35 -14.40 1.5817125 2.0113046 1.2317125 -12.388695 1
#> 3 1 -12.20 -2.55 -0.7353407 -0.8314819 -12.9353407 -3.381482 2
#> 4 1 -2.30 -13.70 2.0957003 0.7632774 -0.2042997 -12.936723 1
#> 5 1 -12.60 -7.80 -0.5206775 -1.0379903 -13.1206775 -8.837990 2
#> 6 1 -7.60 -12.40 -0.8414909 -0.4550326 -8.4414909 -12.855033 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4040 -71550 15175
#> initial value 998.131940
#> iter 2 value 679.095775
#> iter 3 value 678.808825
#> iter 4 value 678.558364
#> iter 5 value 658.754880
#> iter 6 value 656.516846
#> iter 7 value 656.459682
#> iter 8 value 656.459248
#> iter 8 value 656.459246
#> final value 656.459246
#> converged
#> This is Run number 304
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.94660983 1.1101118 -3.3533902 -11.489888 1
#> 2 1 -0.35 -14.40 1.83882387 0.6360577 1.4888239 -13.763942 1
#> 3 1 -12.20 -2.55 0.94724169 -0.1211945 -11.2527583 -2.671195 2
#> 4 1 -2.30 -13.70 2.19157220 -0.7847739 -0.1084278 -14.484774 1
#> 5 1 -12.60 -7.80 0.01988784 -1.6893389 -12.5801122 -9.489339 2
#> 6 1 -7.60 -12.40 4.42522970 1.1246218 -3.1747703 -11.275378 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4680 -72725 14850
#> initial value 998.131940
#> iter 2 value 668.884317
#> iter 3 value 668.859752
#> iter 4 value 668.838752
#> iter 5 value 648.142674
#> iter 6 value 645.772774
#> iter 7 value 645.713496
#> iter 8 value 645.713134
#> iter 8 value 645.713132
#> final value 645.713132
#> converged
#> This is Run number 305
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.1003863 3.01097083 -3.199614 -9.589029 1
#> 2 1 -0.35 -14.40 1.3704185 1.68533034 1.020418 -12.714670 1
#> 3 1 -12.20 -2.55 -0.6622231 1.14830060 -12.862223 -1.401699 2
#> 4 1 -2.30 -13.70 0.2178820 -0.90470878 -2.082118 -14.604709 1
#> 5 1 -12.60 -7.80 2.5020377 0.22112112 -10.097962 -7.578879 2
#> 6 1 -7.60 -12.40 -0.3834629 0.07793818 -7.983463 -12.322062 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4280 -72825 12925
#> initial value 998.131940
#> iter 2 value 671.422850
#> iter 3 value 670.733129
#> iter 4 value 670.159158
#> iter 5 value 649.458375
#> iter 6 value 647.090333
#> iter 7 value 647.030893
#> iter 8 value 647.030495
#> iter 8 value 647.030492
#> final value 647.030492
#> converged
#> This is Run number 306
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.4412168 0.6782692 -3.858783 -11.9217308 1
#> 2 1 -0.35 -14.40 -1.2604351 0.6195563 -1.610435 -13.7804437 1
#> 3 1 -12.20 -2.55 -1.2876512 2.8645561 -13.487651 0.3145561 2
#> 4 1 -2.30 -13.70 0.6265233 -0.3870165 -1.673477 -14.0870165 1
#> 5 1 -12.60 -7.80 -0.3818455 -1.7394617 -12.981846 -9.5394617 2
#> 6 1 -7.60 -12.40 -0.1350732 -0.4277542 -7.735073 -12.8277542 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4740 -73550 13550
#> initial value 998.131940
#> iter 2 value 663.608110
#> iter 3 value 663.344733
#> iter 4 value 663.201955
#> iter 5 value 641.880168
#> iter 6 value 639.372964
#> iter 7 value 639.308829
#> iter 8 value 639.308442
#> iter 8 value 639.308440
#> final value 639.308440
#> converged
#> This is Run number 307
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.4668175 -0.15151849 -3.8331825 -12.751518 1
#> 2 1 -0.35 -14.40 1.5504343 0.88443528 1.2004343 -13.515565 1
#> 3 1 -12.20 -2.55 1.1949489 0.95244060 -11.0050511 -1.597559 2
#> 4 1 -2.30 -13.70 1.7870753 -0.69876176 -0.5129247 -14.398762 1
#> 5 1 -12.60 -7.80 2.0401885 0.03672736 -10.5598115 -7.763273 2
#> 6 1 -7.60 -12.40 1.0883263 0.17657114 -6.5116737 -12.223429 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4980 -71950 14050
#> initial value 998.131940
#> iter 2 value 677.087420
#> iter 3 value 677.060302
#> iter 4 value 677.056316
#> iter 5 value 657.474846
#> iter 6 value 655.487248
#> iter 7 value 655.444552
#> iter 8 value 655.444381
#> iter 8 value 655.444380
#> final value 655.444380
#> converged
#> This is Run number 308
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.04963971 3.1875562 -4.2503603 -9.4124438 1
#> 2 1 -0.35 -14.40 0.56774347 -0.2652690 0.2177435 -14.6652690 1
#> 3 1 -12.20 -2.55 1.43922148 2.0428952 -10.7607785 -0.5071048 2
#> 4 1 -2.30 -13.70 -1.07452934 0.8447218 -3.3745293 -12.8552782 1
#> 5 1 -12.60 -7.80 -1.22868217 0.5425980 -13.8286822 -7.2574020 2
#> 6 1 -7.60 -12.40 -0.32765052 -0.2090900 -7.9276505 -12.6090900 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3920 -70025 14775
#> initial value 998.131940
#> iter 2 value 693.246202
#> iter 3 value 692.972978
#> iter 4 value 692.766081
#> iter 5 value 674.637404
#> iter 6 value 672.779839
#> iter 7 value 672.738981
#> iter 8 value 672.738728
#> iter 8 value 672.738727
#> final value 672.738727
#> converged
#> This is Run number 309
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.1663769 3.35006211 -2.13362310 -9.249938 1
#> 2 1 -0.35 -14.40 0.2618868 0.61020758 -0.08811324 -13.789792 1
#> 3 1 -12.20 -2.55 1.4128365 -0.04031798 -10.78716347 -2.590318 2
#> 4 1 -2.30 -13.70 0.9564685 0.42245143 -1.34353151 -13.277549 1
#> 5 1 -12.60 -7.80 1.9167457 -0.36639195 -10.68325429 -8.166392 2
#> 6 1 -7.60 -12.40 0.5919632 3.66893612 -7.00803681 -8.731064 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4980 -74475 15125
#> initial value 998.131940
#> iter 2 value 652.181726
#> iter 3 value 652.175224
#> iter 4 value 652.175067
#> iter 5 value 626.825430
#> iter 6 value 626.388268
#> iter 7 value 626.375025
#> iter 8 value 626.375014
#> iter 8 value 626.375014
#> final value 626.375014
#> converged
#> This is Run number 310
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.38011793 -0.9337125 -3.919882 -13.533713 1
#> 2 1 -0.35 -14.40 -1.16190623 -1.4664499 -1.511906 -15.866450 1
#> 3 1 -12.20 -2.55 -0.39957010 1.4369974 -12.599570 -1.113003 2
#> 4 1 -2.30 -13.70 0.60833037 -0.5543104 -1.691670 -14.254310 1
#> 5 1 -12.60 -7.80 0.64872281 0.1408607 -11.951277 -7.659139 2
#> 6 1 -7.60 -12.40 -0.06752206 -0.3504345 -7.667522 -12.750434 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4560 -73325 15050
#> initial value 998.131940
#> iter 2 value 663.135982
#> iter 3 value 663.069522
#> iter 4 value 663.013999
#> iter 5 value 641.474129
#> iter 6 value 638.876996
#> iter 7 value 638.805653
#> iter 8 value 638.805121
#> iter 8 value 638.805118
#> final value 638.805118
#> converged
#> This is Run number 311
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.5998406 2.9053289 -3.700159 -9.694671 1
#> 2 1 -0.35 -14.40 3.1703077 -0.2567254 2.820308 -14.656725 1
#> 3 1 -12.20 -2.55 1.5640328 0.8345449 -10.635967 -1.715455 2
#> 4 1 -2.30 -13.70 0.8127583 1.6157217 -1.487242 -12.084278 1
#> 5 1 -12.60 -7.80 0.8034679 1.0888397 -11.796532 -6.711160 2
#> 6 1 -7.60 -12.40 1.2577909 -0.4879629 -6.342209 -12.887963 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4540 -71575 14875
#> initial value 998.131940
#> iter 2 value 679.197454
#> iter 3 value 679.141447
#> iter 4 value 679.113699
#> iter 5 value 659.680456
#> iter 6 value 657.578005
#> iter 7 value 657.530164
#> iter 8 value 657.529904
#> iter 8 value 657.529902
#> final value 657.529902
#> converged
#> This is Run number 312
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.90159666 0.8407245 -5.2015967 -11.7592755 1
#> 2 1 -0.35 -14.40 0.22500277 0.9590881 -0.1249972 -13.4409119 1
#> 3 1 -12.20 -2.55 -0.14822984 2.2048257 -12.3482298 -0.3451743 2
#> 4 1 -2.30 -13.70 0.51595464 0.8218001 -1.7840454 -12.8781999 1
#> 5 1 -12.60 -7.80 -0.29844159 -0.2167464 -12.8984416 -8.0167464 2
#> 6 1 -7.60 -12.40 0.01659311 0.3036194 -7.5834069 -12.0963806 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5040 -74750 15875
#> initial value 998.131940
#> iter 2 value 648.116721
#> iter 3 value 647.991063
#> iter 4 value 647.971193
#> iter 5 value 624.444626
#> iter 6 value 621.395456
#> iter 7 value 621.302130
#> iter 8 value 621.301418
#> iter 8 value 621.301414
#> final value 621.301414
#> converged
#> This is Run number 313
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.1228128 0.1391897 -4.4228128 -12.460810 1
#> 2 1 -0.35 -14.40 -0.6327025 -0.3394561 -0.9827025 -14.739456 1
#> 3 1 -12.20 -2.55 1.2167948 -0.2609518 -10.9832052 -2.810952 2
#> 4 1 -2.30 -13.70 3.7814690 0.6980828 1.4814690 -13.001917 1
#> 5 1 -12.60 -7.80 0.5519300 0.5497890 -12.0480700 -7.250211 2
#> 6 1 -7.60 -12.40 2.1766479 1.1514521 -5.4233521 -11.248548 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4700 -71350 13975
#> initial value 998.131940
#> iter 2 value 682.708790
#> iter 3 value 682.682179
#> iter 4 value 682.662913
#> iter 5 value 663.790954
#> iter 6 value 661.842152
#> iter 7 value 661.801677
#> iter 8 value 661.801500
#> iter 8 value 661.801499
#> final value 661.801499
#> converged
#> This is Run number 314
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.8426874 0.38520361 -3.457313 -12.214796 1
#> 2 1 -0.35 -14.40 -0.8872488 -1.13058458 -1.237249 -15.530585 1
#> 3 1 -12.20 -2.55 0.7595239 -0.03854525 -11.440476 -2.588545 2
#> 4 1 -2.30 -13.70 -0.1188986 0.24780196 -2.418899 -13.452198 1
#> 5 1 -12.60 -7.80 0.4157190 -0.86481197 -12.184281 -8.664812 2
#> 6 1 -7.60 -12.40 -0.3570845 2.24274659 -7.957084 -10.157253 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4920 -70775 14975
#> initial value 998.131940
#> iter 2 value 685.827922
#> iter 3 value 685.721895
#> iter 4 value 685.653701
#> iter 5 value 667.096608
#> iter 6 value 665.194755
#> iter 7 value 665.156298
#> iter 8 value 665.156150
#> iter 8 value 665.156149
#> final value 665.156149
#> converged
#> This is Run number 315
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.41253117 0.92680102 -4.7125312 -11.673199 1
#> 2 1 -0.35 -14.40 -0.03811146 -0.67764064 -0.3881115 -15.077641 1
#> 3 1 -12.20 -2.55 0.73632323 1.18404950 -11.4636768 -1.365951 2
#> 4 1 -2.30 -13.70 -0.64625463 -0.06706682 -2.9462546 -13.767067 1
#> 5 1 -12.60 -7.80 0.95470133 -0.36441307 -11.6452987 -8.164413 2
#> 6 1 -7.60 -12.40 0.18082261 -0.31739472 -7.4191774 -12.717395 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4600 -71175 14925
#> initial value 998.131940
#> iter 2 value 682.602539
#> iter 3 value 682.540548
#> iter 4 value 682.535883
#> iter 5 value 663.470278
#> iter 6 value 661.530163
#> iter 7 value 661.487989
#> iter 8 value 661.487786
#> iter 8 value 661.487785
#> final value 661.487785
#> converged
#> This is Run number 316
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.3244524 2.1212508 -4.6244524 -10.4787492 1
#> 2 1 -0.35 -14.40 -0.4552061 -0.4956122 -0.8052061 -14.8956122 1
#> 3 1 -12.20 -2.55 3.2363652 1.8689467 -8.9636348 -0.6810533 2
#> 4 1 -2.30 -13.70 -0.1828327 -0.7251422 -2.4828327 -14.4251422 1
#> 5 1 -12.60 -7.80 -0.2921240 1.0954942 -12.8921240 -6.7045058 2
#> 6 1 -7.60 -12.40 1.1745988 2.7747275 -6.4254012 -9.6252725 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4700 -72600 16000
#> initial value 998.131940
#> iter 2 value 667.740608
#> iter 3 value 667.440215
#> iter 4 value 667.436741
#> iter 5 value 646.276998
#> iter 6 value 643.916245
#> iter 7 value 643.854263
#> iter 8 value 643.853877
#> iter 8 value 643.853874
#> final value 643.853874
#> converged
#> This is Run number 317
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.07130033 0.81284919 -5.3713003 -11.787151 1
#> 2 1 -0.35 -14.40 -0.17019827 0.64155442 -0.5201983 -13.758446 1
#> 3 1 -12.20 -2.55 0.81786766 -0.02119786 -11.3821323 -2.571198 2
#> 4 1 -2.30 -13.70 -0.01534614 0.80086515 -2.3153461 -12.899135 1
#> 5 1 -12.60 -7.80 -0.65452978 -1.19642720 -13.2545298 -8.996427 2
#> 6 1 -7.60 -12.40 0.06326008 -0.50176614 -7.5367399 -12.901766 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4580 -72900 14675
#> initial value 998.131940
#> iter 2 value 667.680383
#> iter 3 value 667.577284
#> iter 4 value 667.554111
#> iter 5 value 646.685202
#> iter 6 value 644.257458
#> iter 7 value 644.195564
#> iter 8 value 644.195154
#> iter 8 value 644.195151
#> final value 644.195151
#> converged
#> This is Run number 318
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.6118105 0.1089000 -3.688190 -12.4911000 1
#> 2 1 -0.35 -14.40 2.6216055 -0.6472245 2.271606 -15.0472245 1
#> 3 1 -12.20 -2.55 -0.3736721 2.3031958 -12.573672 -0.2468042 2
#> 4 1 -2.30 -13.70 -0.3652096 0.5336930 -2.665210 -13.1663070 1
#> 5 1 -12.60 -7.80 -0.1478153 0.6710779 -12.747815 -7.1289221 2
#> 6 1 -7.60 -12.40 0.7598683 0.1596058 -6.840132 -12.2403942 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5220 -71250 14750
#> initial value 998.131940
#> iter 2 value 681.885821
#> iter 3 value 681.811897
#> iter 4 value 681.714823
#> iter 5 value 662.577375
#> iter 6 value 660.610386
#> iter 7 value 660.570484
#> iter 8 value 660.570337
#> iter 8 value 660.570336
#> final value 660.570336
#> converged
#> This is Run number 319
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.6723726 -0.6254094 -1.62762736 -13.225409 1
#> 2 1 -0.35 -14.40 2.7175534 1.3904762 2.36755344 -13.009524 1
#> 3 1 -12.20 -2.55 0.4926792 -0.2299937 -11.70732078 -2.779994 2
#> 4 1 -2.30 -13.70 2.3194684 3.3121421 0.01946839 -10.387858 1
#> 5 1 -12.60 -7.80 0.7054824 0.5873730 -11.89451763 -7.212627 2
#> 6 1 -7.60 -12.40 1.0244050 -0.5067717 -6.57559501 -12.906772 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4880 -71950 12225
#> initial value 998.131940
#> iter 2 value 679.976367
#> iter 3 value 679.228486
#> iter 4 value 679.132400
#> iter 5 value 659.890529
#> iter 6 value 657.879564
#> iter 7 value 657.837790
#> iter 8 value 657.837637
#> iter 8 value 657.837636
#> final value 657.837636
#> converged
#> This is Run number 320
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.4016198 -0.3313963 -3.8983802 -12.9313963 1
#> 2 1 -0.35 -14.40 2.0978846 2.0152973 1.7478846 -12.3847027 1
#> 3 1 -12.20 -2.55 -0.1893411 1.9675308 -12.3893411 -0.5824692 2
#> 4 1 -2.30 -13.70 1.3315258 0.0951708 -0.9684742 -13.6048292 1
#> 5 1 -12.60 -7.80 -0.0163396 1.1656016 -12.6163396 -6.6343984 2
#> 6 1 -7.60 -12.40 1.0181091 0.4439618 -6.5818909 -11.9560382 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5020 -74250 14600
#> initial value 998.131940
#> iter 2 value 655.210341
#> iter 3 value 655.198564
#> iter 4 value 655.197352
#> iter 5 value 632.393336
#> iter 6 value 630.081241
#> iter 7 value 630.016907
#> iter 8 value 630.016538
#> iter 8 value 630.016535
#> final value 630.016535
#> converged
#> This is Run number 321
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.51904602 0.21034292 -2.7809540 -12.389657 1
#> 2 1 -0.35 -14.40 0.92225006 1.67886475 0.5722501 -12.721135 1
#> 3 1 -12.20 -2.55 1.75572187 0.13731141 -10.4442781 -2.412689 2
#> 4 1 -2.30 -13.70 -0.27492510 0.04788866 -2.5749251 -13.652111 1
#> 5 1 -12.60 -7.80 -0.72011982 1.58515732 -13.3201198 -6.214843 2
#> 6 1 -7.60 -12.40 -0.02319608 -0.21171456 -7.6231961 -12.611715 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5100 -69675 15275
#> initial value 998.131940
#> iter 2 value 694.661172
#> iter 3 value 694.305270
#> iter 4 value 694.011580
#> iter 5 value 676.354006
#> iter 6 value 674.637903
#> iter 7 value 674.605803
#> iter 8 value 674.605702
#> iter 8 value 674.605701
#> final value 674.605701
#> converged
#> This is Run number 322
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.5588916 -0.3735195 -2.741108 -12.9735195 1
#> 2 1 -0.35 -14.40 1.8189173 1.1749640 1.468917 -13.2250360 1
#> 3 1 -12.20 -2.55 0.8639515 2.7555332 -11.336049 0.2055332 2
#> 4 1 -2.30 -13.70 0.4954239 -0.4968644 -1.804576 -14.1968644 1
#> 5 1 -12.60 -7.80 1.2176348 1.0057321 -11.382365 -6.7942679 2
#> 6 1 -7.60 -12.40 0.5977822 -1.7177034 -7.002218 -14.1177034 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5460 -73200 14500
#> initial value 998.131940
#> iter 2 value 664.720399
#> iter 3 value 664.572430
#> iter 4 value 664.487716
#> iter 5 value 643.350031
#> iter 6 value 640.946823
#> iter 7 value 640.888753
#> iter 8 value 640.888506
#> iter 8 value 640.888505
#> final value 640.888505
#> converged
#> This is Run number 323
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.2594828 -0.30645308 -3.040517 -12.906453 1
#> 2 1 -0.35 -14.40 -1.3768672 -0.23723717 -1.726867 -14.637237 1
#> 3 1 -12.20 -2.55 -1.3394729 0.43067312 -13.539473 -2.119327 2
#> 4 1 -2.30 -13.70 -0.1935774 -0.33493277 -2.493577 -14.034933 1
#> 5 1 -12.60 -7.80 0.8125653 0.59772826 -11.787435 -7.202272 2
#> 6 1 -7.60 -12.40 -0.4671219 -0.09493849 -8.067122 -12.494938 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4400 -74075 15750
#> initial value 998.131940
#> iter 2 value 654.982839
#> iter 3 value 654.758236
#> iter 4 value 654.605223
#> iter 5 value 631.793966
#> iter 6 value 628.827712
#> iter 7 value 628.734044
#> iter 8 value 628.733134
#> iter 8 value 628.733128
#> final value 628.733128
#> converged
#> This is Run number 324
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.9040928 2.5333885 -3.3959072 -10.066611 1
#> 2 1 -0.35 -14.40 0.3846246 0.4646980 0.0346246 -13.935302 1
#> 3 1 -12.20 -2.55 -0.7092510 -0.4246585 -12.9092510 -2.974659 2
#> 4 1 -2.30 -13.70 -0.8729904 0.6848088 -3.1729904 -13.015191 1
#> 5 1 -12.60 -7.80 0.3744677 0.8915139 -12.2255323 -6.908486 2
#> 6 1 -7.60 -12.40 2.3142711 1.6077428 -5.2857289 -10.792257 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4320 -70075 13650
#> initial value 998.131940
#> iter 2 value 694.608502
#> iter 3 value 694.502578
#> iter 4 value 694.421599
#> iter 5 value 676.798038
#> iter 6 value 675.075051
#> iter 7 value 675.041518
#> iter 8 value 675.041368
#> iter 8 value 675.041367
#> final value 675.041367
#> converged
#> This is Run number 325
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.5256880 -1.14459458 -3.774312 -13.744595 1
#> 2 1 -0.35 -14.40 -0.9340195 -0.11155651 -1.284020 -14.511557 1
#> 3 1 -12.20 -2.55 1.5178768 -1.42785667 -10.682123 -3.977857 2
#> 4 1 -2.30 -13.70 0.5607742 -0.50972041 -1.739226 -14.209720 1
#> 5 1 -12.60 -7.80 -0.6451427 0.02164272 -13.245143 -7.778357 2
#> 6 1 -7.60 -12.40 0.1470160 1.66940577 -7.452984 -10.730594 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5620 -73225 14325
#> initial value 998.131940
#> iter 2 value 664.686336
#> iter 3 value 664.677526
#> iter 4 value 664.532501
#> iter 5 value 643.111408
#> iter 6 value 640.725543
#> iter 7 value 640.667039
#> iter 8 value 640.666807
#> iter 8 value 640.666806
#> final value 640.666806
#> converged
#> This is Run number 326
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.5137435 0.9507859 -3.7862565 -11.649214 1
#> 2 1 -0.35 -14.40 1.1094044 -0.8412651 0.7594044 -15.241265 1
#> 3 1 -12.20 -2.55 -1.1016596 6.9977880 -13.3016596 4.447788 2
#> 4 1 -2.30 -13.70 1.5460371 3.1535317 -0.7539629 -10.546468 1
#> 5 1 -12.60 -7.80 -0.6389586 0.5793379 -13.2389586 -7.220662 2
#> 6 1 -7.60 -12.40 -1.3034172 -0.5132094 -8.9034172 -12.913209 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4300 -74700 15250
#> initial value 998.131940
#> iter 2 value 650.226300
#> iter 3 value 649.982125
#> iter 4 value 649.804094
#> iter 5 value 626.099674
#> iter 6 value 622.966017
#> iter 7 value 622.862531
#> iter 8 value 622.861353
#> iter 9 value 622.861341
#> iter 9 value 622.861335
#> iter 9 value 622.861335
#> final value 622.861335
#> converged
#> This is Run number 327
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.2851791 -1.1182837 -4.0148209 -13.718284 1
#> 2 1 -0.35 -14.40 0.8116274 0.2571265 0.4616274 -14.142874 1
#> 3 1 -12.20 -2.55 0.1216117 -0.3191709 -12.0783883 -2.869171 2
#> 4 1 -2.30 -13.70 0.3706010 1.9846147 -1.9293990 -11.715385 1
#> 5 1 -12.60 -7.80 0.9168975 -0.4783456 -11.6831025 -8.278346 2
#> 6 1 -7.60 -12.40 -0.4739907 1.3312239 -8.0739907 -11.068776 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5400 -74875 14800
#> initial value 998.131940
#> iter 2 value 648.790460
#> iter 3 value 648.740853
#> iter 4 value 648.703358
#> iter 5 value 625.484226
#> iter 6 value 622.553624
#> iter 7 value 622.471336
#> iter 8 value 622.470861
#> iter 8 value 622.470859
#> final value 622.470859
#> converged
#> This is Run number 328
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.096423099 1.0643478 -4.20357690 -11.535652 1
#> 2 1 -0.35 -14.40 0.375293257 1.1196818 0.02529326 -13.280318 1
#> 3 1 -12.20 -2.55 -0.449288392 0.6991940 -12.64928839 -1.850806 2
#> 4 1 -2.30 -13.70 0.342709746 0.9301228 -1.95729025 -12.769877 1
#> 5 1 -12.60 -7.80 -0.002414973 -0.4835830 -12.60241497 -8.283583 2
#> 6 1 -7.60 -12.40 0.444552375 -0.3585091 -7.15544762 -12.758509 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5000 -74000 15475
#> initial value 998.131940
#> iter 2 value 655.881594
#> iter 3 value 655.817370
#> iter 4 value 655.804738
#> iter 5 value 633.384578
#> iter 6 value 630.641438
#> iter 7 value 630.564629
#> iter 8 value 630.564121
#> iter 8 value 630.564118
#> final value 630.564118
#> converged
#> This is Run number 329
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.7448232 -0.1893235 -3.5551768 -12.789323 1
#> 2 1 -0.35 -14.40 -0.4443479 1.0357393 -0.7943479 -13.364261 1
#> 3 1 -12.20 -2.55 -1.7985708 -0.5936948 -13.9985708 -3.143695 2
#> 4 1 -2.30 -13.70 2.7834026 0.8694455 0.4834026 -12.830555 1
#> 5 1 -12.60 -7.80 0.4790256 0.8119747 -12.1209744 -6.988025 2
#> 6 1 -7.60 -12.40 1.2977558 0.1907668 -6.3022442 -12.209233 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5200 -72525 15825
#> initial value 998.131940
#> iter 2 value 668.463588
#> iter 3 value 668.141578
#> iter 4 value 667.912195
#> iter 5 value 647.064516
#> iter 6 value 644.657196
#> iter 7 value 644.597774
#> iter 8 value 644.597478
#> iter 8 value 644.597476
#> final value 644.597476
#> converged
#> This is Run number 330
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.0599199 2.0401659 -4.2400801 -10.559834 1
#> 2 1 -0.35 -14.40 1.1230374 -0.6186332 0.7730374 -15.018633 1
#> 3 1 -12.20 -2.55 0.5982664 0.8866273 -11.6017336 -1.663373 2
#> 4 1 -2.30 -13.70 -0.4971279 -0.5936615 -2.7971279 -14.293662 1
#> 5 1 -12.60 -7.80 0.4035949 1.5397717 -12.1964051 -6.260228 2
#> 6 1 -7.60 -12.40 0.9491159 1.8661785 -6.6508841 -10.533821 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4880 -71925 12625
#> initial value 998.131940
#> iter 2 value 679.632267
#> iter 3 value 679.133892
#> iter 4 value 679.073056
#> iter 5 value 659.839272
#> iter 6 value 657.829144
#> iter 7 value 657.787326
#> iter 8 value 657.787168
#> iter 8 value 657.787167
#> final value 657.787167
#> converged
#> This is Run number 331
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.2850318 -1.3132428 -3.0149682 -13.913243 1
#> 2 1 -0.35 -14.40 -0.1027884 1.9406683 -0.4527884 -12.459332 1
#> 3 1 -12.20 -2.55 1.0919716 0.8883473 -11.1080284 -1.661653 2
#> 4 1 -2.30 -13.70 2.5056193 -0.1642488 0.2056193 -13.864249 1
#> 5 1 -12.60 -7.80 1.1652267 -0.5866040 -11.4347733 -8.386604 2
#> 6 1 -7.60 -12.40 -0.4573736 1.0721847 -8.0573736 -11.327815 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5260 -73175 13800
#> initial value 998.131940
#> iter 2 value 666.295862
#> iter 3 value 666.158027
#> iter 4 value 666.132653
#> iter 5 value 645.313845
#> iter 6 value 642.977584
#> iter 7 value 642.923115
#> iter 8 value 642.922885
#> iter 8 value 642.922884
#> final value 642.922884
#> converged
#> This is Run number 332
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.0905728 0.4149702 -3.209427 -12.185030 1
#> 2 1 -0.35 -14.40 -1.6583327 2.1820174 -2.008333 -12.217983 1
#> 3 1 -12.20 -2.55 1.8403202 -0.3340766 -10.359680 -2.884077 2
#> 4 1 -2.30 -13.70 0.8659099 -0.3352845 -1.434090 -14.035284 1
#> 5 1 -12.60 -7.80 2.0989467 1.4494957 -10.501053 -6.350504 2
#> 6 1 -7.60 -12.40 -0.3746841 -0.4586155 -7.974684 -12.858616 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4140 -71500 13725
#> initial value 998.131940
#> iter 2 value 682.092110
#> iter 3 value 681.862744
#> iter 4 value 681.645505
#> iter 5 value 662.109056
#> iter 6 value 660.035526
#> iter 7 value 659.985888
#> iter 8 value 659.985575
#> iter 8 value 659.985573
#> final value 659.985573
#> converged
#> This is Run number 333
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.2163437 1.48873139 -2.0836563 -11.111269 1
#> 2 1 -0.35 -14.40 -0.5283474 1.63709706 -0.8783474 -12.762903 1
#> 3 1 -12.20 -2.55 -0.3797701 -0.49838834 -12.5797701 -3.048388 2
#> 4 1 -2.30 -13.70 -0.3228851 0.89785781 -2.6228851 -12.802142 1
#> 5 1 -12.60 -7.80 0.1382897 -0.71485816 -12.4617103 -8.514858 2
#> 6 1 -7.60 -12.40 -0.6608087 -0.04100183 -8.2608087 -12.441002 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5080 -71125 14200
#> initial value 998.131940
#> iter 2 value 684.070356
#> iter 3 value 684.017702
#> iter 4 value 683.991398
#> iter 5 value 665.327466
#> iter 6 value 663.433549
#> iter 7 value 663.395859
#> iter 8 value 663.395729
#> iter 8 value 663.395728
#> final value 663.395728
#> converged
#> This is Run number 334
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.64818449 -0.34673706 -4.9481845 -12.946737 1
#> 2 1 -0.35 -14.40 0.58187448 -0.11151352 0.2318745 -14.511514 1
#> 3 1 -12.20 -2.55 3.63424912 -0.58258245 -8.5657509 -3.132582 2
#> 4 1 -2.30 -13.70 0.83321727 -1.07430703 -1.4667827 -14.774307 1
#> 5 1 -12.60 -7.80 0.09483488 -0.06065014 -12.5051651 -7.860650 2
#> 6 1 -7.60 -12.40 3.46393636 -1.07857706 -4.1360636 -13.478577 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5500 -72725 14325
#> initial value 998.131940
#> iter 2 value 669.304731
#> iter 3 value 669.211481
#> iter 4 value 669.098134
#> iter 5 value 648.439872
#> iter 6 value 646.177855
#> iter 7 value 646.125407
#> iter 8 value 646.125206
#> iter 8 value 646.125206
#> final value 646.125206
#> converged
#> This is Run number 335
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.7843318 2.5637391 -5.084332 -10.036261 1
#> 2 1 -0.35 -14.40 2.7036816 -0.0143892 2.353682 -14.414389 1
#> 3 1 -12.20 -2.55 0.2670758 -0.4469128 -11.932924 -2.996913 2
#> 4 1 -2.30 -13.70 0.7947618 -0.8580038 -1.505238 -14.558004 1
#> 5 1 -12.60 -7.80 -0.9193085 2.7781901 -13.519309 -5.021810 2
#> 6 1 -7.60 -12.40 -1.3593560 0.2217623 -8.959356 -12.178238 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4680 -71850 12750
#> initial value 998.131940
#> iter 2 value 680.234727
#> iter 3 value 679.772839
#> iter 4 value 679.615706
#> iter 5 value 660.401387
#> iter 6 value 658.375924
#> iter 7 value 658.332968
#> iter 8 value 658.332783
#> iter 8 value 658.332782
#> final value 658.332782
#> converged
#> This is Run number 336
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.6094651 0.3021078 -3.690535 -12.29789 1
#> 2 1 -0.35 -14.40 0.1220400 1.6678420 -0.227960 -12.73216 1
#> 3 1 -12.20 -2.55 1.2594737 -0.1192398 -10.940526 -2.66924 2
#> 4 1 -2.30 -13.70 -0.4633695 3.1252976 -2.763369 -10.57470 1
#> 5 1 -12.60 -7.80 0.1254471 -0.4393096 -12.474553 -8.23931 2
#> 6 1 -7.60 -12.40 1.2359955 0.4075144 -6.364004 -11.99249 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5320 -72875 14550
#> initial value 998.131940
#> iter 2 value 667.676241
#> iter 3 value 667.523728
#> iter 4 value 667.484698
#> iter 5 value 646.794608
#> iter 6 value 644.465882
#> iter 7 value 644.411395
#> iter 8 value 644.411162
#> iter 8 value 644.411161
#> final value 644.411161
#> converged
#> This is Run number 337
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.1095133 0.4206482 -4.190487 -12.179352 1
#> 2 1 -0.35 -14.40 1.4503275 1.0840300 1.100327 -13.315970 1
#> 3 1 -12.20 -2.55 -0.1468290 -0.2538806 -12.346829 -2.803881 2
#> 4 1 -2.30 -13.70 -0.8023243 1.1499920 -3.102324 -12.550008 1
#> 5 1 -12.60 -7.80 1.5111733 1.4915507 -11.088827 -6.308449 2
#> 6 1 -7.60 -12.40 0.1196036 0.4722460 -7.480396 -11.927754 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5000 -72300 15450
#> initial value 998.131940
#> iter 2 value 671.364590
#> iter 3 value 671.213108
#> iter 4 value 671.140677
#> iter 5 value 650.749843
#> iter 6 value 648.446296
#> iter 7 value 648.391454
#> iter 8 value 648.391181
#> iter 8 value 648.391179
#> final value 648.391179
#> converged
#> This is Run number 338
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.5789224 0.4937766 -4.8789224 -12.106223 1
#> 2 1 -0.35 -14.40 -1.2233164 3.9919768 -1.5733164 -10.408023 1
#> 3 1 -12.20 -2.55 0.7591689 0.3901026 -11.4408311 -2.159897 2
#> 4 1 -2.30 -13.70 1.8011081 1.9281555 -0.4988919 -11.771844 1
#> 5 1 -12.60 -7.80 2.4213451 -0.9617723 -10.1786549 -8.761772 2
#> 6 1 -7.60 -12.40 0.2185939 -0.3773866 -7.3814061 -12.777387 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 3980 -72700 16250
#> initial value 998.131940
#> iter 2 value 666.676964
#> iter 3 value 666.049341
#> iter 4 value 665.729589
#> iter 5 value 644.134832
#> iter 6 value 641.412082
#> iter 7 value 641.328537
#> iter 8 value 641.327702
#> iter 8 value 641.327698
#> final value 641.327698
#> converged
#> This is Run number 339
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.4909826 -0.06667264 -4.7909826 -12.666673 1
#> 2 1 -0.35 -14.40 1.3429358 -0.35452567 0.9929358 -14.754526 1
#> 3 1 -12.20 -2.55 0.1958913 0.63025169 -12.0041087 -1.919748 2
#> 4 1 -2.30 -13.70 -0.4551774 1.94161897 -2.7551774 -11.758381 1
#> 5 1 -12.60 -7.80 1.8293919 3.10237889 -10.7706081 -4.697621 2
#> 6 1 -7.60 -12.40 0.8113387 0.80132999 -6.7886613 -11.598670 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5020 -72400 13725
#> initial value 998.131940
#> iter 2 value 673.582361
#> iter 3 value 673.484496
#> iter 4 value 673.484349
#> iter 5 value 669.298129
#> iter 6 value 651.924578
#> iter 7 value 651.386263
#> iter 8 value 651.364630
#> iter 8 value 651.364627
#> final value 651.364627
#> converged
#> This is Run number 340
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 3.19389843 1.0122650 -1.1061016 -11.587735 1
#> 2 1 -0.35 -14.40 0.93756621 -1.0631056 0.5875662 -15.463106 1
#> 3 1 -12.20 -2.55 2.35240918 -0.7007454 -9.8475908 -3.250745 2
#> 4 1 -2.30 -13.70 1.20286252 0.3994354 -1.0971375 -13.300565 1
#> 5 1 -12.60 -7.80 0.99575171 0.1371500 -11.6042483 -7.662850 2
#> 6 1 -7.60 -12.40 0.07356457 1.7702402 -7.5264354 -10.629760 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5180 -72750 13375
#> initial value 998.131940
#> iter 2 value 670.892518
#> iter 3 value 670.660909
#> iter 4 value 670.657175
#> iter 5 value 650.322142
#> iter 6 value 648.211047
#> iter 7 value 648.163948
#> iter 8 value 648.163769
#> iter 8 value 648.163768
#> final value 648.163768
#> converged
#> This is Run number 341
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.1671084 2.2299441 -4.132892 -10.3700559 1
#> 2 1 -0.35 -14.40 3.1489284 5.1141109 2.798928 -9.2858891 1
#> 3 1 -12.20 -2.55 -0.4685277 2.4420192 -12.668528 -0.1079808 2
#> 4 1 -2.30 -13.70 -1.7830299 -0.2160543 -4.083030 -13.9160543 1
#> 5 1 -12.60 -7.80 1.2159377 2.1914284 -11.384062 -5.6085716 2
#> 6 1 -7.60 -12.40 3.0821752 2.1361747 -4.517825 -10.2638253 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5240 -71600 14325
#> initial value 998.131940
#> iter 2 value 679.549299
#> iter 3 value 679.377339
#> iter 4 value 679.341113
#> iter 5 value 660.144719
#> iter 6 value 658.139651
#> iter 7 value 658.098328
#> iter 8 value 658.098184
#> iter 8 value 658.098184
#> final value 658.098184
#> converged
#> This is Run number 342
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.8256820 -1.3718982 -5.1256820 -13.971898 1
#> 2 1 -0.35 -14.40 0.8541209 1.3717721 0.5041209 -13.028228 1
#> 3 1 -12.20 -2.55 1.1546833 -0.1763758 -11.0453167 -2.726376 2
#> 4 1 -2.30 -13.70 3.0505932 -1.2643140 0.7505932 -14.964314 1
#> 5 1 -12.60 -7.80 -0.4067087 -1.1759458 -13.0067087 -8.975946 2
#> 6 1 -7.60 -12.40 -1.2343166 -0.3686313 -8.8343166 -12.768631 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4760 -74225 15925
#> initial value 998.131940
#> iter 2 value 653.050032
#> iter 3 value 652.877996
#> iter 4 value 652.874635
#> iter 5 value 629.782907
#> iter 6 value 626.991409
#> iter 7 value 626.906443
#> iter 8 value 626.905769
#> iter 8 value 626.905764
#> final value 626.905764
#> converged
#> This is Run number 343
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.3027092 -0.18447901 -2.997291 -12.784479 1
#> 2 1 -0.35 -14.40 1.9555279 -1.09733042 1.605528 -15.497330 1
#> 3 1 -12.20 -2.55 2.9848850 -0.06202388 -9.215115 -2.612024 2
#> 4 1 -2.30 -13.70 0.5241754 0.80559432 -1.775825 -12.894406 1
#> 5 1 -12.60 -7.80 0.7781284 1.64336869 -11.821872 -6.156631 2
#> 6 1 -7.60 -12.40 1.3584420 -1.05672034 -6.241558 -13.456720 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5100 -71950 15025
#> initial value 998.131940
#> iter 2 value 675.248827
#> iter 3 value 675.157296
#> iter 4 value 675.077646
#> iter 5 value 655.232007
#> iter 6 value 653.069979
#> iter 7 value 653.021337
#> iter 8 value 653.021126
#> iter 8 value 653.021125
#> final value 653.021125
#> converged
#> This is Run number 344
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.77499802 0.1946544 -5.074998 -12.405346 1
#> 2 1 -0.35 -14.40 1.21444501 0.2777549 0.864445 -14.122245 1
#> 3 1 -12.20 -2.55 1.33505890 0.7782135 -10.864941 -1.771787 2
#> 4 1 -2.30 -13.70 -0.91163287 -0.3589550 -3.211633 -14.058955 1
#> 5 1 -12.60 -7.80 -0.03330502 -0.5415594 -12.633305 -8.341559 2
#> 6 1 -7.60 -12.40 1.23811226 0.8625359 -6.361888 -11.537464 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4100 -71550 13875
#> initial value 998.131940
#> iter 2 value 681.416341
#> iter 3 value 680.895878
#> iter 4 value 680.712080
#> iter 5 value 661.301512
#> iter 6 value 659.195372
#> iter 7 value 659.145372
#> iter 8 value 659.145049
#> iter 8 value 659.145047
#> final value 659.145047
#> converged
#> This is Run number 345
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.2392715 2.4728178 -2.060729 -10.1271822 1
#> 2 1 -0.35 -14.40 1.7787138 0.8326608 1.428714 -13.5673392 1
#> 3 1 -12.20 -2.55 1.2083266 1.5577171 -10.991673 -0.9922829 2
#> 4 1 -2.30 -13.70 -0.3749565 1.0657966 -2.674957 -12.6342034 1
#> 5 1 -12.60 -7.80 -0.5306768 0.5411447 -13.130677 -7.2588553 2
#> 6 1 -7.60 -12.40 -0.7309169 2.3591141 -8.330917 -10.0408859 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4880 -70025 15150
#> initial value 998.131940
#> iter 2 value 692.033128
#> iter 3 value 691.834344
#> iter 4 value 691.727919
#> iter 5 value 673.853903
#> iter 6 value 672.082234
#> iter 7 value 672.048374
#> iter 8 value 672.048254
#> iter 8 value 672.048254
#> final value 672.048254
#> converged
#> This is Run number 346
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.36846618 1.2983255 -5.6684662 -11.301675 1
#> 2 1 -0.35 -14.40 0.01257023 1.3514941 -0.3374298 -13.048506 1
#> 3 1 -12.20 -2.55 -0.41376057 0.2546103 -12.6137606 -2.295390 2
#> 4 1 -2.30 -13.70 -1.06068861 0.1581442 -3.3606886 -13.541856 1
#> 5 1 -12.60 -7.80 0.13982525 0.2794331 -12.4601747 -7.520567 2
#> 6 1 -7.60 -12.40 1.16578525 1.7867672 -6.4342148 -10.613233 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4360 -70300 13225
#> initial value 998.131940
#> iter 2 value 693.324270
#> iter 3 value 693.116272
#> iter 4 value 692.942731
#> iter 5 value 675.215929
#> iter 6 value 673.481186
#> iter 7 value 673.448328
#> iter 8 value 673.448189
#> iter 8 value 673.448189
#> final value 673.448189
#> converged
#> This is Run number 347
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.01088177 1.42409559 -4.310882 -11.175904 1
#> 2 1 -0.35 -14.40 -1.49051920 0.10439753 -1.840519 -14.295602 1
#> 3 1 -12.20 -2.55 4.99277011 5.45852762 -7.207230 2.908528 2
#> 4 1 -2.30 -13.70 0.34040070 0.37636083 -1.959599 -13.323639 1
#> 5 1 -12.60 -7.80 0.86727466 1.37097212 -11.732725 -6.429028 2
#> 6 1 -7.60 -12.40 1.61362252 0.04685644 -5.986377 -12.353144 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4680 -72575 16075
#> initial value 998.131940
#> iter 2 value 667.821076
#> iter 3 value 667.486242
#> iter 4 value 667.483189
#> iter 5 value 646.289656
#> iter 6 value 643.940742
#> iter 7 value 643.878720
#> iter 8 value 643.878331
#> iter 8 value 643.878328
#> final value 643.878328
#> converged
#> This is Run number 348
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.6002200 -0.2833144 -4.900220 -12.883314 1
#> 2 1 -0.35 -14.40 1.4414921 0.5730300 1.091492 -13.826970 1
#> 3 1 -12.20 -2.55 -0.9862215 -0.2793236 -13.186221 -2.829324 2
#> 4 1 -2.30 -13.70 0.1504591 0.6520765 -2.149541 -13.047924 1
#> 5 1 -12.60 -7.80 0.3608665 0.4078976 -12.239133 -7.392102 2
#> 6 1 -7.60 -12.40 1.4355563 -0.8148450 -6.164444 -13.214845 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4400 -71325 14025
#> initial value 998.131940
#> iter 2 value 683.007030
#> iter 3 value 682.864737
#> iter 4 value 682.800587
#> iter 5 value 663.813650
#> iter 6 value 661.811766
#> iter 7 value 661.767800
#> iter 8 value 661.767569
#> iter 8 value 661.767567
#> final value 661.767567
#> converged
#> This is Run number 349
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.2931477 -0.2752378 -2.006852 -12.875238 1
#> 2 1 -0.35 -14.40 -1.4789647 -0.1345636 -1.828965 -14.534564 1
#> 3 1 -12.20 -2.55 -0.8251059 1.1573939 -13.025106 -1.392606 2
#> 4 1 -2.30 -13.70 -1.5911617 0.8237216 -3.891162 -12.876278 1
#> 5 1 -12.60 -7.80 -1.3256999 -0.6853975 -13.925700 -8.485398 2
#> 6 1 -7.60 -12.40 2.2360763 3.8227097 -5.363924 -8.577290 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4780 -70425 12625
#> initial value 998.131940
#> iter 2 value 692.919152
#> iter 3 value 692.569657
#> iter 4 value 692.531504
#> iter 5 value 674.914774
#> iter 6 value 673.231181
#> iter 7 value 673.200919
#> iter 8 value 673.200826
#> iter 8 value 673.200825
#> final value 673.200825
#> converged
#> This is Run number 350
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.1073399 2.93588850 -3.1926601 -9.664112 1
#> 2 1 -0.35 -14.40 1.0990814 -0.58670613 0.7490814 -14.986706 1
#> 3 1 -12.20 -2.55 0.8991235 0.53482788 -11.3008765 -2.015172 2
#> 4 1 -2.30 -13.70 1.0909989 -0.03798768 -1.2090011 -13.737988 1
#> 5 1 -12.60 -7.80 2.1163665 -1.34230765 -10.4836335 -9.142308 2
#> 6 1 -7.60 -12.40 1.9196169 0.51795487 -5.6803831 -11.882045 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4980 -71700 14650
#> initial value 998.131940
#> iter 2 value 678.247567
#> iter 3 value 678.224450
#> iter 4 value 678.211701
#> iter 5 value 658.780652
#> iter 6 value 656.717171
#> iter 7 value 656.672342
#> iter 8 value 656.672152
#> iter 8 value 656.672151
#> final value 656.672151
#> converged
#> This is Run number 351
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.8248076 6.5883507 -3.475192 -6.011649 1
#> 2 1 -0.35 -14.40 4.5655969 0.9252487 4.215597 -13.474751 1
#> 3 1 -12.20 -2.55 0.2066380 -0.8165295 -11.993362 -3.366530 2
#> 4 1 -2.30 -13.70 -1.4200856 0.5478349 -3.720086 -13.152165 1
#> 5 1 -12.60 -7.80 2.3849773 0.9724468 -10.215023 -6.827553 2
#> 6 1 -7.60 -12.40 0.1696931 0.7142394 -7.430307 -11.685761 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4480 -74675 15750
#> initial value 998.131940
#> iter 2 value 649.388150
#> iter 3 value 649.200799
#> iter 4 value 649.060900
#> iter 5 value 625.514331
#> iter 6 value 622.363402
#> iter 7 value 622.259160
#> iter 8 value 622.258087
#> iter 8 value 622.258079
#> final value 622.258079
#> converged
#> This is Run number 352
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.34967835 0.6066405 -1.950322 -11.993360 1
#> 2 1 -0.35 -14.40 2.02968792 0.5219640 1.679688 -13.878036 1
#> 3 1 -12.20 -2.55 -0.44638991 0.9714796 -12.646390 -1.578520 2
#> 4 1 -2.30 -13.70 0.13935858 0.5160533 -2.160641 -13.183947 1
#> 5 1 -12.60 -7.80 -0.97224734 2.2054580 -13.572247 -5.594542 2
#> 6 1 -7.60 -12.40 -0.08778266 1.2568611 -7.687783 -11.143139 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5020 -69425 14675
#> initial value 998.131940
#> iter 2 value 697.999050
#> iter 3 value 697.848947
#> iter 4 value 697.733735
#> iter 5 value 680.552561
#> iter 6 value 678.943665
#> iter 7 value 678.915146
#> iter 8 value 678.915064
#> iter 8 value 678.915063
#> final value 678.915063
#> converged
#> This is Run number 353
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.77990787 1.4034466 -5.0799079 -11.196553 1
#> 2 1 -0.35 -14.40 -0.03464405 -0.3349866 -0.3846441 -14.734987 1
#> 3 1 -12.20 -2.55 0.95509409 1.0916792 -11.2449059 -1.458321 2
#> 4 1 -2.30 -13.70 1.06071419 0.6677371 -1.2392858 -13.032263 1
#> 5 1 -12.60 -7.80 0.07313668 0.6929441 -12.5268633 -7.107056 2
#> 6 1 -7.60 -12.40 -0.21661466 0.4998908 -7.8166147 -11.900109 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5140 -70425 13725
#> initial value 998.131940
#> iter 2 value 690.967585
#> iter 3 value 690.885951
#> iter 4 value 690.816990
#> iter 5 value 673.011226
#> iter 6 value 671.293789
#> iter 7 value 671.263053
#> iter 8 value 671.262968
#> iter 8 value 671.262968
#> final value 671.262968
#> converged
#> This is Run number 354
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.83239029 2.4327924 -3.4676097 -10.167208 1
#> 2 1 -0.35 -14.40 -0.08989048 0.3655506 -0.4398905 -14.034449 1
#> 3 1 -12.20 -2.55 1.10496791 0.1031058 -11.0950321 -2.446894 2
#> 4 1 -2.30 -13.70 -0.08537642 1.6373796 -2.3853764 -12.062620 1
#> 5 1 -12.60 -7.80 1.86936806 1.8168476 -10.7306319 -5.983152 2
#> 6 1 -7.60 -12.40 1.45870756 -0.5832702 -6.1412924 -12.983270 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4800 -72025 13625
#> initial value 998.131940
#> iter 2 value 677.240541
#> iter 3 value 677.129684
#> iter 4 value 677.099849
#> iter 5 value 657.588599
#> iter 6 value 655.509178
#> iter 7 value 655.463988
#> iter 8 value 655.463786
#> iter 8 value 655.463785
#> final value 655.463785
#> converged
#> This is Run number 355
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.5084151 2.1770545 -3.7915849 -10.422946 1
#> 2 1 -0.35 -14.40 0.5325364 0.5758755 0.1825364 -13.824125 1
#> 3 1 -12.20 -2.55 -1.0563473 -1.8014126 -13.2563473 -4.351413 2
#> 4 1 -2.30 -13.70 -0.6442297 1.8447957 -2.9442297 -11.855204 1
#> 5 1 -12.60 -7.80 -1.1176403 -0.1706724 -13.7176403 -7.970672 2
#> 6 1 -7.60 -12.40 -0.6765971 0.7933571 -8.2765971 -11.606643 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4940 -73775 14450
#> initial value 998.131940
#> iter 2 value 659.903089
#> iter 3 value 659.883830
#> iter 4 value 659.876714
#> iter 5 value 638.074248
#> iter 6 value 635.534459
#> iter 7 value 635.467631
#> iter 8 value 635.467233
#> iter 8 value 635.467230
#> final value 635.467230
#> converged
#> This is Run number 356
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.8612065 -0.5357593 -5.1612065 -13.135759 1
#> 2 1 -0.35 -14.40 0.7260521 0.7443275 0.3760521 -13.655673 1
#> 3 1 -12.20 -2.55 2.6059749 -1.6108792 -9.5940251 -4.160879 2
#> 4 1 -2.30 -13.70 -0.4546274 0.6470014 -2.7546274 -13.052999 1
#> 5 1 -12.60 -7.80 1.9501343 -0.7676856 -10.6498657 -8.567686 2
#> 6 1 -7.60 -12.40 1.8251768 0.2054678 -5.7748232 -12.194532 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4400 -74475 16400
#> initial value 998.131940
#> iter 2 value 649.940840
#> iter 3 value 649.524804
#> iter 4 value 649.411632
#> iter 5 value 625.770920
#> iter 6 value 622.564725
#> iter 7 value 622.455778
#> iter 8 value 622.454603
#> iter 8 value 622.454595
#> final value 622.454595
#> converged
#> This is Run number 357
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.6822620 0.2806171 -1.6177380 -12.319383 1
#> 2 1 -0.35 -14.40 1.1855287 3.5706674 0.8355287 -10.829333 1
#> 3 1 -12.20 -2.55 0.7629191 2.1751270 -11.4370809 -0.374873 2
#> 4 1 -2.30 -13.70 -0.5247966 -0.9953561 -2.8247966 -14.695356 1
#> 5 1 -12.60 -7.80 1.3376574 1.2473625 -11.2623426 -6.552637 2
#> 6 1 -7.60 -12.40 -0.6295391 1.2010973 -8.2295391 -11.198903 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4100 -68725 14200
#> initial value 998.131940
#> iter 2 value 705.325548
#> iter 3 value 705.217258
#> iter 4 value 705.180436
#> iter 5 value 688.653235
#> iter 6 value 687.134055
#> iter 7 value 687.106795
#> iter 8 value 687.106679
#> iter 8 value 687.106679
#> final value 687.106679
#> converged
#> This is Run number 358
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.0028109 -0.5926509 -5.302811 -13.1926509 1
#> 2 1 -0.35 -14.40 -0.9193052 0.3573068 -1.269305 -14.0426932 1
#> 3 1 -12.20 -2.55 3.5699979 2.8083456 -8.630002 0.2583456 2
#> 4 1 -2.30 -13.70 0.9404328 -0.3054375 -1.359567 -14.0054375 1
#> 5 1 -12.60 -7.80 3.5950166 0.5135107 -9.004983 -7.2864893 2
#> 6 1 -7.60 -12.40 5.5445013 -0.6663771 -2.055499 -13.0663771 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4320 -74475 15775
#> initial value 998.131940
#> iter 2 value 651.275273
#> iter 3 value 651.010354
#> iter 4 value 650.781893
#> iter 5 value 627.370207
#> iter 6 value 624.235453
#> iter 7 value 624.130167
#> iter 8 value 624.129017
#> iter 8 value 624.129009
#> final value 624.129009
#> converged
#> This is Run number 359
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.01909169 0.7301709 -4.3190917 -11.869829 1
#> 2 1 -0.35 -14.40 0.55449919 -1.1368269 0.2044992 -15.536827 1
#> 3 1 -12.20 -2.55 0.69519392 -0.2438830 -11.5048061 -2.793883 2
#> 4 1 -2.30 -13.70 -0.23507157 -0.5601263 -2.5350716 -14.260126 1
#> 5 1 -12.60 -7.80 0.71849880 -0.6199339 -11.8815012 -8.419934 2
#> 6 1 -7.60 -12.40 1.03371240 -0.4925327 -6.5662876 -12.892533 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4560 -72225 15175
#> initial value 998.131940
#> iter 2 value 672.830084
#> iter 3 value 672.741770
#> iter 4 value 672.714543
#> iter 5 value 652.443315
#> iter 6 value 650.150104
#> iter 7 value 650.093706
#> iter 8 value 650.093359
#> iter 8 value 650.093357
#> final value 650.093357
#> converged
#> This is Run number 360
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.5602377 -0.39477931 -3.7397623 -12.994779 1
#> 2 1 -0.35 -14.40 -0.1257078 1.91772528 -0.4757078 -12.482275 1
#> 3 1 -12.20 -2.55 -0.8962944 -0.10508832 -13.0962944 -2.655088 2
#> 4 1 -2.30 -13.70 -0.6523312 -0.05745084 -2.9523312 -13.757451 1
#> 5 1 -12.60 -7.80 1.8012496 1.18286493 -10.7987504 -6.617135 2
#> 6 1 -7.60 -12.40 0.1383296 -0.90226206 -7.4616704 -13.302262 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4200 -72950 15575
#> initial value 998.131940
#> iter 2 value 665.704694
#> iter 3 value 665.419772
#> iter 4 value 665.191965
#> iter 5 value 643.729818
#> iter 6 value 641.090473
#> iter 7 value 641.013802
#> iter 8 value 641.013117
#> iter 8 value 641.013113
#> final value 641.013113
#> converged
#> This is Run number 361
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.5954827 -1.5602131 -3.7045173 -14.160213 1
#> 2 1 -0.35 -14.40 1.1160491 1.4892950 0.7660491 -12.910705 1
#> 3 1 -12.20 -2.55 -0.1437470 -0.4267943 -12.3437470 -2.976794 2
#> 4 1 -2.30 -13.70 0.9940293 0.7436643 -1.3059707 -12.956336 1
#> 5 1 -12.60 -7.80 2.3554640 0.3271568 -10.2445360 -7.472843 2
#> 6 1 -7.60 -12.40 -0.2158819 0.2666108 -7.8158819 -12.133389 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4380 -73450 14425
#> initial value 998.131940
#> iter 2 value 663.233981
#> iter 3 value 662.827922
#> iter 4 value 662.752803
#> iter 5 value 641.190977
#> iter 6 value 638.574835
#> iter 7 value 638.502080
#> iter 8 value 638.501509
#> iter 8 value 638.501505
#> final value 638.501505
#> converged
#> This is Run number 362
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.2996126 0.8438570 -4.5996126 -11.756143 1
#> 2 1 -0.35 -14.40 1.0555928 2.6733843 0.7055928 -11.726616 1
#> 3 1 -12.20 -2.55 -1.0173093 0.2128436 -13.2173093 -2.337156 2
#> 4 1 -2.30 -13.70 -0.2562210 -0.8082332 -2.5562210 -14.508233 1
#> 5 1 -12.60 -7.80 0.7708876 1.0074236 -11.8291124 -6.792576 2
#> 6 1 -7.60 -12.40 -0.6954565 4.0344098 -8.2954565 -8.365590 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4880 -72375 14925
#> initial value 998.131940
#> iter 2 value 671.776373
#> iter 3 value 671.752043
#> iter 4 value 671.746946
#> iter 5 value 651.407128
#> iter 6 value 649.212482
#> iter 7 value 649.160707
#> iter 8 value 649.160447
#> iter 8 value 649.160445
#> final value 649.160445
#> converged
#> This is Run number 363
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 9.70053434 1.4265574 5.4005343 -11.173443 1
#> 2 1 -0.35 -14.40 -0.48234160 1.2975517 -0.8323416 -13.102448 1
#> 3 1 -12.20 -2.55 0.38633674 1.8400930 -11.8136633 -0.709907 2
#> 4 1 -2.30 -13.70 0.90282609 0.5866696 -1.3971739 -13.113330 1
#> 5 1 -12.60 -7.80 0.05953014 3.3003409 -12.5404699 -4.499659 2
#> 6 1 -7.60 -12.40 6.41939479 1.3031550 -1.1806052 -11.096845 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4980 -71725 14200
#> initial value 998.131940
#> iter 2 value 678.830183
#> iter 3 value 678.816635
#> iter 4 value 678.806087
#> iter 5 value 659.492904
#> iter 6 value 657.483333
#> iter 7 value 657.440976
#> iter 8 value 657.440807
#> iter 8 value 657.440806
#> final value 657.440806
#> converged
#> This is Run number 364
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.11072849 -0.55822929 -4.410728 -13.1582293 1
#> 2 1 -0.35 -14.40 -0.11263900 2.59579198 -0.462639 -11.8042080 1
#> 3 1 -12.20 -2.55 -0.09789082 2.29948038 -12.297891 -0.2505196 2
#> 4 1 -2.30 -13.70 -0.78760317 0.05172517 -3.087603 -13.6482748 1
#> 5 1 -12.60 -7.80 0.23564141 0.06785036 -12.364359 -7.7321496 2
#> 6 1 -7.60 -12.40 1.46944085 -0.04543822 -6.130559 -12.4454382 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4740 -71575 15025
#> initial value 998.131940
#> iter 2 value 678.802229
#> iter 3 value 678.741043
#> iter 4 value 678.739620
#> iter 5 value 659.032495
#> iter 6 value 657.199518
#> iter 7 value 657.158318
#> iter 8 value 657.158132
#> iter 8 value 657.158131
#> final value 657.158131
#> converged
#> This is Run number 365
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.4461019 -1.0913300 -3.8538981 -13.691330 1
#> 2 1 -0.35 -14.40 1.2427839 -0.7453512 0.8927839 -15.145351 1
#> 3 1 -12.20 -2.55 3.0002903 0.1635470 -9.1997097 -2.386453 2
#> 4 1 -2.30 -13.70 2.1267570 -0.5799179 -0.1732430 -14.279918 1
#> 5 1 -12.60 -7.80 -0.8674098 -0.3456677 -13.4674098 -8.145668 2
#> 6 1 -7.60 -12.40 -0.3858713 -0.5307512 -7.9858713 -12.930751 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5100 -70750 12325
#> initial value 998.131940
#> iter 2 value 690.312947
#> iter 3 value 689.777532
#> iter 4 value 689.777314
#> iter 5 value 670.412826
#> iter 6 value 670.139534
#> iter 7 value 670.134281
#> iter 7 value 670.134277
#> iter 7 value 670.134277
#> final value 670.134277
#> converged
#> This is Run number 366
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.5867217 2.4176488 -1.713278 -10.182351 1
#> 2 1 -0.35 -14.40 -1.9812189 1.1092329 -2.331219 -13.290767 1
#> 3 1 -12.20 -2.55 2.9737970 -1.2989155 -9.226203 -3.848916 2
#> 4 1 -2.30 -13.70 0.7682641 0.9916133 -1.531736 -12.708387 1
#> 5 1 -12.60 -7.80 0.7768984 1.6986888 -11.823102 -6.101311 2
#> 6 1 -7.60 -12.40 0.5981960 2.7699768 -7.001804 -9.630023 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4840 -72025 13425
#> initial value 998.131940
#> iter 2 value 677.540752
#> iter 3 value 677.376479
#> iter 4 value 677.348146
#> iter 5 value 657.883799
#> iter 6 value 655.820918
#> iter 7 value 655.776575
#> iter 8 value 655.776385
#> iter 8 value 655.776384
#> final value 655.776384
#> converged
#> This is Run number 367
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.01823247 -0.4385113 -3.281768 -13.038511 1
#> 2 1 -0.35 -14.40 0.03714097 0.1261384 -0.312859 -14.273862 1
#> 3 1 -12.20 -2.55 1.85147025 1.2580388 -10.348530 -1.291961 2
#> 4 1 -2.30 -13.70 -1.52496971 0.9660994 -3.824970 -12.733901 1
#> 5 1 -12.60 -7.80 -0.13925086 1.4327830 -12.739251 -6.367217 2
#> 6 1 -7.60 -12.40 -0.37874987 -0.7814898 -7.978750 -13.181490 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5140 -74700 14100
#> initial value 998.131940
#> iter 2 value 651.835288
#> iter 3 value 651.722985
#> iter 4 value 651.720727
#> iter 5 value 628.714080
#> iter 6 value 626.120677
#> iter 7 value 626.048146
#> iter 8 value 626.047727
#> iter 8 value 626.047724
#> final value 626.047724
#> converged
#> This is Run number 368
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.5710010 0.7656730 -3.728999 -11.834327 1
#> 2 1 -0.35 -14.40 2.3499028 1.7959884 1.999903 -12.604012 1
#> 3 1 -12.20 -2.55 4.7596482 -0.2358091 -7.440352 -2.785809 2
#> 4 1 -2.30 -13.70 0.1827088 1.4466272 -2.117291 -12.253373 1
#> 5 1 -12.60 -7.80 -0.1175767 1.1492114 -12.717577 -6.650789 2
#> 6 1 -7.60 -12.40 2.1462275 -1.1656708 -5.453772 -13.565671 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5060 -71275 13275
#> initial value 998.131940
#> iter 2 value 684.302548
#> iter 3 value 684.132186
#> iter 4 value 684.126375
#> iter 5 value 665.500972
#> iter 6 value 663.684465
#> iter 7 value 663.649295
#> iter 8 value 663.649184
#> iter 8 value 663.649184
#> final value 663.649184
#> converged
#> This is Run number 369
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.61795489 1.8714176 -4.917955 -10.728582 1
#> 2 1 -0.35 -14.40 0.24970804 6.2815883 -0.100292 -8.118412 1
#> 3 1 -12.20 -2.55 0.53327434 -0.3209109 -11.666726 -2.870911 2
#> 4 1 -2.30 -13.70 0.04546163 1.5856848 -2.254538 -12.114315 1
#> 5 1 -12.60 -7.80 0.28471803 -0.2648906 -12.315282 -8.064891 2
#> 6 1 -7.60 -12.40 0.25722126 0.4821085 -7.342779 -11.917891 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4940 -72700 15325
#> initial value 998.131940
#> iter 2 value 668.052703
#> iter 3 value 667.966432
#> iter 4 value 667.941384
#> iter 5 value 647.142072
#> iter 6 value 644.758169
#> iter 7 value 644.699380
#> iter 8 value 644.699062
#> iter 8 value 644.699060
#> final value 644.699060
#> converged
#> This is Run number 370
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.13172794 2.714959358 -5.431728 -9.885041 1
#> 2 1 -0.35 -14.40 4.01140840 -0.509136669 3.661408 -14.909137 1
#> 3 1 -12.20 -2.55 0.07862682 -0.850850736 -12.121373 -3.400851 2
#> 4 1 -2.30 -13.70 -0.20712172 -0.002409514 -2.507122 -13.702410 1
#> 5 1 -12.60 -7.80 -0.01491786 1.263776564 -12.614918 -6.536223 2
#> 6 1 -7.60 -12.40 0.01551909 -0.120829395 -7.584481 -12.520829 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4760 -74250 15475
#> initial value 998.131940
#> iter 2 value 653.720464
#> iter 3 value 653.653224
#> iter 4 value 653.635878
#> iter 5 value 630.860156
#> iter 6 value 627.989395
#> iter 7 value 627.904184
#> iter 8 value 627.903509
#> iter 8 value 627.903504
#> final value 627.903504
#> converged
#> This is Run number 371
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.2260577 1.37826747 -3.0739423 -11.221733 1
#> 2 1 -0.35 -14.40 -0.2150971 3.89167377 -0.5650971 -10.508326 1
#> 3 1 -12.20 -2.55 0.6330389 0.09499692 -11.5669611 -2.455003 2
#> 4 1 -2.30 -13.70 0.9414097 -1.53093403 -1.3585903 -15.230934 1
#> 5 1 -12.60 -7.80 1.9853434 1.81411664 -10.6146566 -5.985883 2
#> 6 1 -7.60 -12.40 1.5860837 1.19611943 -6.0139163 -11.203881 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4940 -71250 15100
#> initial value 998.131940
#> iter 2 value 681.409061
#> iter 3 value 681.296890
#> iter 4 value 681.231261
#> iter 5 value 662.129123
#> iter 6 value 660.112348
#> iter 7 value 660.069485
#> iter 8 value 660.069307
#> iter 8 value 660.069306
#> final value 660.069306
#> converged
#> This is Run number 372
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.57486658 -0.9329996 -3.725133 -13.533000 1
#> 2 1 -0.35 -14.40 1.77788626 -1.0802525 1.427886 -15.480252 1
#> 3 1 -12.20 -2.55 -0.22633568 -0.5481014 -12.426336 -3.098101 2
#> 4 1 -2.30 -13.70 -0.74572439 -0.2533488 -3.045724 -13.953349 1
#> 5 1 -12.60 -7.80 0.03455774 2.3524350 -12.565442 -5.447565 2
#> 6 1 -7.60 -12.40 -0.84299646 1.9179953 -8.442996 -10.482005 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4600 -73975 13425
#> initial value 998.131940
#> iter 2 value 659.982506
#> iter 3 value 659.568527
#> iter 4 value 659.267500
#> iter 5 value 637.340129
#> iter 6 value 634.677755
#> iter 7 value 634.605331
#> iter 8 value 634.604827
#> iter 8 value 634.604823
#> final value 634.604823
#> converged
#> This is Run number 373
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.2054051 -0.9210944 -4.094595 -13.521094 1
#> 2 1 -0.35 -14.40 -1.7023421 0.6837717 -2.052342 -13.716228 1
#> 3 1 -12.20 -2.55 3.5977272 -0.7035526 -8.602273 -3.253553 2
#> 4 1 -2.30 -13.70 -0.1949605 1.3218418 -2.494961 -12.378158 1
#> 5 1 -12.60 -7.80 1.8319626 2.2583648 -10.768037 -5.541635 2
#> 6 1 -7.60 -12.40 3.6917699 3.4113489 -3.908230 -8.988651 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5000 -72850 14575
#> initial value 998.131940
#> iter 2 value 668.068283
#> iter 3 value 668.065887
#> iter 4 value 668.063056
#> iter 5 value 647.319393
#> iter 6 value 645.045239
#> iter 7 value 644.990534
#> iter 8 value 644.990264
#> iter 8 value 644.990263
#> final value 644.990263
#> converged
#> This is Run number 374
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.54990897 -0.2290490 -2.7500910 -12.829049 1
#> 2 1 -0.35 -14.40 -0.01723026 0.6165511 -0.3672303 -13.783449 1
#> 3 1 -12.20 -2.55 1.16584605 -0.2260482 -11.0341539 -2.776048 2
#> 4 1 -2.30 -13.70 -0.76099610 0.1764719 -3.0609961 -13.523528 1
#> 5 1 -12.60 -7.80 1.23064339 0.9201171 -11.3693566 -6.879883 2
#> 6 1 -7.60 -12.40 0.34123858 -0.9483364 -7.2587614 -13.348336 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4920 -71825 15150
#> initial value 998.131940
#> iter 2 value 676.237080
#> iter 3 value 676.148584
#> iter 4 value 676.110720
#> iter 5 value 656.367920
#> iter 6 value 654.216108
#> iter 7 value 654.167658
#> iter 8 value 654.167433
#> iter 8 value 654.167432
#> final value 654.167432
#> converged
#> This is Run number 375
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.8780682 1.5339997 -2.421932 -11.066000 1
#> 2 1 -0.35 -14.40 3.3912128 1.7364163 3.041213 -12.663584 1
#> 3 1 -12.20 -2.55 0.7829151 -0.3088097 -11.417085 -2.858810 2
#> 4 1 -2.30 -13.70 0.5557549 0.8816281 -1.744245 -12.818372 1
#> 5 1 -12.60 -7.80 -0.3074128 -0.1384035 -12.907413 -7.938403 2
#> 6 1 -7.60 -12.40 0.4755934 -1.4237831 -7.124407 -13.823783 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5840 -72525 15000
#> initial value 998.131940
#> iter 2 value 669.613859
#> iter 3 value 668.410393
#> iter 4 value 668.267309
#> iter 5 value 647.651984
#> iter 6 value 645.342454
#> iter 7 value 645.289521
#> iter 8 value 645.289311
#> iter 8 value 645.289310
#> final value 645.289310
#> converged
#> This is Run number 376
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.399841515 -0.5932114 -2.900158 -13.193211 1
#> 2 1 -0.35 -14.40 -0.735494865 0.2128780 -1.085495 -14.187122 1
#> 3 1 -12.20 -2.55 -0.002815999 -0.8533295 -12.202816 -3.403330 2
#> 4 1 -2.30 -13.70 -0.106645403 -0.3690832 -2.406645 -14.069083 1
#> 5 1 -12.60 -7.80 -1.001747964 0.3079549 -13.601748 -7.492045 2
#> 6 1 -7.60 -12.40 0.248914561 0.2859660 -7.351085 -12.114034 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4980 -74300 14975
#> initial value 998.131940
#> iter 2 value 654.084752
#> iter 3 value 654.083385
#> iter 4 value 654.083062
#> iter 5 value 629.661366
#> iter 6 value 628.668183
#> iter 7 value 628.637712
#> iter 8 value 628.637584
#> iter 8 value 628.637582
#> final value 628.637582
#> converged
#> This is Run number 377
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.1640866 0.1100695 -4.464087 -12.489930 1
#> 2 1 -0.35 -14.40 -0.6580748 -0.8089155 -1.008075 -15.208915 1
#> 3 1 -12.20 -2.55 0.5508934 0.8326071 -11.649107 -1.717393 2
#> 4 1 -2.30 -13.70 -0.7518318 -0.5420917 -3.051832 -14.242092 1
#> 5 1 -12.60 -7.80 -0.7584968 -1.2275647 -13.358497 -9.027565 2
#> 6 1 -7.60 -12.40 -0.7049537 0.4756426 -8.304954 -11.924357 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5180 -72575 14825
#> initial value 998.131940
#> iter 2 value 669.974899
#> iter 3 value 669.912356
#> iter 4 value 669.871031
#> iter 5 value 649.391015
#> iter 6 value 647.105034
#> iter 7 value 647.052292
#> iter 8 value 647.052053
#> iter 8 value 647.052051
#> final value 647.052051
#> converged
#> This is Run number 378
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.1514094 1.6852598 -3.1485906 -10.914740 1
#> 2 1 -0.35 -14.40 2.3606291 -0.1299934 2.0106291 -14.529993 1
#> 3 1 -12.20 -2.55 1.8657544 -0.9325485 -10.3342456 -3.482549 2
#> 4 1 -2.30 -13.70 1.9480119 -0.1032353 -0.3519881 -13.803235 1
#> 5 1 -12.60 -7.80 -0.7660642 1.5638573 -13.3660642 -6.236143 2
#> 6 1 -7.60 -12.40 3.0893788 -0.5746761 -4.5106212 -12.974676 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4840 -72625 14750
#> initial value 998.131940
#> iter 2 value 669.877909
#> iter 3 value 669.872952
#> iter 4 value 669.872572
#> iter 5 value 648.150566
#> iter 6 value 647.032919
#> iter 7 value 647.004499
#> iter 8 value 647.004392
#> iter 8 value 647.004391
#> final value 647.004391
#> converged
#> This is Run number 379
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.2811313 -0.82300655 -4.5811313 -13.423007 1
#> 2 1 -0.35 -14.40 1.2110859 0.97708144 0.8610859 -13.422919 1
#> 3 1 -12.20 -2.55 3.3571007 0.09311554 -8.8428993 -2.456884 2
#> 4 1 -2.30 -13.70 -1.0490999 0.29133757 -3.3490999 -13.408662 1
#> 5 1 -12.60 -7.80 0.1938440 0.42867681 -12.4061560 -7.371323 2
#> 6 1 -7.60 -12.40 -0.5103977 1.12378656 -8.1103977 -11.276213 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4060 -75050 15350
#> initial value 998.131940
#> iter 2 value 646.876562
#> iter 3 value 646.246371
#> iter 4 value 645.930359
#> iter 5 value 621.478030
#> iter 6 value 618.113183
#> iter 7 value 617.990792
#> iter 8 value 617.989060
#> iter 9 value 617.989041
#> iter 10 value 617.989031
#> iter 11 value 617.989017
#> iter 11 value 617.989017
#> iter 11 value 617.989017
#> final value 617.989017
#> converged
#> This is Run number 380
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.3743034 2.69583092 -3.9256966 -9.904169 1
#> 2 1 -0.35 -14.40 -0.3375278 1.96416161 -0.6875278 -12.435838 1
#> 3 1 -12.20 -2.55 2.4924447 -2.22804386 -9.7075553 -4.778044 2
#> 4 1 -2.30 -13.70 -0.4729267 0.02510135 -2.7729267 -13.674899 1
#> 5 1 -12.60 -7.80 -1.0378233 0.17902151 -13.6378233 -7.620978 2
#> 6 1 -7.60 -12.40 -0.8039199 -1.17292323 -8.4039199 -13.572923 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4800 -71600 14850
#> initial value 998.131940
#> iter 2 value 678.874940
#> iter 3 value 678.842439
#> iter 4 value 678.838688
#> iter 5 value 659.355389
#> iter 6 value 657.369552
#> iter 7 value 657.325858
#> iter 8 value 657.325660
#> iter 8 value 657.325658
#> final value 657.325658
#> converged
#> This is Run number 381
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.24662514 1.35721748 -4.5466251 -11.242783 1
#> 2 1 -0.35 -14.40 0.02814471 0.03612207 -0.3218553 -14.363878 1
#> 3 1 -12.20 -2.55 -0.70961523 0.85716627 -12.9096152 -1.692834 2
#> 4 1 -2.30 -13.70 0.17965208 4.29849299 -2.1203479 -9.401507 1
#> 5 1 -12.60 -7.80 1.08511119 1.16498162 -11.5148888 -6.635018 2
#> 6 1 -7.60 -12.40 -0.91109084 -0.57951769 -8.5110908 -12.979518 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4440 -70925 14600
#> initial value 998.131940
#> iter 2 value 685.487792
#> iter 3 value 685.436154
#> iter 4 value 685.391665
#> iter 5 value 666.723751
#> iter 6 value 664.777461
#> iter 7 value 664.735816
#> iter 8 value 664.735604
#> iter 8 value 664.735603
#> final value 664.735603
#> converged
#> This is Run number 382
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.93349212 -0.6956709 -3.3665079 -13.295671 1
#> 2 1 -0.35 -14.40 1.75888215 -1.2123057 1.4088822 -15.612306 1
#> 3 1 -12.20 -2.55 3.60494473 0.7264511 -8.5950553 -1.823549 2
#> 4 1 -2.30 -13.70 1.54312786 -0.1604962 -0.7568721 -13.860496 1
#> 5 1 -12.60 -7.80 -0.15845437 1.2146482 -12.7584544 -6.585352 2
#> 6 1 -7.60 -12.40 0.07115255 -0.6040118 -7.5288474 -13.004012 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4500 -72800 14650
#> initial value 998.131940
#> iter 2 value 668.673157
#> iter 3 value 668.508230
#> iter 4 value 668.479243
#> iter 5 value 647.708488
#> iter 6 value 645.293526
#> iter 7 value 645.231794
#> iter 8 value 645.231372
#> iter 8 value 645.231369
#> final value 645.231369
#> converged
#> This is Run number 383
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.2028241 2.0974165 -4.5028241 -10.502583 1
#> 2 1 -0.35 -14.40 0.5346075 0.4393457 0.1846075 -13.960654 1
#> 3 1 -12.20 -2.55 -0.4212169 -0.5548950 -12.6212169 -3.104895 2
#> 4 1 -2.30 -13.70 2.1645489 1.2590335 -0.1354511 -12.440966 1
#> 5 1 -12.60 -7.80 0.7724697 -0.6244329 -11.8275303 -8.424433 2
#> 6 1 -7.60 -12.40 1.5100835 0.5326360 -6.0899165 -11.867364 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4560 -71650 14700
#> initial value 998.131940
#> iter 2 value 678.846262
#> iter 3 value 678.811369
#> iter 4 value 678.781960
#> iter 5 value 659.330961
#> iter 6 value 657.227740
#> iter 7 value 657.180028
#> iter 8 value 657.179770
#> iter 8 value 657.179769
#> final value 657.179769
#> converged
#> This is Run number 384
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.99549760 0.267883669 -3.3045024 -12.3321163 1
#> 2 1 -0.35 -14.40 1.14379457 2.192335287 0.7937946 -12.2076647 1
#> 3 1 -12.20 -2.55 0.09736492 1.996201425 -12.1026351 -0.5537986 2
#> 4 1 -2.30 -13.70 -0.23341442 -0.035418155 -2.5334144 -13.7354182 1
#> 5 1 -12.60 -7.80 0.51685179 1.059658212 -12.0831482 -6.7403418 2
#> 6 1 -7.60 -12.40 0.38232513 0.007891422 -7.2176749 -12.3921086 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4840 -72850 13700
#> initial value 998.131940
#> iter 2 value 669.676332
#> iter 3 value 669.540482
#> iter 4 value 669.499222
#> iter 5 value 649.030752
#> iter 6 value 646.736989
#> iter 7 value 646.682883
#> iter 8 value 646.682608
#> iter 8 value 646.682606
#> final value 646.682606
#> converged
#> This is Run number 385
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.3265118 -0.87820937 -5.626512 -13.4782094 1
#> 2 1 -0.35 -14.40 -0.7634076 -0.30681093 -1.113408 -14.7068109 1
#> 3 1 -12.20 -2.55 -0.4141484 2.21113036 -12.614148 -0.3388696 2
#> 4 1 -2.30 -13.70 3.6917226 5.13036474 1.391723 -8.5696353 1
#> 5 1 -12.60 -7.80 0.3809284 -0.06032114 -12.219072 -7.8603211 2
#> 6 1 -7.60 -12.40 -0.1314865 0.15343655 -7.731486 -12.2465635 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4460 -74800 15075
#> initial value 998.131940
#> iter 2 value 649.547786
#> iter 3 value 649.218725
#> iter 4 value 649.141340
#> iter 5 value 625.677752
#> iter 6 value 622.570029
#> iter 7 value 622.469901
#> iter 8 value 622.468878
#> iter 8 value 622.468869
#> final value 622.468869
#> converged
#> This is Run number 386
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.15378318 0.8420150 -5.453783 -11.757985 1
#> 2 1 -0.35 -14.40 1.50583429 -1.0079140 1.155834 -15.407914 1
#> 3 1 -12.20 -2.55 1.04946332 -0.7121757 -11.150537 -3.262176 2
#> 4 1 -2.30 -13.70 -0.97833314 -0.1920455 -3.278333 -13.892046 1
#> 5 1 -12.60 -7.80 0.06193092 -0.3192316 -12.538069 -8.119232 2
#> 6 1 -7.60 -12.40 0.67482102 0.8467077 -6.925179 -11.553292 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4620 -70475 14500
#> initial value 998.131940
#> iter 2 value 689.502966
#> iter 3 value 689.484756
#> iter 4 value 689.482164
#> iter 5 value 671.259561
#> iter 6 value 669.561896
#> iter 7 value 669.528260
#> iter 8 value 669.528126
#> iter 8 value 669.528125
#> final value 669.528125
#> converged
#> This is Run number 387
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.08805677 1.5961187 -2.211943 -11.003881 1
#> 2 1 -0.35 -14.40 1.42770046 0.7102376 1.077700 -13.689762 1
#> 3 1 -12.20 -2.55 -0.05589414 1.3196000 -12.255894 -1.230400 2
#> 4 1 -2.30 -13.70 -0.23475321 -0.7212975 -2.534753 -14.421297 1
#> 5 1 -12.60 -7.80 1.12630698 0.3894166 -11.473693 -7.410583 2
#> 6 1 -7.60 -12.40 0.52267726 -0.8309596 -7.077323 -13.230960 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4360 -72150 14550
#> initial value 998.131940
#> iter 2 value 674.770565
#> iter 3 value 674.532135
#> iter 4 value 674.483624
#> iter 5 value 654.440696
#> iter 6 value 652.182754
#> iter 7 value 652.127792
#> iter 8 value 652.127427
#> iter 8 value 652.127424
#> final value 652.127424
#> converged
#> This is Run number 388
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.6118877 1.0815356 -3.688112 -11.518464 1
#> 2 1 -0.35 -14.40 1.4554537 -0.6413781 1.105454 -15.041378 1
#> 3 1 -12.20 -2.55 1.2972599 -0.3893293 -10.902740 -2.939329 2
#> 4 1 -2.30 -13.70 -0.4422258 0.9905778 -2.742226 -12.709422 1
#> 5 1 -12.60 -7.80 2.1794159 -0.7046315 -10.420584 -8.504631 2
#> 6 1 -7.60 -12.40 1.2174276 -0.2512370 -6.382572 -12.651237 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5020 -72650 16250
#> initial value 998.131940
#> iter 2 value 666.574001
#> iter 3 value 666.125039
#> iter 4 value 665.976174
#> iter 5 value 644.781999
#> iter 6 value 642.268719
#> iter 7 value 642.203741
#> iter 8 value 642.203374
#> iter 8 value 642.203372
#> final value 642.203372
#> converged
#> This is Run number 389
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.4436331 4.49467339 -3.85636695 -8.105327 1
#> 2 1 -0.35 -14.40 0.3318243 1.58944666 -0.01817568 -12.810553 1
#> 3 1 -12.20 -2.55 1.6680216 0.44554189 -10.53197841 -2.104458 2
#> 4 1 -2.30 -13.70 0.2988160 0.01985401 -2.00118400 -13.680146 1
#> 5 1 -12.60 -7.80 1.8015214 0.23391804 -10.79847864 -7.566082 2
#> 6 1 -7.60 -12.40 -0.7561767 -0.02222277 -8.35617666 -12.422223 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4620 -72450 14775
#> initial value 998.131940
#> iter 2 value 671.532911
#> iter 3 value 671.502680
#> iter 4 value 671.477756
#> iter 5 value 651.105620
#> iter 6 value 648.800749
#> iter 7 value 648.744278
#> iter 8 value 648.743938
#> iter 8 value 648.743935
#> final value 648.743935
#> converged
#> This is Run number 390
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.2590906 3.0828411 -4.559091 -9.517159 1
#> 2 1 -0.35 -14.40 -0.9504547 2.6854958 -1.300455 -11.714504 1
#> 3 1 -12.20 -2.55 2.6656746 -0.1591727 -9.534325 -2.709173 2
#> 4 1 -2.30 -13.70 -0.3169159 1.0030569 -2.616916 -12.696943 1
#> 5 1 -12.60 -7.80 -0.5437199 0.7415460 -13.143720 -7.058454 2
#> 6 1 -7.60 -12.40 2.3068546 0.7163272 -5.293145 -11.683673 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4500 -72025 14775
#> initial value 998.131940
#> iter 2 value 675.403745
#> iter 3 value 675.349118
#> iter 4 value 675.304664
#> iter 5 value 655.372284
#> iter 6 value 653.153039
#> iter 7 value 653.099870
#> iter 8 value 653.099549
#> iter 8 value 653.099547
#> final value 653.099547
#> converged
#> This is Run number 391
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.64213004 -0.5862174 -4.942130 -13.186217 1
#> 2 1 -0.35 -14.40 2.11835571 -0.2768678 1.768356 -14.676868 1
#> 3 1 -12.20 -2.55 1.02123320 6.3755098 -11.178767 3.825510 2
#> 4 1 -2.30 -13.70 -0.38409478 -0.5861854 -2.684095 -14.286185 1
#> 5 1 -12.60 -7.80 -0.15141692 4.2771842 -12.751417 -3.522816 2
#> 6 1 -7.60 -12.40 0.07968461 0.9954523 -7.520315 -11.404548 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4340 -71950 12800
#> initial value 998.131940
#> iter 2 value 679.448655
#> iter 3 value 678.858937
#> iter 4 value 678.412240
#> iter 5 value 658.874311
#> iter 6 value 656.762682
#> iter 7 value 656.715105
#> iter 8 value 656.714844
#> iter 8 value 656.714843
#> final value 656.714843
#> converged
#> This is Run number 392
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 2.0347111 -0.2997248 -2.2652889 -12.899725 1
#> 2 1 -0.35 -14.40 -0.0213697 3.3486733 -0.3713697 -11.051327 1
#> 3 1 -12.20 -2.55 1.1011357 0.2832718 -11.0988643 -2.266728 2
#> 4 1 -2.30 -13.70 3.2566784 -0.3009832 0.9566784 -14.000983 1
#> 5 1 -12.60 -7.80 1.6585178 -0.5962333 -10.9414822 -8.396233 2
#> 6 1 -7.60 -12.40 0.8531375 0.3878074 -6.7468625 -12.012193 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4640 -72725 13675
#> initial value 998.131940
#> iter 2 value 670.962379
#> iter 3 value 670.785339
#> iter 4 value 670.655218
#> iter 5 value 650.268496
#> iter 6 value 647.971520
#> iter 7 value 647.916743
#> iter 8 value 647.916436
#> iter 8 value 647.916434
#> final value 647.916434
#> converged
#> This is Run number 393
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.1728994 0.49463701 -3.127101 -12.105363 1
#> 2 1 -0.35 -14.40 -1.5363894 -0.39306095 -1.886389 -14.793061 1
#> 3 1 -12.20 -2.55 1.8340732 0.32229649 -10.365927 -2.227704 2
#> 4 1 -2.30 -13.70 -0.3805726 0.67815335 -2.680573 -13.021847 1
#> 5 1 -12.60 -7.80 2.0409330 0.06195916 -10.559067 -7.738041 2
#> 6 1 -7.60 -12.40 0.6132919 -0.79570881 -6.986708 -13.195709 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5360 -73225 13950
#> initial value 998.131940
#> iter 2 value 665.520988
#> iter 3 value 665.390102
#> iter 4 value 665.320057
#> iter 5 value 644.413062
#> iter 6 value 642.046750
#> iter 7 value 641.991539
#> iter 8 value 641.991312
#> iter 8 value 641.991311
#> final value 641.991311
#> converged
#> This is Run number 394
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.5976996 0.6341318 -3.7023004 -11.965868 1
#> 2 1 -0.35 -14.40 0.0425985 0.2291795 -0.3074015 -14.170821 1
#> 3 1 -12.20 -2.55 -0.5592776 0.7237825 -12.7592776 -1.826217 2
#> 4 1 -2.30 -13.70 -0.3516388 0.2601469 -2.6516388 -13.439853 1
#> 5 1 -12.60 -7.80 0.2060465 -0.3523917 -12.3939535 -8.152392 2
#> 6 1 -7.60 -12.40 0.3678169 -1.5555695 -7.2321831 -13.955569 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5220 -71325 13225
#> initial value 998.131940
#> iter 2 value 683.834238
#> iter 3 value 683.616508
#> iter 4 value 683.574142
#> iter 5 value 664.957415
#> iter 6 value 663.090190
#> iter 7 value 663.054470
#> iter 8 value 663.054365
#> iter 8 value 663.054365
#> final value 663.054365
#> converged
#> This is Run number 395
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.3162041 3.409546065 -4.61620405 -9.190454 1
#> 2 1 -0.35 -14.40 0.4267161 0.386028959 0.07671614 -14.013971 1
#> 3 1 -12.20 -2.55 0.1115938 0.238280409 -12.08840618 -2.311720 2
#> 4 1 -2.30 -13.70 0.7718747 -0.770536547 -1.52812530 -14.470537 1
#> 5 1 -12.60 -7.80 0.5131319 -0.005922391 -12.08686810 -7.805922 2
#> 6 1 -7.60 -12.40 1.5996178 0.030106035 -6.00038221 -12.369894 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5600 -74550 15125
#> initial value 998.131940
#> iter 2 value 651.064890
#> iter 3 value 650.621236
#> iter 4 value 650.605118
#> iter 5 value 627.679508
#> iter 6 value 624.819958
#> iter 7 value 624.741247
#> iter 8 value 624.740823
#> iter 8 value 624.740821
#> final value 624.740821
#> converged
#> This is Run number 396
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.1662022 0.9409474 -4.1337978 -11.659053 1
#> 2 1 -0.35 -14.40 -0.2750074 0.1244792 -0.6250074 -14.275521 1
#> 3 1 -12.20 -2.55 0.2385702 -1.0719245 -11.9614298 -3.621925 2
#> 4 1 -2.30 -13.70 1.3299788 1.4116138 -0.9700212 -12.288386 1
#> 5 1 -12.60 -7.80 2.2035846 -0.4130746 -10.3964154 -8.213075 2
#> 6 1 -7.60 -12.40 0.9462348 0.2536262 -6.6537652 -12.146374 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5120 -74000 14225
#> initial value 998.131940
#> iter 2 value 658.116323
#> iter 3 value 658.059359
#> iter 4 value 658.058795
#> iter 5 value 635.190630
#> iter 6 value 633.492198
#> iter 7 value 633.446551
#> iter 8 value 633.446357
#> iter 8 value 633.446355
#> final value 633.446355
#> converged
#> This is Run number 397
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 0.9373730 2.9264764 -3.3626270 -9.673524 1
#> 2 1 -0.35 -14.40 0.7813726 -0.9344105 0.4313726 -15.334410 1
#> 3 1 -12.20 -2.55 -0.1344729 -1.5412636 -12.3344729 -4.091264 2
#> 4 1 -2.30 -13.70 -1.0523780 0.1023750 -3.3523780 -13.597625 1
#> 5 1 -12.60 -7.80 -0.8736665 1.1594645 -13.4736665 -6.640535 2
#> 6 1 -7.60 -12.40 -1.5656720 0.1807164 -9.1656720 -12.219284 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5440 -72300 13800
#> initial value 998.131940
#> iter 2 value 674.072068
#> iter 3 value 673.894852
#> iter 4 value 673.751665
#> iter 5 value 653.913386
#> iter 6 value 651.789729
#> iter 7 value 651.744894
#> iter 8 value 651.744744
#> iter 8 value 651.744744
#> final value 651.744744
#> converged
#> This is Run number 398
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 1.80882089 1.5085413 -2.491179 -11.09145870 1
#> 2 1 -0.35 -14.40 -1.08462787 2.3356897 -1.434628 -12.06431029 1
#> 3 1 -12.20 -2.55 0.09543092 2.5183198 -12.104569 -0.03168025 2
#> 4 1 -2.30 -13.70 1.12205737 0.1796286 -1.177943 -13.52037136 1
#> 5 1 -12.60 -7.80 1.28236998 -0.1828278 -11.317630 -7.98282776 2
#> 6 1 -7.60 -12.40 -0.43474305 1.5504189 -8.034743 -10.84958112 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4460 -74375 16250
#> initial value 998.131940
#> iter 2 value 651.153594
#> iter 3 value 650.812314
#> iter 4 value 650.725092
#> iter 5 value 627.323430
#> iter 6 value 624.197270
#> iter 7 value 624.094192
#> iter 8 value 624.093145
#> iter 8 value 624.093138
#> final value 624.093138
#> converged
#> This is Run number 399
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -0.0504533 1.0578019 -4.350453 -11.542198 1
#> 2 1 -0.35 -14.40 -0.7823749 -1.1968938 -1.132375 -15.596894 1
#> 3 1 -12.20 -2.55 1.0670194 0.7360541 -11.132981 -1.813946 2
#> 4 1 -2.30 -13.70 -1.2507973 0.3416819 -3.550797 -13.358318 1
#> 5 1 -12.60 -7.80 1.2278414 0.7945179 -11.372159 -7.005482 2
#> 6 1 -7.60 -12.40 0.5799862 0.6721747 -7.020014 -11.727825 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4540 -70800 14600
#> initial value 998.131940
#> iter 2 value 686.529176
#> iter 3 value 686.496561
#> iter 4 value 686.478242
#> iter 5 value 667.973117
#> iter 6 value 666.080436
#> iter 7 value 666.041173
#> iter 8 value 666.040991
#> iter 8 value 666.040990
#> final value 666.040990
#> converged
#> This is Run number 400
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 9 80 50 0 60 200 100 1
#> 2 1 12 60 25 100 40 200 0 1
#> 3 1 13 20 200 100 80 25 0 1
#> 4 1 70 80 50 100 20 200 25 1
#> 5 1 71 60 200 100 80 100 0 1
#> 6 1 73 60 100 0 40 200 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -4.30 -12.60 -1.93221339 -0.2428991 -6.232213 -12.842899 1
#> 2 1 -0.35 -14.40 3.15680315 0.3766600 2.806803 -14.023340 1
#> 3 1 -12.20 -2.55 -0.48498522 -0.1312370 -12.684985 -2.681237 2
#> 4 1 -2.30 -13.70 -0.04158429 3.1096781 -2.341584 -10.590322 1
#> 5 1 -12.60 -7.80 -0.82381035 0.9514004 -13.423810 -6.848600 2
#> 6 1 -7.60 -12.40 0.19613015 -0.3287559 -7.403870 -12.728756 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4820 -71525 13475
#> initial value 998.131940
#> iter 2 value 681.920935
#> iter 3 value 681.800826
#> iter 4 value 681.783559
#> iter 5 value 662.856611
#> iter 6 value 660.915060
#> iter 7 value 660.875253
#> iter 8 value 660.875095
#> iter 8 value 660.875094
#> final value 660.875094
#> converged
#>
#>
#> ================ ==== === ===== ==== ====== ===== ===== ===== ===== ======== ====
#> \ vars n mean sd median min max range skew kurtosis se
#> ================ ==== === ===== ==== ====== ===== ===== ===== ===== ======== ====
#> est_bpreis 1 400 0.00 0.00 0.00 0.00 0.00 0.01 0.04 -0.04 0.00
#> est_blade 2 400 -0.01 0.00 -0.01 -0.01 -0.01 0.00 -0.16 0.00 0.00
#> est_bwarte 3 400 0.00 0.00 0.00 0.00 0.00 0.00 -0.20 -0.14 0.00
#> rob_pval0_bpreis 4 400 0.60 0.26 0.62 0.02 1.00 0.98 -0.26 -0.94 0.01
#> rob_pval0_blade 5 400 0.00 0.00 0.00 0.00 0.00 0.00 NaN NaN 0.00
#> rob_pval0_bwarte 6 400 0.03 0.07 0.00 0.00 0.93 0.93 6.77 68.33 0.00
#> ================ ==== === ===== ==== ====== ===== ===== ===== ===== ======== ====
#>
#> FALSE TRUE
#> 99.5 0.5
#> 'simple' is deprecated and will be removed in the future. Use 'exact' instead.
#> bcoeff_lookup already exists; skipping modification.
#> Utility function used in simulation, ie the true utility:
#>
#> $u1
#> $u1$v1
#> V.1 ~ bpreis * alt1.x1 + blade * alt1.x2 + bwarte * alt1.x3
#> <environment: 0x5cc613e605b8>
#>
#> $u1$v2
#> V.2 ~ bpreis * alt2.x1 + blade * alt2.x2 + bwarte * alt2.x3
#> <environment: 0x5cc613ccff70>
#>
#>
#> $u2
#> $u2$v1
#> V.1 ~ bpreis * alt1.x1
#> <environment: 0x5cc61414a1d8>
#>
#> $u2$v2
#> V.2 ~ bpreis * alt2.x1
#> <environment: 0x5cc6137be2f0>
#> 'destype' is deprecated. Please use 'designtype' instead.
#> New names:
#>
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 3.02528852 -0.70994333 2.475289 -13.909943 1
#> 2 1 -3.10 -5.40 0.68244517 0.34087389 -2.417555 -5.059126 1
#> 3 1 -14.60 -12.20 0.46499630 0.81641767 -14.135004 -11.383582 2
#> 4 1 -14.20 -0.55 0.08203439 0.14672696 -14.117966 -0.403273 2
#> 5 1 -5.40 -3.30 0.23605425 -1.75537171 -5.163946 -5.055372 2
#> 6 1 -4.10 -2.55 0.35449270 -0.03041502 -3.745507 -2.580415 2
#>
#>
#> Transformed utility function (type: simple ):
#> [1] "U_1 = @bpreis * $alt1_x1 + @blade * $alt1_x2 + @bwarte * $alt1_x3 ;U_2 = @bpreis * $alt2_x1 + @blade * $alt2_x2 + @bwarte * $alt2_x3 ;"
#> This is Run number 1
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.90763948 3.3271422 0.3576395 -9.8728578 1
#> 2 1 -3.10 -5.40 1.31834491 -1.0308874 -1.7816551 -6.4308874 1
#> 3 1 -14.60 -12.20 0.05001073 0.2634511 -14.5499893 -11.9365489 2
#> 4 1 -14.20 -0.55 1.06277693 0.2813064 -13.1372231 -0.2686936 2
#> 5 1 -5.40 -3.30 4.81348729 2.8871078 -0.5865127 -0.4128922 2
#> 6 1 -4.10 -2.55 0.09799839 1.5344117 -4.0020016 -1.0155883 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6840 -37450 6375
#> initial value 998.131940
#> iter 2 value 846.008014
#> iter 3 value 841.618609
#> iter 4 value 839.665146
#> iter 5 value 790.901987
#> iter 6 value 780.312642
#> iter 7 value 778.593460
#> iter 8 value 778.554095
#> iter 9 value 778.554064
#> iter 10 value 778.554048
#> iter 11 value 778.553994
#> iter 12 value 778.553948
#> iter 12 value 778.553948
#> iter 12 value 778.553948
#> final value 778.553948
#> converged
#> This is Run number 2
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -1.07548223 1.3968750 -1.625482 -11.8031250 1
#> 2 1 -3.10 -5.40 -0.06506065 2.4283387 -3.165061 -2.9716613 2
#> 3 1 -14.60 -12.20 2.20947592 0.8640842 -12.390524 -11.3359158 2
#> 4 1 -14.20 -0.55 0.31487723 -0.4384846 -13.885123 -0.9884846 2
#> 5 1 -5.40 -3.30 -0.68525370 -0.2645240 -6.085254 -3.5645240 2
#> 6 1 -4.10 -2.55 1.07677584 1.7133891 -3.023224 -0.8366109 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5980 -35625 6825
#> initial value 998.131940
#> iter 2 value 867.326617
#> iter 3 value 863.824257
#> iter 4 value 860.627073
#> iter 5 value 806.029443
#> iter 6 value 796.289687
#> iter 7 value 794.611451
#> iter 8 value 794.578634
#> iter 9 value 794.578597
#> iter 10 value 794.578575
#> iter 11 value 794.578526
#> iter 12 value 794.578497
#> iter 12 value 794.578497
#> iter 12 value 794.578497
#> final value 794.578497
#> converged
#> This is Run number 3
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.2596672 2.63915318 -0.8096672 -10.5608468 1
#> 2 1 -3.10 -5.40 -0.2666580 1.70993192 -3.3666580 -3.6900681 1
#> 3 1 -14.60 -12.20 0.9038578 1.64217847 -13.6961422 -10.5578215 2
#> 4 1 -14.20 -0.55 -1.1036047 -0.40434470 -15.3036047 -0.9543447 2
#> 5 1 -5.40 -3.30 3.0835202 -0.07462033 -2.3164798 -3.3746203 1
#> 6 1 -4.10 -2.55 1.3449096 1.24575656 -2.7550904 -1.3042434 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6500 -35900 6700
#> initial value 998.131940
#> iter 2 value 864.518948
#> iter 3 value 862.014149
#> iter 4 value 860.827859
#> iter 5 value 806.669401
#> iter 6 value 796.701543
#> iter 7 value 794.981859
#> iter 8 value 794.946218
#> iter 9 value 794.946163
#> iter 10 value 794.946135
#> iter 11 value 794.946081
#> iter 12 value 794.946044
#> iter 12 value 794.946044
#> iter 12 value 794.946044
#> final value 794.946044
#> converged
#> This is Run number 4
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.31690216 -0.5165564 1.766902 -13.7165564 1
#> 2 1 -3.10 -5.40 1.34806806 -1.2833637 -1.751932 -6.6833637 1
#> 3 1 -14.60 -12.20 0.44226740 0.8483838 -14.157733 -11.3516162 2
#> 4 1 -14.20 -0.55 5.29976916 -0.2112677 -8.900231 -0.7612677 2
#> 5 1 -5.40 -3.30 0.06069289 0.3663346 -5.339307 -2.9336654 2
#> 6 1 -4.10 -2.55 2.23548737 1.0176448 -1.864513 -1.5323552 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5780 -35175 6625
#> initial value 998.131940
#> iter 2 value 873.950383
#> iter 3 value 870.540146
#> iter 4 value 866.423359
#> iter 5 value 811.257507
#> iter 6 value 801.766063
#> iter 7 value 800.069095
#> iter 8 value 800.035564
#> iter 9 value 800.035523
#> iter 9 value 800.035518
#> iter 9 value 800.035518
#> final value 800.035518
#> converged
#> This is Run number 5
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.60841637 1.5035540 -1.158416 -11.6964460 1
#> 2 1 -3.10 -5.40 -0.02662212 0.6990950 -3.126622 -4.7009050 1
#> 3 1 -14.60 -12.20 0.68905188 -1.4797568 -13.910948 -13.6797568 2
#> 4 1 -14.20 -0.55 0.15421777 0.2720571 -14.045782 -0.2779429 2
#> 5 1 -5.40 -3.30 1.52828884 -0.8506574 -3.871711 -4.1506574 1
#> 6 1 -4.10 -2.55 1.01621204 2.8245259 -3.083788 0.2745259 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7140 -37725 6200
#> initial value 998.131940
#> iter 2 value 842.959388
#> iter 3 value 838.955024
#> iter 4 value 837.745270
#> iter 5 value 789.908635
#> iter 6 value 779.168498
#> iter 7 value 777.421442
#> iter 8 value 777.379389
#> iter 9 value 777.379341
#> iter 10 value 777.379320
#> iter 11 value 777.379269
#> iter 12 value 777.379231
#> iter 12 value 777.379231
#> iter 12 value 777.379231
#> final value 777.379231
#> converged
#> This is Run number 6
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.96458983 -0.01651627 2.414590 -13.2165163 1
#> 2 1 -3.10 -5.40 -0.30920491 -0.03919222 -3.409205 -5.4391922 1
#> 3 1 -14.60 -12.20 -1.37443707 -0.98443402 -15.974437 -13.1844340 2
#> 4 1 -14.20 -0.55 -0.06324216 0.25459055 -14.263242 -0.2954094 2
#> 5 1 -5.40 -3.30 0.62203563 -0.65071920 -4.777964 -3.9507192 2
#> 6 1 -4.10 -2.55 -0.06144710 2.21022169 -4.161447 -0.3397783 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6160 -36200 8025
#> initial value 998.131940
#> iter 2 value 852.244929
#> iter 3 value 848.032253
#> iter 4 value 846.815170
#> iter 5 value 791.322603
#> iter 6 value 781.353095
#> iter 7 value 779.783530
#> iter 8 value 779.759555
#> iter 9 value 779.759466
#> iter 10 value 779.759429
#> iter 11 value 779.759395
#> iter 11 value 779.759393
#> iter 11 value 779.759393
#> final value 779.759393
#> converged
#> This is Run number 7
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.5893729 -0.5764677 1.039373 -13.776468 1
#> 2 1 -3.10 -5.40 0.4759561 -0.3696834 -2.624044 -5.769683 1
#> 3 1 -14.60 -12.20 -0.1647257 0.7736950 -14.764726 -11.426305 2
#> 4 1 -14.20 -0.55 1.7520382 1.1146010 -12.447962 0.564601 2
#> 5 1 -5.40 -3.30 2.6332645 -0.1968581 -2.766735 -3.496858 1
#> 6 1 -4.10 -2.55 -0.3475618 -0.1663319 -4.447562 -2.716332 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6860 -37000 5525
#> initial value 998.131940
#> iter 2 value 856.624433
#> iter 3 value 853.021841
#> iter 4 value 850.296973
#> iter 5 value 801.728826
#> iter 6 value 791.388143
#> iter 7 value 789.372335
#> iter 8 value 789.316471
#> iter 9 value 789.316334
#> iter 10 value 789.316318
#> iter 11 value 789.316293
#> iter 12 value 789.316267
#> iter 12 value 789.316267
#> iter 12 value 789.316267
#> final value 789.316267
#> converged
#> This is Run number 8
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.8172738 2.4534360 0.2672738 -10.7465640 1
#> 2 1 -3.10 -5.40 0.7103202 1.7419968 -2.3896798 -3.6580032 1
#> 3 1 -14.60 -12.20 1.7699617 -0.6803334 -12.8300383 -12.8803334 1
#> 4 1 -14.20 -0.55 -0.0116915 0.7570815 -14.2116915 0.2070815 2
#> 5 1 -5.40 -3.30 0.4358475 -0.3331423 -4.9641525 -3.6331423 2
#> 6 1 -4.10 -2.55 1.2185100 -0.7765633 -2.8814900 -3.3265633 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6620 -35850 4900
#> initial value 998.131940
#> iter 2 value 874.470913
#> iter 3 value 871.575852
#> iter 4 value 868.031280
#> iter 5 value 817.511681
#> iter 6 value 807.911319
#> iter 7 value 805.587309
#> iter 8 value 805.521409
#> iter 9 value 805.521172
#> iter 9 value 805.521171
#> iter 9 value 805.521171
#> final value 805.521171
#> converged
#> This is Run number 9
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.9109775 0.2846043 0.3609775 -12.9153957 1
#> 2 1 -3.10 -5.40 2.6267803 0.4605270 -0.4732197 -4.9394730 1
#> 3 1 -14.60 -12.20 0.1995857 0.3387105 -14.4004143 -11.8612895 2
#> 4 1 -14.20 -0.55 0.8196019 1.1677647 -13.3803981 0.6177647 2
#> 5 1 -5.40 -3.30 0.8505988 0.1984909 -4.5494012 -3.1015091 2
#> 6 1 -4.10 -2.55 -1.2096666 1.0250598 -5.3096666 -1.5249402 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6880 -36775 4900
#> initial value 998.131940
#> iter 2 value 862.546980
#> iter 3 value 859.065098
#> iter 4 value 855.529214
#> iter 5 value 807.602880
#> iter 6 value 797.527878
#> iter 7 value 795.209905
#> iter 8 value 795.138811
#> iter 9 value 795.138545
#> iter 9 value 795.138543
#> iter 9 value 795.138543
#> final value 795.138543
#> converged
#> This is Run number 10
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.4155003 0.6573723 -0.9655003 -12.5426277 1
#> 2 1 -3.10 -5.40 -0.8535027 0.4388569 -3.9535027 -4.9611431 1
#> 3 1 -14.60 -12.20 2.2610975 0.5162272 -12.3389025 -11.6837728 2
#> 4 1 -14.20 -0.55 1.3489547 1.0674091 -12.8510453 0.5174091 2
#> 5 1 -5.40 -3.30 1.3190987 0.7864555 -4.0809013 -2.5135445 2
#> 6 1 -4.10 -2.55 0.2320448 0.6830972 -3.8679552 -1.8669028 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6540 -38000 7350
#> initial value 998.131940
#> iter 2 value 832.559051
#> iter 3 value 825.688466
#> iter 4 value 823.045355
#> iter 5 value 774.766609
#> iter 6 value 764.263658
#> iter 7 value 762.710131
#> iter 8 value 762.680964
#> iter 9 value 762.680812
#> iter 10 value 762.680759
#> iter 11 value 762.680741
#> iter 12 value 762.680712
#> iter 12 value 762.680712
#> iter 12 value 762.680712
#> final value 762.680712
#> converged
#> This is Run number 11
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.1327490 -0.42473652 -0.682749 -13.6247365 1
#> 2 1 -3.10 -5.40 0.6089120 -0.80196043 -2.491088 -6.2019604 1
#> 3 1 -14.60 -12.20 2.1590566 -0.54859181 -12.440943 -12.7485918 1
#> 4 1 -14.20 -0.55 2.1562311 0.98918902 -12.043769 0.4391890 2
#> 5 1 -5.40 -3.30 -0.3810852 -0.09280456 -5.781085 -3.3928046 2
#> 6 1 -4.10 -2.55 7.8963118 1.77255253 3.796312 -0.7774475 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 8040 -37500 4550
#> initial value 998.131940
#> iter 2 value 852.955869
#> iter 3 value 851.264820
#> iter 4 value 851.100315
#> iter 5 value 804.604739
#> iter 6 value 794.331647
#> iter 7 value 791.691864
#> iter 8 value 791.599390
#> iter 9 value 791.598904
#> iter 10 value 791.598874
#> iter 10 value 791.598865
#> iter 10 value 791.598857
#> final value 791.598857
#> converged
#> This is Run number 12
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.6851811 4.1366897 -1.235181 -9.0633103 1
#> 2 1 -3.10 -5.40 0.6562851 -0.6038914 -2.443715 -6.0038914 1
#> 3 1 -14.60 -12.20 1.3640892 0.2060611 -13.235911 -11.9939389 2
#> 4 1 -14.20 -0.55 0.9021882 2.0582305 -13.297812 1.5082305 2
#> 5 1 -5.40 -3.30 2.9437295 1.5084200 -2.456271 -1.7915800 2
#> 6 1 -4.10 -2.55 1.5622043 2.7017777 -2.537796 0.1517777 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5820 -35575 7675
#> initial value 998.131940
#> iter 2 value 862.508341
#> iter 3 value 858.841360
#> iter 4 value 856.316249
#> iter 5 value 799.814967
#> iter 6 value 790.126421
#> iter 7 value 788.533776
#> iter 8 value 788.507746
#> iter 9 value 788.507708
#> iter 10 value 788.507689
#> iter 11 value 788.507649
#> iter 12 value 788.507622
#> iter 12 value 788.507622
#> iter 12 value 788.507622
#> final value 788.507622
#> converged
#> This is Run number 13
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.2728004 -1.4115889 -0.2771996 -14.6115889 1
#> 2 1 -3.10 -5.40 1.2974715 0.7113266 -1.8025285 -4.6886734 1
#> 3 1 -14.60 -12.20 -0.9698873 0.3584653 -15.5698873 -11.8415347 2
#> 4 1 -14.20 -0.55 -0.9139499 0.3816086 -15.1139499 -0.1683914 2
#> 5 1 -5.40 -3.30 -0.5925152 -0.8766069 -5.9925152 -4.1766069 2
#> 6 1 -4.10 -2.55 1.8775163 -0.4745635 -2.2224837 -3.0245635 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6940 -37450 6950
#> initial value 998.131940
#> iter 2 value 842.477219
#> iter 3 value 838.100773
#> iter 4 value 837.309596
#> iter 5 value 787.424159
#> iter 6 value 776.823732
#> iter 7 value 775.209031
#> iter 8 value 775.177699
#> iter 9 value 775.177639
#> iter 10 value 775.177599
#> iter 11 value 775.177542
#> iter 12 value 775.177515
#> iter 12 value 775.177515
#> iter 12 value 775.177515
#> final value 775.177515
#> converged
#> This is Run number 14
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.007086136 -0.678872632 -0.5429139 -13.8788726 1
#> 2 1 -3.10 -5.40 1.055067697 0.988465113 -2.0449323 -4.4115349 1
#> 3 1 -14.60 -12.20 0.071203475 -0.009621214 -14.5287965 -12.2096212 2
#> 4 1 -14.20 -0.55 -0.356258462 0.734024416 -14.5562585 0.1840244 2
#> 5 1 -5.40 -3.30 -0.456796061 -1.059954760 -5.8567961 -4.3599548 2
#> 6 1 -4.10 -2.55 -0.401851520 0.242717664 -4.5018515 -2.3072823 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6160 -34000 5800
#> initial value 998.131940
#> iter 2 value 891.884291
#> iter 3 value 891.372681
#> iter 4 value 889.684086
#> iter 5 value 832.187507
#> iter 6 value 823.371373
#> iter 7 value 821.515912
#> iter 8 value 821.476543
#> iter 9 value 821.476445
#> iter 10 value 821.476410
#> iter 11 value 821.476361
#> iter 12 value 821.476339
#> iter 12 value 821.476339
#> iter 12 value 821.476339
#> final value 821.476339
#> converged
#> This is Run number 15
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.0322411 -1.3915722 0.4822411 -14.591572 1
#> 2 1 -3.10 -5.40 1.0014754 -0.1896714 -2.0985246 -5.589671 1
#> 3 1 -14.60 -12.20 -1.2917684 -0.6700770 -15.8917684 -12.870077 2
#> 4 1 -14.20 -0.55 0.6982712 1.9278354 -13.5017288 1.377835 2
#> 5 1 -5.40 -3.30 -0.8914384 1.8268969 -6.2914384 -1.473103 2
#> 6 1 -4.10 -2.55 -0.1766601 -0.7452310 -4.2766601 -3.295231 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6960 -37025 5125
#> initial value 998.131940
#> iter 2 value 858.158445
#> iter 3 value 854.688204
#> iter 4 value 851.704301
#> iter 5 value 803.931486
#> iter 6 value 793.663393
#> iter 7 value 791.468722
#> iter 8 value 791.402874
#> iter 9 value 791.402658
#> iter 9 value 791.402651
#> iter 9 value 791.402651
#> final value 791.402651
#> converged
#> This is Run number 16
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.9018604 -0.2478147 0.3518604 -13.447815 1
#> 2 1 -3.10 -5.40 0.8878357 -1.2255654 -2.2121643 -6.625565 1
#> 3 1 -14.60 -12.20 0.1952865 0.8974560 -14.4047135 -11.302544 2
#> 4 1 -14.20 -0.55 1.8889190 1.9316187 -12.3110810 1.381619 2
#> 5 1 -5.40 -3.30 -1.3585837 0.7021674 -6.7585837 -2.597833 2
#> 6 1 -4.10 -2.55 3.2344755 0.8036624 -0.8655245 -1.746338 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6980 -38200 5900
#> initial value 998.131940
#> iter 2 value 838.088742
#> iter 3 value 832.784959
#> iter 4 value 829.566952
#> iter 5 value 784.317969
#> iter 6 value 773.504847
#> iter 7 value 771.744850
#> iter 8 value 771.699360
#> iter 9 value 771.699322
#> iter 10 value 771.699306
#> iter 11 value 771.699274
#> iter 12 value 771.699248
#> iter 12 value 771.699248
#> iter 12 value 771.699248
#> final value 771.699248
#> converged
#> This is Run number 17
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -1.4699835 -1.60596936 -2.019983 -14.8059694 1
#> 2 1 -3.10 -5.40 0.9589402 2.82214065 -2.141060 -2.5778594 1
#> 3 1 -14.60 -12.20 -0.9442063 -0.44304215 -15.544206 -12.6430421 2
#> 4 1 -14.20 -0.55 -0.6162783 1.18262700 -14.816278 0.6326270 2
#> 5 1 -5.40 -3.30 0.3171382 -0.03873979 -5.082862 -3.3387398 2
#> 6 1 -4.10 -2.55 0.4505116 1.90761315 -3.649488 -0.6423869 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6560 -36800 5900
#> initial value 998.131940
#> iter 2 value 857.510607
#> iter 3 value 853.330390
#> iter 4 value 849.878216
#> iter 5 value 800.392253
#> iter 6 value 790.125813
#> iter 7 value 788.249307
#> iter 8 value 788.201994
#> iter 9 value 788.201914
#> iter 10 value 788.201896
#> iter 11 value 788.201865
#> iter 12 value 788.201840
#> iter 12 value 788.201840
#> iter 12 value 788.201840
#> final value 788.201840
#> converged
#> This is Run number 18
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.2769878 0.6203175 -0.8269878 -12.57968248 1
#> 2 1 -3.10 -5.40 0.1897700 0.6231066 -2.9102300 -4.77689344 1
#> 3 1 -14.60 -12.20 1.3097676 -1.0104082 -13.2902324 -13.21040819 2
#> 4 1 -14.20 -0.55 -0.2063501 0.5607748 -14.4063501 0.01077476 2
#> 5 1 -5.40 -3.30 1.0059570 1.1162843 -4.3940430 -2.18371571 2
#> 6 1 -4.10 -2.55 2.5403404 -0.7440465 -1.5596596 -3.29404647 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7120 -37625 5425
#> initial value 998.131940
#> iter 2 value 848.463241
#> iter 3 value 844.637671
#> iter 4 value 842.220890
#> iter 5 value 795.590487
#> iter 6 value 784.976642
#> iter 7 value 782.967100
#> iter 8 value 782.908764
#> iter 9 value 782.908623
#> iter 10 value 782.908610
#> iter 11 value 782.908587
#> iter 12 value 782.908560
#> iter 12 value 782.908560
#> iter 12 value 782.908560
#> final value 782.908560
#> converged
#> This is Run number 19
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.67211170 1.14135383 -1.222112 -12.0586462 1
#> 2 1 -3.10 -5.40 0.15864553 -0.25965880 -2.941354 -5.6596588 1
#> 3 1 -14.60 -12.20 -0.34257991 0.04829052 -14.942580 -12.1517095 2
#> 4 1 -14.20 -0.55 2.81741666 0.44337880 -11.382583 -0.1066212 2
#> 5 1 -5.40 -3.30 1.66806534 2.83809823 -3.731935 -0.4619018 2
#> 6 1 -4.10 -2.55 -0.09347346 0.18823489 -4.193473 -2.3617651 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6560 -34200 5725
#> initial value 998.131940
#> iter 2 value 889.870831
#> iter 3 value 889.845133
#> iter 4 value 889.263657
#> iter 5 value 832.129051
#> iter 6 value 823.189725
#> iter 7 value 821.244600
#> iter 8 value 821.200639
#> iter 9 value 821.200505
#> iter 10 value 821.200473
#> iter 11 value 821.200421
#> iter 12 value 821.200384
#> iter 12 value 821.200384
#> iter 12 value 821.200384
#> final value 821.200384
#> converged
#> This is Run number 20
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.30423031 -1.10831156 1.754230 -14.3083116 1
#> 2 1 -3.10 -5.40 -0.91667914 -0.48616013 -4.016679 -5.8861601 1
#> 3 1 -14.60 -12.20 -0.41635986 0.54867341 -15.016360 -11.6513266 2
#> 4 1 -14.20 -0.55 -0.14695708 0.05488111 -14.346957 -0.4951189 2
#> 5 1 -5.40 -3.30 -1.00014124 0.05551978 -6.400141 -3.2444802 2
#> 6 1 -4.10 -2.55 0.02980048 1.31491638 -4.070200 -1.2350836 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6480 -36425 5775
#> initial value 998.131940
#> iter 2 value 863.071898
#> iter 3 value 859.250788
#> iter 4 value 855.677165
#> iter 5 value 805.340072
#> iter 6 value 795.261526
#> iter 7 value 793.329150
#> iter 8 value 793.280011
#> iter 9 value 793.279911
#> iter 10 value 793.279893
#> iter 11 value 793.279865
#> iter 12 value 793.279841
#> iter 12 value 793.279841
#> iter 12 value 793.279841
#> final value 793.279841
#> converged
#> This is Run number 21
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.5928889 1.09935063 -1.142889 -12.100649 1
#> 2 1 -3.10 -5.40 1.3318646 -0.03801232 -1.768135 -5.438012 1
#> 3 1 -14.60 -12.20 2.7456376 -0.37546229 -11.854362 -12.575462 1
#> 4 1 -14.20 -0.55 1.4145979 1.87392680 -12.785402 1.323927 2
#> 5 1 -5.40 -3.30 1.9204827 0.06833140 -3.479517 -3.231669 2
#> 6 1 -4.10 -2.55 1.0080361 0.37972500 -3.091964 -2.170275 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7180 -37950 6600
#> initial value 998.131940
#> iter 2 value 837.463524
#> iter 3 value 832.968779
#> iter 4 value 832.161672
#> iter 5 value 784.384601
#> iter 6 value 773.584206
#> iter 7 value 771.947058
#> iter 8 value 771.912242
#> iter 9 value 771.912190
#> iter 10 value 771.912174
#> iter 11 value 771.912116
#> iter 12 value 771.912064
#> iter 12 value 771.912064
#> iter 12 value 771.912064
#> final value 771.912064
#> converged
#> This is Run number 22
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.0004067 -0.1451873 0.4504067 -13.345187 1
#> 2 1 -3.10 -5.40 0.2963629 -0.6412208 -2.8036371 -6.041221 1
#> 3 1 -14.60 -12.20 -0.4551832 0.9531311 -15.0551832 -11.246869 2
#> 4 1 -14.20 -0.55 1.2865208 2.9002974 -12.9134792 2.350297 2
#> 5 1 -5.40 -3.30 1.7545089 3.7876630 -3.6454911 0.487663 2
#> 6 1 -4.10 -2.55 1.9242531 -0.6416953 -2.1757469 -3.191695 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6800 -37700 6225
#> initial value 998.131940
#> iter 2 value 843.455679
#> iter 3 value 838.468736
#> iter 4 value 835.658685
#> iter 5 value 788.185609
#> iter 6 value 777.539505
#> iter 7 value 775.812061
#> iter 8 value 775.770988
#> iter 8 value 775.770978
#> final value 775.770978
#> converged
#> This is Run number 23
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.1851123 2.12442795 -0.7351123 -11.0755720 1
#> 2 1 -3.10 -5.40 1.1633453 -1.00339144 -1.9366547 -6.4033914 1
#> 3 1 -14.60 -12.20 0.2517174 -0.06717963 -14.3482826 -12.2671796 2
#> 4 1 -14.20 -0.55 1.6656914 1.16418985 -12.5343086 0.6141899 2
#> 5 1 -5.40 -3.30 0.7368808 -0.36778735 -4.6631192 -3.6677873 2
#> 6 1 -4.10 -2.55 3.5560307 1.87139922 -0.5439693 -0.6786008 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6520 -36200 7250
#> initial value 998.131940
#> iter 2 value 857.326565
#> iter 3 value 854.218695
#> iter 4 value 853.424959
#> iter 5 value 799.192136
#> iter 6 value 789.079422
#> iter 7 value 787.455928
#> iter 8 value 787.426717
#> iter 9 value 787.426670
#> iter 10 value 787.426643
#> iter 11 value 787.426592
#> iter 12 value 787.426558
#> iter 12 value 787.426558
#> iter 12 value 787.426558
#> final value 787.426558
#> converged
#> This is Run number 24
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.1028852 -0.40175250 0.5528852 -13.6017525 1
#> 2 1 -3.10 -5.40 0.1010775 -0.80254492 -2.9989225 -6.2025449 1
#> 3 1 -14.60 -12.20 1.6710429 -0.63969226 -12.9289571 -12.8396923 2
#> 4 1 -14.20 -0.55 0.3923208 0.04321433 -13.8076792 -0.5067857 2
#> 5 1 -5.40 -3.30 -1.8015909 0.40920632 -7.2015909 -2.8907937 2
#> 6 1 -4.10 -2.55 0.6377588 2.09116315 -3.4622412 -0.4588369 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7020 -37075 5550
#> initial value 998.131940
#> iter 2 value 855.369759
#> iter 3 value 852.158857
#> iter 4 value 850.223396
#> iter 5 value 801.559165
#> iter 6 value 791.157497
#> iter 7 value 789.140580
#> iter 8 value 789.084399
#> iter 9 value 789.084257
#> iter 10 value 789.084240
#> iter 11 value 789.084211
#> iter 12 value 789.084179
#> iter 12 value 789.084179
#> iter 12 value 789.084179
#> final value 789.084179
#> converged
#> This is Run number 25
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.2016096 2.0915790 -0.3483904 -11.10842098 1
#> 2 1 -3.10 -5.40 1.6181303 -0.2183448 -1.4818697 -5.61834483 1
#> 3 1 -14.60 -12.20 0.5942565 -0.3904294 -14.0057435 -12.59042940 2
#> 4 1 -14.20 -0.55 -0.2502198 0.5955215 -14.4502198 0.04552153 2
#> 5 1 -5.40 -3.30 -0.9592553 0.8275175 -6.3592553 -2.47248247 2
#> 6 1 -4.10 -2.55 1.5250736 2.4588837 -2.5749264 -0.09111634 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6800 -35125 5675
#> initial value 998.131940
#> iter 2 value 879.376211
#> iter 3 value 878.516697
#> iter 4 value 877.882543
#> iter 5 value 823.164834
#> iter 6 value 813.713999
#> iter 7 value 811.682071
#> iter 8 value 811.631826
#> iter 9 value 811.631668
#> iter 10 value 811.631643
#> iter 11 value 811.631596
#> iter 12 value 811.631552
#> iter 12 value 811.631552
#> iter 12 value 811.631552
#> final value 811.631552
#> converged
#> This is Run number 26
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.9780091 0.841295097 -1.528009 -12.358705 1
#> 2 1 -3.10 -5.40 -0.7917333 -0.003626345 -3.891733 -5.403626 1
#> 3 1 -14.60 -12.20 -1.0191406 1.264259285 -15.619141 -10.935741 2
#> 4 1 -14.20 -0.55 1.1462230 -0.637701908 -13.053777 -1.187702 2
#> 5 1 -5.40 -3.30 -0.3320388 -0.107109513 -5.732039 -3.407110 2
#> 6 1 -4.10 -2.55 0.3063906 -0.083140267 -3.793609 -2.633140 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7160 -37025 6400
#> initial value 998.131940
#> iter 2 value 851.286052
#> iter 3 value 848.298588
#> iter 4 value 847.909854
#> iter 5 value 797.491697
#> iter 6 value 786.969108
#> iter 7 value 785.213030
#> iter 8 value 785.172513
#> iter 9 value 785.172450
#> iter 10 value 785.172422
#> iter 11 value 785.172371
#> iter 12 value 785.172329
#> iter 12 value 785.172329
#> iter 12 value 785.172329
#> final value 785.172329
#> converged
#> This is Run number 27
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.57378316 0.48994614 -1.123783 -12.71005386 1
#> 2 1 -3.10 -5.40 0.06764351 0.91904312 -3.032356 -4.48095688 1
#> 3 1 -14.60 -12.20 0.03402399 -1.57107320 -14.565976 -13.77107320 2
#> 4 1 -14.20 -0.55 1.13051606 0.26428112 -13.069484 -0.28571888 2
#> 5 1 -5.40 -3.30 1.50562647 0.06397476 -3.894374 -3.23602524 2
#> 6 1 -4.10 -2.55 -0.62960691 2.59190933 -4.729607 0.04190933 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6600 -37100 5350
#> initial value 998.131940
#> iter 2 value 856.319949
#> iter 3 value 851.369330
#> iter 4 value 846.279053
#> iter 5 value 799.255183
#> iter 6 value 788.950911
#> iter 7 value 786.904113
#> iter 8 value 786.845369
#> iter 9 value 786.845218
#> iter 9 value 786.845212
#> iter 9 value 786.845212
#> final value 786.845212
#> converged
#> This is Run number 28
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.02871953 1.6896084 -0.5787195 -11.5103916 1
#> 2 1 -3.10 -5.40 0.34195407 0.4020162 -2.7580459 -4.9979838 1
#> 3 1 -14.60 -12.20 1.49695882 1.0179127 -13.1030412 -11.1820873 2
#> 4 1 -14.20 -0.55 3.61156968 -0.2811987 -10.5884303 -0.8311987 2
#> 5 1 -5.40 -3.30 2.35300115 3.1575593 -3.0469988 -0.1424407 2
#> 6 1 -4.10 -2.55 2.01573259 0.7375350 -2.0842674 -1.8124650 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7040 -37750 5800
#> initial value 998.131940
#> iter 2 value 844.890248
#> iter 3 value 840.628251
#> iter 4 value 838.289830
#> iter 5 value 791.457824
#> iter 6 value 780.760415
#> iter 7 value 778.908586
#> iter 8 value 778.859363
#> iter 9 value 778.859290
#> iter 10 value 778.859278
#> iter 11 value 778.859246
#> iter 12 value 778.859210
#> iter 12 value 778.859210
#> iter 12 value 778.859210
#> final value 778.859210
#> converged
#> This is Run number 29
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -1.0815741 2.5485167 -1.6315741 -10.6514833 1
#> 2 1 -3.10 -5.40 2.1204126 3.0512005 -0.9795874 -2.3487995 1
#> 3 1 -14.60 -12.20 1.3595612 -0.1133413 -13.2404388 -12.3133413 2
#> 4 1 -14.20 -0.55 1.5056242 6.1388371 -12.6943758 5.5888371 2
#> 5 1 -5.40 -3.30 -1.0710219 0.7489865 -6.4710219 -2.5510135 2
#> 6 1 -4.10 -2.55 -0.6618376 1.6070881 -4.7618376 -0.9429119 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6420 -35200 6050
#> initial value 998.131940
#> iter 2 value 876.764607
#> iter 3 value 875.119595
#> iter 4 value 873.514273
#> iter 5 value 818.592312
#> iter 6 value 809.056116
#> iter 7 value 807.184957
#> iter 8 value 807.142274
#> iter 9 value 807.142175
#> iter 10 value 807.142148
#> iter 11 value 807.142100
#> iter 12 value 807.142064
#> iter 12 value 807.142064
#> iter 12 value 807.142064
#> final value 807.142064
#> converged
#> This is Run number 30
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.1761005 0.7041782 0.6261005 -12.495822 1
#> 2 1 -3.10 -5.40 3.6892650 2.6210078 0.5892650 -2.778992 1
#> 3 1 -14.60 -12.20 -0.3270635 -0.2283315 -14.9270635 -12.428331 2
#> 4 1 -14.20 -0.55 1.0243556 2.1288107 -13.1756444 1.578811 2
#> 5 1 -5.40 -3.30 1.2665419 0.9696446 -4.1334581 -2.330355 2
#> 6 1 -4.10 -2.55 -0.5698317 -1.2119660 -4.6698317 -3.761966 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6260 -37100 7750
#> initial value 998.131940
#> iter 2 value 842.375680
#> iter 3 value 836.456847
#> iter 4 value 834.270061
#> iter 5 value 782.314896
#> iter 6 value 772.090541
#> iter 7 value 770.520730
#> iter 8 value 770.494031
#> iter 9 value 770.493916
#> iter 10 value 770.493871
#> iter 11 value 770.493840
#> iter 11 value 770.493832
#> iter 11 value 770.493832
#> final value 770.493832
#> converged
#> This is Run number 31
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.2438523 0.18476167 -0.3061477 -13.015238 1
#> 2 1 -3.10 -5.40 -0.4294206 1.13176764 -3.5294206 -4.268232 1
#> 3 1 -14.60 -12.20 -0.1782107 1.12148934 -14.7782107 -11.078511 2
#> 4 1 -14.20 -0.55 -0.1298008 2.45862916 -14.3298008 1.908629 2
#> 5 1 -5.40 -3.30 1.9006468 -1.26230712 -3.4993532 -4.562307 1
#> 6 1 -4.10 -2.55 1.0552392 -0.04266944 -3.0447608 -2.592669 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7140 -36350 7225
#> initial value 998.131940
#> iter 2 value 855.035748
#> iter 3 value 852.297027
#> iter 4 value 852.287530
#> iter 5 value 797.931585
#> iter 6 value 788.373247
#> iter 7 value 787.023050
#> iter 8 value 787.005493
#> iter 9 value 787.005427
#> iter 10 value 787.005390
#> iter 11 value 787.005335
#> iter 12 value 787.005309
#> iter 12 value 787.005309
#> iter 12 value 787.005309
#> final value 787.005309
#> converged
#> This is Run number 32
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.8037927 -1.253516838 0.2537927 -14.453517 1
#> 2 1 -3.10 -5.40 0.9352684 -0.884203752 -2.1647316 -6.284204 1
#> 3 1 -14.60 -12.20 0.2690616 -1.395348476 -14.3309384 -13.595348 2
#> 4 1 -14.20 -0.55 0.8509543 -0.684905491 -13.3490457 -1.234905 2
#> 5 1 -5.40 -3.30 2.6400784 0.586606358 -2.7599216 -2.713394 2
#> 6 1 -4.10 -2.55 3.2934225 0.007551378 -0.8065775 -2.542449 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6120 -34825 6000
#> initial value 998.131940
#> iter 2 value 881.540029
#> iter 3 value 879.631843
#> iter 4 value 876.971482
#> iter 5 value 821.486135
#> iter 6 value 812.189833
#> iter 7 value 810.344482
#> iter 8 value 810.304011
#> iter 9 value 810.303926
#> iter 10 value 810.303897
#> iter 11 value 810.303854
#> iter 12 value 810.303830
#> iter 12 value 810.303830
#> iter 12 value 810.303830
#> final value 810.303830
#> converged
#> This is Run number 33
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.7910883 0.6583296 -1.341088 -12.541670 1
#> 2 1 -3.10 -5.40 -1.2980438 2.0007552 -4.398044 -3.399245 2
#> 3 1 -14.60 -12.20 0.2346143 -1.3645944 -14.365386 -13.564594 2
#> 4 1 -14.20 -0.55 0.6166877 2.2742823 -13.583312 1.724282 2
#> 5 1 -5.40 -3.30 -0.4732141 0.6414012 -5.873214 -2.658599 2
#> 6 1 -4.10 -2.55 -0.1478530 -0.2795808 -4.247853 -2.829581 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6240 -35975 6850
#> initial value 998.131940
#> iter 2 value 862.791964
#> iter 3 value 859.443090
#> iter 4 value 857.227500
#> iter 5 value 803.291850
#> iter 6 value 793.347989
#> iter 7 value 791.666575
#> iter 8 value 791.633237
#> iter 9 value 791.633212
#> iter 10 value 791.633193
#> iter 11 value 791.633137
#> iter 12 value 791.633087
#> iter 12 value 791.633087
#> iter 12 value 791.633087
#> final value 791.633087
#> converged
#> This is Run number 34
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.9155134 0.8590109 2.365513 -12.340989 1
#> 2 1 -3.10 -5.40 -0.1582469 -0.7946782 -3.258247 -6.194678 1
#> 3 1 -14.60 -12.20 0.1085565 0.4978171 -14.491443 -11.702183 2
#> 4 1 -14.20 -0.55 -0.6297086 2.2563965 -14.829709 1.706397 2
#> 5 1 -5.40 -3.30 1.2242334 0.6975717 -4.175767 -2.602428 2
#> 6 1 -4.10 -2.55 2.1796121 1.1285298 -1.920388 -1.421470 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6680 -35025 6325
#> initial value 998.131940
#> iter 2 value 877.143999
#> iter 3 value 876.335647
#> iter 4 value 875.977975
#> iter 5 value 819.922496
#> iter 6 value 810.385148
#> iter 7 value 808.565600
#> iter 8 value 808.525264
#> iter 9 value 808.525163
#> iter 10 value 808.525128
#> iter 11 value 808.525077
#> iter 12 value 808.525039
#> iter 12 value 808.525039
#> iter 12 value 808.525039
#> final value 808.525039
#> converged
#> This is Run number 35
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 3.0618697 -0.2888840 2.511870 -13.48888404 1
#> 2 1 -3.10 -5.40 1.3374503 3.7474568 -1.762550 -1.65254316 2
#> 3 1 -14.60 -12.20 4.1863313 -0.3793027 -10.413669 -12.57930274 1
#> 4 1 -14.20 -0.55 -0.4995222 0.4882928 -14.699522 -0.06170717 2
#> 5 1 -5.40 -3.30 1.3373114 0.2094678 -4.062689 -3.09053218 2
#> 6 1 -4.10 -2.55 3.4902420 -0.8667621 -0.609758 -3.41676212 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6380 -34675 6500
#> initial value 998.131940
#> iter 2 value 880.393541
#> iter 3 value 879.685418
#> iter 4 value 878.951580
#> iter 5 value 821.673131
#> iter 6 value 812.324977
#> iter 7 value 810.575187
#> iter 8 value 810.539071
#> iter 9 value 810.538991
#> iter 10 value 810.538958
#> iter 11 value 810.538905
#> iter 12 value 810.538869
#> iter 12 value 810.538869
#> iter 12 value 810.538869
#> final value 810.538869
#> converged
#> This is Run number 36
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.8711150 4.3417512 -1.421115 -8.858249 1
#> 2 1 -3.10 -5.40 -0.4820179 0.7993986 -3.582018 -4.600601 1
#> 3 1 -14.60 -12.20 -0.1290721 1.4134096 -14.729072 -10.786590 2
#> 4 1 -14.20 -0.55 -0.2502163 -1.3961456 -14.450216 -1.946146 2
#> 5 1 -5.40 -3.30 0.7440296 -0.7031899 -4.655970 -4.003190 2
#> 6 1 -4.10 -2.55 -0.3338736 -0.0954286 -4.433874 -2.645429 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6420 -36325 6975
#> initial value 998.131940
#> iter 2 value 857.529775
#> iter 3 value 854.007269
#> iter 4 value 852.397119
#> iter 5 value 799.134658
#> iter 6 value 789.010538
#> iter 7 value 787.351198
#> iter 8 value 787.318949
#> iter 9 value 787.318898
#> iter 10 value 787.318878
#> iter 11 value 787.318841
#> iter 12 value 787.318795
#> iter 12 value 787.318795
#> iter 12 value 787.318795
#> final value 787.318795
#> converged
#> This is Run number 37
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 3.44194458 3.04977080 2.891945 -10.150229 1
#> 2 1 -3.10 -5.40 -0.05867224 -0.02637799 -3.158672 -5.426378 1
#> 3 1 -14.60 -12.20 1.32198780 -0.21497665 -13.278012 -12.414977 2
#> 4 1 -14.20 -0.55 0.76769024 1.71260750 -13.432310 1.162608 2
#> 5 1 -5.40 -3.30 -1.36621538 -0.67287046 -6.766215 -3.972870 2
#> 6 1 -4.10 -2.55 1.15238164 1.00978923 -2.947618 -1.540211 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6960 -35750 5750
#> initial value 998.131940
#> iter 2 value 871.335724
#> iter 3 value 869.935185
#> iter 4 value 869.353913
#> iter 5 value 816.198433
#> iter 6 value 806.385880
#> iter 7 value 804.363888
#> iter 8 value 804.312014
#> iter 9 value 804.311858
#> iter 10 value 804.311838
#> iter 11 value 804.311793
#> iter 12 value 804.311744
#> iter 12 value 804.311744
#> iter 12 value 804.311744
#> final value 804.311744
#> converged
#> This is Run number 38
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -1.48747983 -0.3561501 -2.037480 -13.556150 1
#> 2 1 -3.10 -5.40 -0.08109352 1.4390424 -3.181094 -3.960958 1
#> 3 1 -14.60 -12.20 0.23939822 0.4258075 -14.360602 -11.774193 2
#> 4 1 -14.20 -0.55 -0.76195443 1.6610349 -14.961954 1.111035 2
#> 5 1 -5.40 -3.30 0.97056866 1.0708088 -4.429431 -2.229191 2
#> 6 1 -4.10 -2.55 0.21458828 0.5043978 -3.885412 -2.045602 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6820 -33575 5600
#> initial value 998.131940
#> iter 2 value 897.063583
#> iter 3 value 887.136399
#> iter 4 value 887.134608
#> iter 5 value 832.713079
#> iter 6 value 829.366513
#> iter 7 value 829.072332
#> iter 8 value 829.069095
#> iter 9 value 829.069081
#> iter 9 value 829.069072
#> iter 9 value 829.069072
#> final value 829.069072
#> converged
#> This is Run number 39
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.1288270 2.123097 0.578827 -11.07690298 1
#> 2 1 -3.10 -5.40 -0.3590513 3.940038 -3.459051 -1.45996202 2
#> 3 1 -14.60 -12.20 1.1853197 -1.194410 -13.414680 -13.39441048 2
#> 4 1 -14.20 -0.55 1.0059849 -1.130828 -13.194015 -1.68082758 2
#> 5 1 -5.40 -3.30 -1.0397888 3.288205 -6.439789 -0.01179513 2
#> 6 1 -4.10 -2.55 1.3144319 2.043665 -2.785568 -0.50633482 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7340 -36525 5625
#> initial value 998.131940
#> iter 2 value 861.836748
#> iter 3 value 860.033088
#> iter 4 value 859.751793
#> iter 5 value 808.961541
#> iter 6 value 798.768162
#> iter 7 value 796.696260
#> iter 8 value 796.638826
#> iter 9 value 796.638642
#> iter 9 value 796.638631
#> iter 9 value 796.638631
#> final value 796.638631
#> converged
#> This is Run number 40
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.0602308 -0.04286488 1.510231 -13.242865 1
#> 2 1 -3.10 -5.40 -0.7350309 -0.57858643 -3.835031 -5.978586 1
#> 3 1 -14.60 -12.20 0.8259237 -0.61664390 -13.774076 -12.816644 2
#> 4 1 -14.20 -0.55 0.1763125 -0.64580687 -14.023688 -1.195807 2
#> 5 1 -5.40 -3.30 -0.1383749 -0.54246787 -5.538375 -3.842468 2
#> 6 1 -4.10 -2.55 -1.2590609 1.41281785 -5.359061 -1.137182 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5660 -34725 6500
#> initial value 998.131940
#> iter 2 value 879.939139
#> iter 3 value 876.938940
#> iter 4 value 872.570489
#> iter 5 value 816.522535
#> iter 6 value 807.273387
#> iter 7 value 805.573748
#> iter 8 value 805.540527
#> iter 9 value 805.540483
#> iter 10 value 805.540465
#> iter 11 value 805.540426
#> iter 12 value 805.540399
#> iter 12 value 805.540399
#> iter 12 value 805.540399
#> final value 805.540399
#> converged
#> This is Run number 41
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.5971686 -0.0900051 -1.147169 -13.2900051 1
#> 2 1 -3.10 -5.40 0.8435273 0.2443101 -2.256473 -5.1556899 1
#> 3 1 -14.60 -12.20 -0.2806119 1.4277655 -14.880612 -10.7722345 2
#> 4 1 -14.20 -0.55 -0.4497592 0.9993572 -14.649759 0.4493572 2
#> 5 1 -5.40 -3.30 -1.2637693 1.0777000 -6.663769 -2.2223000 2
#> 6 1 -4.10 -2.55 1.7881045 1.3910188 -2.311896 -1.1589812 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6840 -35850 6725
#> initial value 998.131940
#> iter 2 value 864.743688
#> iter 3 value 862.887441
#> iter 4 value 862.665327
#> iter 5 value 808.268533
#> iter 6 value 798.255520
#> iter 7 value 796.535853
#> iter 8 value 796.499965
#> iter 9 value 796.499899
#> iter 10 value 796.499871
#> iter 11 value 796.499820
#> iter 12 value 796.499779
#> iter 12 value 796.499779
#> iter 12 value 796.499779
#> final value 796.499779
#> converged
#> This is Run number 42
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.5786297 0.9502352 0.02862967 -12.2497648 1
#> 2 1 -3.10 -5.40 1.5831812 0.8693745 -1.51681880 -4.5306255 1
#> 3 1 -14.60 -12.20 3.8805490 1.5633660 -10.71945104 -10.6366340 2
#> 4 1 -14.20 -0.55 0.4784841 1.2811602 -13.72151592 0.7311602 2
#> 5 1 -5.40 -3.30 0.2023230 -0.1746245 -5.19767698 -3.4746245 2
#> 6 1 -4.10 -2.55 -0.4773904 1.7613269 -4.57739036 -0.7886731 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5200 -35850 6925
#> initial value 998.131940
#> iter 2 value 863.711103
#> iter 3 value 855.620223
#> iter 4 value 845.516666
#> iter 5 value 794.218855
#> iter 6 value 784.560768
#> iter 7 value 782.915906
#> iter 8 value 782.883024
#> iter 9 value 782.883010
#> iter 9 value 782.883003
#> iter 9 value 782.882999
#> final value 782.882999
#> converged
#> This is Run number 43
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.2903718 -0.01899182 -0.2596282 -13.218992 1
#> 2 1 -3.10 -5.40 1.2847837 0.29257514 -1.8152163 -5.107425 1
#> 3 1 -14.60 -12.20 0.1202789 0.25972464 -14.4797211 -11.940275 2
#> 4 1 -14.20 -0.55 0.6586039 0.81701003 -13.5413961 0.267010 2
#> 5 1 -5.40 -3.30 -0.3467488 0.51700360 -5.7467488 -2.782996 2
#> 6 1 -4.10 -2.55 -1.2006524 0.21509695 -5.3006524 -2.334903 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7360 -36625 6600
#> initial value 998.131940
#> iter 2 value 855.113026
#> iter 3 value 852.644027
#> iter 4 value 852.642868
#> iter 5 value 819.237401
#> iter 6 value 795.742695
#> iter 7 value 789.324616
#> iter 8 value 788.816495
#> iter 9 value 788.809893
#> iter 10 value 788.809409
#> iter 10 value 788.809407
#> iter 11 value 788.809252
#> iter 12 value 788.809213
#> iter 12 value 788.809212
#> iter 12 value 788.809207
#> final value 788.809207
#> converged
#> This is Run number 44
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.2375763 1.3362224 1.6875763 -11.8637776 1
#> 2 1 -3.10 -5.40 2.3992194 2.8040849 -0.7007806 -2.5959151 1
#> 3 1 -14.60 -12.20 0.5918640 0.2361572 -14.0081360 -11.9638428 2
#> 4 1 -14.20 -0.55 -0.9069951 -1.2991577 -15.1069951 -1.8491577 2
#> 5 1 -5.40 -3.30 -0.4112167 -0.3071463 -5.8112167 -3.6071463 2
#> 6 1 -4.10 -2.55 -0.5922469 2.2823608 -4.6922469 -0.2676392 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6660 -35500 5875
#> initial value 998.131940
#> iter 2 value 873.967290
#> iter 3 value 872.361213
#> iter 4 value 871.168556
#> iter 5 value 817.243993
#> iter 6 value 807.560423
#> iter 7 value 805.611581
#> iter 8 value 805.564298
#> iter 9 value 805.564174
#> iter 10 value 805.564148
#> iter 11 value 805.564102
#> iter 12 value 805.564063
#> iter 12 value 805.564063
#> iter 12 value 805.564063
#> final value 805.564063
#> converged
#> This is Run number 45
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.44042163 -0.13406200 1.890422 -13.3340620 1
#> 2 1 -3.10 -5.40 1.65572743 1.18148744 -1.444273 -4.2185126 1
#> 3 1 -14.60 -12.20 1.61769692 2.55863551 -12.982303 -9.6413645 2
#> 4 1 -14.20 -0.55 -0.49397490 0.39271394 -14.693975 -0.1572861 2
#> 5 1 -5.40 -3.30 1.79973408 -0.02646449 -3.600266 -3.3264645 2
#> 6 1 -4.10 -2.55 -0.05053943 -0.55346720 -4.150539 -3.1034672 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5920 -37250 6550
#> initial value 998.131940
#> iter 2 value 848.014700
#> iter 3 value 840.013990
#> iter 4 value 832.053518
#> iter 5 value 784.690326
#> iter 6 value 774.421756
#> iter 7 value 772.759254
#> iter 8 value 772.721783
#> iter 9 value 772.721762
#> iter 10 value 772.721745
#> iter 10 value 772.721744
#> iter 10 value 772.721736
#> final value 772.721736
#> converged
#> This is Run number 46
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.2737670 0.5499266 -0.276233 -12.6500734 1
#> 2 1 -3.10 -5.40 -1.0484543 -0.2121670 -4.148454 -5.6121670 1
#> 3 1 -14.60 -12.20 1.6365239 0.6632613 -12.963476 -11.5367387 2
#> 4 1 -14.20 -0.55 -1.1759768 1.3965002 -15.375977 0.8465002 2
#> 5 1 -5.40 -3.30 0.5231508 0.2075821 -4.876849 -3.0924179 2
#> 6 1 -4.10 -2.55 0.1164578 -0.5671421 -3.983542 -3.1171421 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7360 -37300 5425
#> initial value 998.131940
#> iter 2 value 852.626409
#> iter 3 value 849.935070
#> iter 4 value 848.984754
#> iter 5 value 800.889632
#> iter 6 value 790.375687
#> iter 7 value 788.293627
#> iter 8 value 788.232684
#> iter 9 value 788.232503
#> iter 10 value 788.232489
#> iter 11 value 788.232460
#> iter 12 value 788.232420
#> iter 12 value 788.232420
#> iter 12 value 788.232420
#> final value 788.232420
#> converged
#> This is Run number 47
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.6300780 1.56966357 0.08007803 -11.6303364 1
#> 2 1 -3.10 -5.40 -0.1913320 0.23919605 -3.29133200 -5.1608040 1
#> 3 1 -14.60 -12.20 4.2020514 -0.04677445 -10.39794864 -12.2467744 1
#> 4 1 -14.20 -0.55 0.1323049 -0.02702305 -14.06769507 -0.5770231 2
#> 5 1 -5.40 -3.30 0.8463657 -0.43920171 -4.55363433 -3.7392017 2
#> 6 1 -4.10 -2.55 1.0126725 -1.07252224 -3.08732749 -3.6225222 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7260 -37000 5925
#> initial value 998.131940
#> iter 2 value 854.158836
#> iter 3 value 851.567206
#> iter 4 value 851.059739
#> iter 5 value 801.261349
#> iter 6 value 790.787372
#> iter 7 value 788.877314
#> iter 8 value 788.827321
#> iter 9 value 788.827207
#> iter 9 value 788.827201
#> iter 9 value 788.827201
#> final value 788.827201
#> converged
#> This is Run number 48
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.2539028 0.06772222 -0.8039028 -13.132278 1
#> 2 1 -3.10 -5.40 -0.5961863 0.48816791 -3.6961863 -4.911832 1
#> 3 1 -14.60 -12.20 0.7160626 0.51346851 -13.8839374 -11.686531 2
#> 4 1 -14.20 -0.55 -1.4157417 -0.99311614 -15.6157417 -1.543116 2
#> 5 1 -5.40 -3.30 -0.9984778 0.27636498 -6.3984778 -3.023635 2
#> 6 1 -4.10 -2.55 -0.4248569 0.81217026 -4.5248569 -1.737830 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7180 -36925 5375
#> initial value 998.131940
#> iter 2 value 858.072758
#> iter 3 value 855.494011
#> iter 4 value 854.184873
#> iter 5 value 805.132719
#> iter 6 value 794.819313
#> iter 7 value 792.695070
#> iter 8 value 792.633642
#> iter 9 value 792.633451
#> iter 10 value 792.633436
#> iter 11 value 792.633407
#> iter 12 value 792.633370
#> iter 12 value 792.633370
#> iter 12 value 792.633370
#> final value 792.633370
#> converged
#> This is Run number 49
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 4.3889999 -0.22298296 3.8389999 -13.422983 1
#> 2 1 -3.10 -5.40 2.7390048 -0.74260982 -0.3609952 -6.142610 1
#> 3 1 -14.60 -12.20 1.4892839 0.10449874 -13.1107161 -12.095501 2
#> 4 1 -14.20 -0.55 4.4172220 -0.76497796 -9.7827780 -1.314978 2
#> 5 1 -5.40 -3.30 0.8313674 0.56727496 -4.5686326 -2.732725 2
#> 6 1 -4.10 -2.55 -1.1003850 0.08046487 -5.2003850 -2.469535 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6880 -37275 6225
#> initial value 998.131940
#> iter 2 value 849.203593
#> iter 3 value 845.270743
#> iter 4 value 843.495642
#> iter 5 value 794.364982
#> iter 6 value 783.825540
#> iter 7 value 782.053933
#> iter 8 value 782.011697
#> iter 9 value 782.011645
#> iter 10 value 782.011620
#> iter 11 value 782.011574
#> iter 12 value 782.011540
#> iter 12 value 782.011540
#> iter 12 value 782.011540
#> final value 782.011540
#> converged
#> This is Run number 50
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.6848857 -0.71710307 0.1348857 -13.91710307 1
#> 2 1 -3.10 -5.40 1.6522845 0.01985095 -1.4477155 -5.38014905 1
#> 3 1 -14.60 -12.20 1.5942695 -0.70054723 -13.0057305 -12.90054723 2
#> 4 1 -14.20 -0.55 -0.2749450 0.61301487 -14.4749450 0.06301487 2
#> 5 1 -5.40 -3.30 -1.1179694 1.64046619 -6.5179694 -1.65953381 2
#> 6 1 -4.10 -2.55 2.3153471 -1.12760421 -1.7846529 -3.67760421 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7100 -38475 5775
#> initial value 998.131940
#> iter 2 value 834.707319
#> iter 3 value 829.327361
#> iter 4 value 826.121382
#> iter 5 value 781.935358
#> iter 6 value 771.032585
#> iter 7 value 769.269291
#> iter 8 value 769.222283
#> iter 9 value 769.222245
#> iter 10 value 769.222230
#> iter 11 value 769.222202
#> iter 12 value 769.222177
#> iter 12 value 769.222177
#> iter 12 value 769.222177
#> final value 769.222177
#> converged
#> This is Run number 51
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 3.57689198 6.2459850 3.026892 -6.95401501 1
#> 2 1 -3.10 -5.40 -0.03573173 1.8230600 -3.135732 -3.57693998 1
#> 3 1 -14.60 -12.20 -0.29760448 -0.2663611 -14.897604 -12.46636111 2
#> 4 1 -14.20 -0.55 -0.03108330 0.5954091 -14.231083 0.04540907 2
#> 5 1 -5.40 -3.30 -0.83128064 0.1282684 -6.231281 -3.17173155 2
#> 6 1 -4.10 -2.55 1.76226649 1.4020213 -2.337734 -1.14797875 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6460 -35075 6200
#> initial value 998.131940
#> iter 2 value 877.400258
#> iter 3 value 876.117809
#> iter 4 value 874.993758
#> iter 5 value 819.360260
#> iter 6 value 809.852678
#> iter 7 value 808.017948
#> iter 8 value 807.977143
#> iter 9 value 807.977049
#> iter 10 value 807.977029
#> iter 11 value 807.976977
#> iter 12 value 807.976930
#> iter 12 value 807.976930
#> iter 12 value 807.976930
#> final value 807.976930
#> converged
#> This is Run number 52
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.4154121 -0.9393118 -0.9654121 -14.1393118 1
#> 2 1 -3.10 -5.40 -1.0435682 -0.3345817 -4.1435682 -5.7345817 1
#> 3 1 -14.60 -12.20 -0.0839636 3.2662338 -14.6839636 -8.9337662 2
#> 4 1 -14.20 -0.55 -0.7104044 1.5267000 -14.9104044 0.9767000 2
#> 5 1 -5.40 -3.30 1.2597101 -0.8465731 -4.1402899 -4.1465731 1
#> 6 1 -4.10 -2.55 0.4533354 2.4415905 -3.6466646 -0.1084095 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6240 -35150 6175
#> initial value 998.131940
#> iter 2 value 876.748170
#> iter 3 value 874.745235
#> iter 4 value 872.551730
#> iter 5 value 817.455390
#> iter 6 value 807.948841
#> iter 7 value 806.128040
#> iter 8 value 806.088021
#> iter 9 value 806.087940
#> iter 10 value 806.087914
#> iter 11 value 806.087866
#> iter 12 value 806.087834
#> iter 12 value 806.087834
#> iter 12 value 806.087834
#> final value 806.087834
#> converged
#> This is Run number 53
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.3641055 -0.12455895 -0.1858945 -13.3245590 1
#> 2 1 -3.10 -5.40 0.8611351 0.04788928 -2.2388649 -5.3521107 1
#> 3 1 -14.60 -12.20 2.4188890 2.34135071 -12.1811110 -9.8586493 2
#> 4 1 -14.20 -0.55 0.2661438 0.39920648 -13.9338562 -0.1507935 2
#> 5 1 -5.40 -3.30 -0.7013659 -1.17018169 -6.1013659 -4.4701817 2
#> 6 1 -4.10 -2.55 -0.4575937 -0.11791132 -4.5575937 -2.6679113 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7360 -36975 5050
#> initial value 998.131940
#> iter 2 value 858.766285
#> iter 3 value 856.505303
#> iter 4 value 855.406027
#> iter 5 value 806.908035
#> iter 6 value 796.656528
#> iter 7 value 794.357745
#> iter 8 value 794.286839
#> iter 9 value 794.286568
#> iter 9 value 794.286559
#> iter 9 value 794.286559
#> final value 794.286559
#> converged
#> This is Run number 54
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 5.8288162 1.10939934 5.278816 -12.0906007 1
#> 2 1 -3.10 -5.40 0.8919155 1.35745723 -2.208084 -4.0425428 1
#> 3 1 -14.60 -12.20 0.5531039 -0.14536215 -14.046896 -12.3453621 2
#> 4 1 -14.20 -0.55 -0.6094792 0.66251262 -14.809479 0.1125126 2
#> 5 1 -5.40 -3.30 2.3909652 1.07593305 -3.009035 -2.2240670 2
#> 6 1 -4.10 -2.55 0.9300900 -0.05004199 -3.169910 -2.6000420 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7000 -37000 6650
#> initial value 998.131940
#> iter 2 value 850.310502
#> iter 3 value 846.975834
#> iter 4 value 846.414691
#> iter 5 value 795.552068
#> iter 6 value 785.057484
#> iter 7 value 783.361517
#> iter 8 value 783.325248
#> iter 9 value 783.325192
#> iter 10 value 783.325146
#> iter 11 value 783.325119
#> iter 12 value 783.325075
#> iter 12 value 783.325075
#> iter 12 value 783.325075
#> final value 783.325075
#> converged
#> This is Run number 55
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -1.7125633 -0.5978205 -2.262563 -13.7978205 1
#> 2 1 -3.10 -5.40 1.9987461 -0.1016176 -1.101254 -5.5016176 1
#> 3 1 -14.60 -12.20 2.3013537 -1.0250485 -12.298646 -13.2250485 1
#> 4 1 -14.20 -0.55 0.8753168 0.2105602 -13.324683 -0.3394398 2
#> 5 1 -5.40 -3.30 -0.1944710 -1.0464553 -5.594471 -4.3464553 2
#> 6 1 -4.10 -2.55 2.3245014 3.8866693 -1.775499 1.3366693 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7160 -35925 5275
#> initial value 998.131940
#> iter 2 value 871.356504
#> iter 3 value 870.026344
#> iter 4 value 869.430263
#> iter 5 value 817.472846
#> iter 6 value 807.695637
#> iter 7 value 805.459436
#> iter 8 value 805.396891
#> iter 9 value 805.396660
#> iter 10 value 805.396643
#> iter 11 value 805.396608
#> iter 12 value 805.396561
#> iter 12 value 805.396561
#> iter 12 value 805.396561
#> final value 805.396561
#> converged
#> This is Run number 56
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.1664080 0.4530496 -0.3835920 -12.7469504 1
#> 2 1 -3.10 -5.40 3.7673337 1.6311263 0.6673337 -3.7688737 1
#> 3 1 -14.60 -12.20 -0.5232585 -0.3995885 -15.1232585 -12.5995885 2
#> 4 1 -14.20 -0.55 -0.6599525 1.0199003 -14.8599525 0.4699003 2
#> 5 1 -5.40 -3.30 -0.9773258 3.1994619 -6.3773258 -0.1005381 2
#> 6 1 -4.10 -2.55 1.0627373 0.2833656 -3.0372627 -2.2666344 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6900 -36400 5600
#> initial value 998.131940
#> iter 2 value 864.024170
#> iter 3 value 861.553426
#> iter 4 value 859.985296
#> iter 5 value 809.133649
#> iter 6 value 799.041254
#> iter 7 value 797.000537
#> iter 8 value 796.945799
#> iter 9 value 796.945648
#> iter 10 value 796.945627
#> iter 11 value 796.945592
#> iter 12 value 796.945558
#> iter 12 value 796.945558
#> iter 12 value 796.945558
#> final value 796.945558
#> converged
#> This is Run number 57
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.87461357 0.4559739 0.3246136 -12.7440261 1
#> 2 1 -3.10 -5.40 1.27989564 1.0181819 -1.8201044 -4.3818181 1
#> 3 1 -14.60 -12.20 1.73271499 -0.2148022 -12.8672850 -12.4148022 2
#> 4 1 -14.20 -0.55 0.20883433 0.3358096 -13.9911657 -0.2141904 2
#> 5 1 -5.40 -3.30 3.29456437 1.7528611 -2.1054356 -1.5471389 2
#> 6 1 -4.10 -2.55 0.04918419 -0.9003145 -4.0508158 -3.4503145 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6900 -35200 6225
#> initial value 998.131940
#> iter 2 value 875.455855
#> iter 3 value 874.643664
#> iter 4 value 874.516223
#> iter 5 value 819.116137
#> iter 6 value 809.509320
#> iter 7 value 807.655408
#> iter 8 value 807.612717
#> iter 9 value 807.612601
#> iter 10 value 807.612565
#> iter 11 value 807.612517
#> iter 12 value 807.612478
#> iter 12 value 807.612478
#> iter 12 value 807.612478
#> final value 807.612478
#> converged
#> This is Run number 58
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.15926646 0.6281227 0.6092665 -12.5718773 1
#> 2 1 -3.10 -5.40 0.07699589 0.2286272 -3.0230041 -5.1713728 1
#> 3 1 -14.60 -12.20 2.01313884 -0.3366699 -12.5868612 -12.5366699 2
#> 4 1 -14.20 -0.55 0.91913810 -0.2840501 -13.2808619 -0.8340501 2
#> 5 1 -5.40 -3.30 -0.04272691 0.5890152 -5.4427269 -2.7109848 2
#> 6 1 -4.10 -2.55 0.42215462 0.1747527 -3.6778454 -2.3752473 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7000 -36000 5175
#> initial value 998.131940
#> iter 2 value 871.064688
#> iter 3 value 869.299270
#> iter 4 value 867.996016
#> iter 5 value 816.578208
#> iter 6 value 806.797234
#> iter 7 value 804.545625
#> iter 8 value 804.482354
#> iter 9 value 804.482128
#> iter 10 value 804.482113
#> iter 11 value 804.482084
#> iter 12 value 804.482046
#> iter 12 value 804.482046
#> iter 12 value 804.482046
#> final value 804.482046
#> converged
#> This is Run number 59
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 4.1462113 4.23903553 3.596211 -8.9609645 1
#> 2 1 -3.10 -5.40 1.7416780 -0.41273359 -1.358322 -5.8127336 1
#> 3 1 -14.60 -12.20 1.0393375 0.64389394 -13.560663 -11.5561061 2
#> 4 1 -14.20 -0.55 -0.5483619 0.11878525 -14.748362 -0.4312148 2
#> 5 1 -5.40 -3.30 0.3761423 -0.39769563 -5.023858 -3.6976956 2
#> 6 1 -4.10 -2.55 0.9891929 -0.07118942 -3.110807 -2.6211894 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6420 -35150 4975
#> initial value 998.131940
#> iter 2 value 882.688804
#> iter 3 value 880.307277
#> iter 4 value 876.895968
#> iter 5 value 824.348310
#> iter 6 value 815.098853
#> iter 7 value 812.851323
#> iter 8 value 812.792574
#> iter 9 value 812.792383
#> iter 9 value 812.792378
#> iter 9 value 812.792378
#> final value 812.792378
#> converged
#> This is Run number 60
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.20595812 -0.8429036 0.6559581 -14.042904 1
#> 2 1 -3.10 -5.40 -0.43248878 0.8501238 -3.5324888 -4.549876 1
#> 3 1 -14.60 -12.20 2.74286261 0.1811496 -11.8571374 -12.018850 1
#> 4 1 -14.20 -0.55 0.90853949 0.3793970 -13.2914605 -0.170603 2
#> 5 1 -5.40 -3.30 -0.03072660 0.1016667 -5.4307266 -3.198333 2
#> 6 1 -4.10 -2.55 -0.09063984 -1.0531822 -4.1906398 -3.603182 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7640 -38500 5800
#> initial value 998.131940
#> iter 2 value 833.584716
#> iter 3 value 829.690277
#> iter 4 value 829.021469
#> iter 5 value 784.113162
#> iter 6 value 773.072376
#> iter 7 value 771.289213
#> iter 8 value 771.241556
#> iter 9 value 771.241497
#> iter 10 value 771.241474
#> iter 11 value 771.241435
#> iter 12 value 771.241398
#> iter 12 value 771.241398
#> iter 12 value 771.241398
#> final value 771.241398
#> converged
#> This is Run number 61
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.5419113 0.11439873 -0.0080887 -13.085601 1
#> 2 1 -3.10 -5.40 1.0956233 2.49124902 -2.0043767 -2.908751 1
#> 3 1 -14.60 -12.20 1.4977985 -1.24502531 -13.1022015 -13.445025 1
#> 4 1 -14.20 -0.55 0.6427194 2.05607883 -13.5572806 1.506079 2
#> 5 1 -5.40 -3.30 0.4762617 -0.09217469 -4.9237383 -3.392175 2
#> 6 1 -4.10 -2.55 1.5894364 -0.37330100 -2.5105636 -2.923301 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6760 -37100 6725
#> initial value 998.131940
#> iter 2 value 848.730091
#> iter 3 value 844.678835
#> iter 4 value 843.304543
#> iter 5 value 792.761646
#> iter 6 value 782.295202
#> iter 7 value 780.622544
#> iter 8 value 780.587632
#> iter 9 value 780.587588
#> iter 10 value 780.587571
#> iter 11 value 780.587513
#> iter 12 value 780.587472
#> iter 12 value 780.587472
#> iter 12 value 780.587472
#> final value 780.587472
#> converged
#> This is Run number 62
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.9139384 -2.15732736 2.363938 -15.3573274 1
#> 2 1 -3.10 -5.40 0.8526767 -0.88428581 -2.247323 -6.2842858 1
#> 3 1 -14.60 -12.20 1.4023388 -0.70876568 -13.197661 -12.9087657 2
#> 4 1 -14.20 -0.55 1.8296629 1.46862685 -12.370337 0.9186269 2
#> 5 1 -5.40 -3.30 -1.0892800 -1.77985339 -6.489280 -5.0798534 2
#> 6 1 -4.10 -2.55 0.4477539 0.01667347 -3.652246 -2.5333265 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6780 -38075 7100
#> initial value 998.131940
#> iter 2 value 832.971080
#> iter 3 value 826.885085
#> iter 4 value 824.988393
#> iter 5 value 777.116743
#> iter 6 value 766.477676
#> iter 7 value 764.913249
#> iter 8 value 764.883386
#> iter 9 value 764.883265
#> iter 10 value 764.883204
#> iter 11 value 764.883160
#> iter 11 value 764.883150
#> iter 11 value 764.883150
#> final value 764.883150
#> converged
#> This is Run number 63
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.7372771 3.5585879 0.1872771 -9.64141205 1
#> 2 1 -3.10 -5.40 0.8746554 -0.2288145 -2.2253446 -5.62881451 1
#> 3 1 -14.60 -12.20 -1.4710510 6.8631531 -16.0710510 -5.33684694 2
#> 4 1 -14.20 -0.55 2.6052865 0.5216402 -11.5947135 -0.02835976 2
#> 5 1 -5.40 -3.30 -1.2243449 0.9170877 -6.6243449 -2.38291230 2
#> 6 1 -4.10 -2.55 2.9234830 1.0612305 -1.1765170 -1.48876950 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5680 -35925 7425
#> initial value 998.131940
#> iter 2 value 859.824114
#> iter 3 value 854.628633
#> iter 4 value 850.130175
#> iter 5 value 795.795886
#> iter 6 value 786.022296
#> iter 7 value 784.415994
#> iter 8 value 784.387619
#> iter 9 value 784.387590
#> iter 9 value 784.387579
#> iter 9 value 784.387579
#> final value 784.387579
#> converged
#> This is Run number 64
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.52212276 0.7078553 -0.02787724 -12.492145 1
#> 2 1 -3.10 -5.40 0.09584287 1.4064986 -3.00415713 -3.993501 1
#> 3 1 -14.60 -12.20 1.03948289 0.3349791 -13.56051711 -11.865021 2
#> 4 1 -14.20 -0.55 0.44355666 -0.1102650 -13.75644334 -0.660265 2
#> 5 1 -5.40 -3.30 1.99598889 1.8249909 -3.40401111 -1.475009 2
#> 6 1 -4.10 -2.55 0.62703952 1.0168970 -3.47296048 -1.533103 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7320 -37650 6775
#> initial value 998.131940
#> iter 2 value 840.414655
#> iter 3 value 836.456611
#> iter 4 value 836.286390
#> iter 5 value 787.291582
#> iter 6 value 776.556132
#> iter 7 value 774.940335
#> iter 8 value 774.908057
#> iter 9 value 774.907996
#> iter 10 value 774.907983
#> iter 11 value 774.907925
#> iter 12 value 774.907867
#> iter 12 value 774.907867
#> iter 12 value 774.907867
#> final value 774.907867
#> converged
#> This is Run number 65
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.555526450 0.70935307 0.00552645 -12.490647 1
#> 2 1 -3.10 -5.40 0.677317776 0.30674618 -2.42268222 -5.093254 1
#> 3 1 -14.60 -12.20 -0.186692276 -0.46753686 -14.78669228 -12.667537 2
#> 4 1 -14.20 -0.55 -0.536453057 4.40439089 -14.73645306 3.854391 2
#> 5 1 -5.40 -3.30 2.014109335 0.70523606 -3.38589066 -2.594764 2
#> 6 1 -4.10 -2.55 0.004830214 0.04225053 -4.09516979 -2.507749 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6660 -36725 6275
#> initial value 998.131940
#> iter 2 value 856.380557
#> iter 3 value 852.790542
#> iter 4 value 850.744315
#> iter 5 value 799.938549
#> iter 6 value 789.642032
#> iter 7 value 787.854440
#> iter 8 value 787.812804
#> iter 9 value 787.812745
#> iter 10 value 787.812720
#> iter 11 value 787.812674
#> iter 12 value 787.812641
#> iter 12 value 787.812641
#> iter 12 value 787.812641
#> final value 787.812641
#> converged
#> This is Run number 66
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.00815106 0.1760391 -0.5581511 -13.0239609 1
#> 2 1 -3.10 -5.40 -1.35246494 0.3157016 -4.4524649 -5.0842984 1
#> 3 1 -14.60 -12.20 -0.07906295 0.5126871 -14.6790630 -11.6873129 2
#> 4 1 -14.20 -0.55 3.09785307 1.0645618 -11.1021469 0.5145618 2
#> 5 1 -5.40 -3.30 -1.13508223 -1.2326382 -6.5350822 -4.5326382 2
#> 6 1 -4.10 -2.55 0.57028920 0.7032660 -3.5297108 -1.8467340 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6380 -34900 5850
#> initial value 998.131940
#> iter 2 value 881.374096
#> iter 3 value 880.013139
#> iter 4 value 878.299595
#> iter 5 value 822.960650
#> iter 6 value 813.624941
#> iter 7 value 811.707917
#> iter 8 value 811.663869
#> iter 9 value 811.663758
#> iter 10 value 811.663728
#> iter 11 value 811.663682
#> iter 12 value 811.663653
#> iter 12 value 811.663653
#> iter 12 value 811.663653
#> final value 811.663653
#> converged
#> This is Run number 67
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.3713217 0.1636658 1.8213217 -13.0363342 1
#> 2 1 -3.10 -5.40 2.1652965 -1.5301550 -0.9347035 -6.9301550 1
#> 3 1 -14.60 -12.20 0.5132486 0.6827706 -14.0867514 -11.5172294 2
#> 4 1 -14.20 -0.55 1.0991903 0.7464201 -13.1008097 0.1964201 2
#> 5 1 -5.40 -3.30 -0.6811577 -0.2405168 -6.0811577 -3.5405168 2
#> 6 1 -4.10 -2.55 1.6933582 2.9008811 -2.4066418 0.3508811 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6820 -36200 6200
#> initial value 998.131940
#> iter 2 value 863.431541
#> iter 3 value 861.137029
#> iter 4 value 860.229728
#> iter 5 value 807.700596
#> iter 6 value 797.597579
#> iter 7 value 795.750441
#> iter 8 value 795.706577
#> iter 9 value 795.706486
#> iter 9 value 795.706480
#> iter 9 value 795.706480
#> final value 795.706480
#> converged
#> This is Run number 68
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.9171304 0.9422976 0.3671304 -12.257702 1
#> 2 1 -3.10 -5.40 -0.1683480 2.5036243 -3.2683480 -2.896376 2
#> 3 1 -14.60 -12.20 0.5176264 1.5245893 -14.0823736 -10.675411 2
#> 4 1 -14.20 -0.55 0.8280348 -0.7116315 -13.3719652 -1.261632 2
#> 5 1 -5.40 -3.30 -0.7010016 -1.0764084 -6.1010016 -4.376408 2
#> 6 1 -4.10 -2.55 0.5696001 0.8923430 -3.5303999 -1.657657 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6900 -36600 5750
#> initial value 998.131940
#> iter 2 value 860.680423
#> iter 3 value 857.925725
#> iter 4 value 856.342827
#> iter 5 value 805.847498
#> iter 6 value 795.630827
#> iter 7 value 793.658271
#> iter 8 value 793.606400
#> iter 9 value 793.606274
#> iter 10 value 793.606253
#> iter 11 value 793.606216
#> iter 12 value 793.606180
#> iter 12 value 793.606180
#> iter 12 value 793.606180
#> final value 793.606180
#> converged
#> This is Run number 69
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.7871790 -0.3351889 0.237179 -13.5351889 1
#> 2 1 -3.10 -5.40 0.4127323 -0.8865635 -2.687268 -6.2865635 1
#> 3 1 -14.60 -12.20 -0.1620805 -1.1695105 -14.762080 -13.3695105 2
#> 4 1 -14.20 -0.55 -1.9598202 0.1269472 -16.159820 -0.4230528 2
#> 5 1 -5.40 -3.30 1.6375937 0.1371785 -3.762406 -3.1628215 2
#> 6 1 -4.10 -2.55 -1.4715882 -1.2228203 -5.571588 -3.7728203 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6840 -37875 5975
#> initial value 998.131940
#> iter 2 value 842.374326
#> iter 3 value 837.175906
#> iter 4 value 833.792511
#> iter 5 value 787.460786
#> iter 6 value 776.763863
#> iter 7 value 774.992202
#> iter 8 value 774.947288
#> iter 9 value 774.947247
#> iter 10 value 774.947229
#> iter 11 value 774.947197
#> iter 12 value 774.947171
#> iter 12 value 774.947171
#> iter 12 value 774.947171
#> final value 774.947171
#> converged
#> This is Run number 70
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.2424477 -0.17622219 -0.7924477 -13.3762222 1
#> 2 1 -3.10 -5.40 0.5972408 1.49510342 -2.5027592 -3.9048966 1
#> 3 1 -14.60 -12.20 0.4533154 -0.03868423 -14.1466846 -12.2386842 2
#> 4 1 -14.20 -0.55 -0.9982893 -0.28073384 -15.1982893 -0.8307338 2
#> 5 1 -5.40 -3.30 0.7920413 -0.68096510 -4.6079587 -3.9809651 2
#> 6 1 -4.10 -2.55 0.3880924 1.63201439 -3.7119076 -0.9179856 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6400 -36750 7175
#> initial value 998.131940
#> iter 2 value 850.777886
#> iter 3 value 846.291342
#> iter 4 value 844.364725
#> iter 5 value 792.157329
#> iter 6 value 781.908793
#> iter 7 value 780.289095
#> iter 8 value 780.258948
#> iter 9 value 780.258903
#> iter 10 value 780.258878
#> iter 11 value 780.258826
#> iter 12 value 780.258794
#> iter 12 value 780.258794
#> iter 12 value 780.258794
#> final value 780.258794
#> converged
#> This is Run number 71
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.19084771 1.13443707 1.640848 -12.06556293 1
#> 2 1 -3.10 -5.40 1.32307589 1.41940661 -1.776924 -3.98059339 1
#> 3 1 -14.60 -12.20 0.01993147 0.11092971 -14.580069 -12.08907029 2
#> 4 1 -14.20 -0.55 -0.54061510 0.60119558 -14.740615 0.05119558 2
#> 5 1 -5.40 -3.30 2.88295296 0.09000784 -2.517047 -3.20999216 1
#> 6 1 -4.10 -2.55 0.20654238 1.79578034 -3.893458 -0.75421966 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6900 -37850 5550
#> initial value 998.131940
#> iter 2 value 844.907264
#> iter 3 value 839.893606
#> iter 4 value 835.983063
#> iter 5 value 790.433869
#> iter 6 value 779.765795
#> iter 7 value 777.857197
#> iter 8 value 777.803455
#> iter 9 value 777.803363
#> iter 9 value 777.803351
#> iter 9 value 777.803351
#> final value 777.803351
#> converged
#> This is Run number 72
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.5803215 -0.02311054 2.030322 -13.223111 1
#> 2 1 -3.10 -5.40 -0.1729393 1.02227524 -3.272939 -4.377725 1
#> 3 1 -14.60 -12.20 0.5193857 -0.11709595 -14.080614 -12.317096 2
#> 4 1 -14.20 -0.55 0.3033881 1.88141669 -13.896612 1.331417 2
#> 5 1 -5.40 -3.30 -0.5558121 0.22091701 -5.955812 -3.079083 2
#> 6 1 -4.10 -2.55 0.6662322 3.72649579 -3.433768 1.176496 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5760 -34850 7500
#> initial value 998.131940
#> iter 2 value 872.339430
#> iter 3 value 870.162178
#> iter 4 value 868.036495
#> iter 5 value 809.631511
#> iter 6 value 800.238197
#> iter 7 value 798.647632
#> iter 8 value 798.621647
#> iter 9 value 798.621623
#> iter 10 value 798.621607
#> iter 11 value 798.621559
#> iter 12 value 798.621519
#> iter 12 value 798.621519
#> iter 12 value 798.621519
#> final value 798.621519
#> converged
#> This is Run number 73
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.08003648 -1.1342280 -0.6300365 -14.3342280 1
#> 2 1 -3.10 -5.40 1.34404849 -0.5162046 -1.7559515 -5.9162046 1
#> 3 1 -14.60 -12.20 1.36242488 1.1450045 -13.2375751 -11.0549955 2
#> 4 1 -14.20 -0.55 -1.22126230 0.2398502 -15.4212623 -0.3101498 2
#> 5 1 -5.40 -3.30 -0.72537236 3.0684756 -6.1253724 -0.2315244 2
#> 6 1 -4.10 -2.55 1.24535672 0.3746493 -2.8546433 -2.1753507 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6360 -36175 6600
#> initial value 998.131940
#> iter 2 value 861.731030
#> iter 3 value 858.306923
#> iter 4 value 856.022179
#> iter 5 value 803.120636
#> iter 6 value 793.082269
#> iter 7 value 791.357190
#> iter 8 value 791.320678
#> iter 9 value 791.320632
#> iter 10 value 791.320606
#> iter 11 value 791.320556
#> iter 12 value 791.320523
#> iter 12 value 791.320523
#> iter 12 value 791.320523
#> final value 791.320523
#> converged
#> This is Run number 74
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.3670278 1.21874292 -0.1829722 -11.9812571 1
#> 2 1 -3.10 -5.40 1.2219771 1.53410005 -1.8780229 -3.8659000 1
#> 3 1 -14.60 -12.20 2.3629164 0.32123150 -12.2370836 -11.8787685 2
#> 4 1 -14.20 -0.55 1.5101714 -0.43641689 -12.6898286 -0.9864169 2
#> 5 1 -5.40 -3.30 -0.3280363 0.08379687 -5.7280363 -3.2162031 2
#> 6 1 -4.10 -2.55 0.6577881 0.87308810 -3.4422119 -1.6769119 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6780 -37575 6625
#> initial value 998.131940
#> iter 2 value 842.876673
#> iter 3 value 838.010847
#> iter 4 value 836.003402
#> iter 5 value 787.268342
#> iter 6 value 776.665963
#> iter 7 value 775.007555
#> iter 8 value 774.972042
#> iter 9 value 774.972004
#> iter 10 value 774.971980
#> iter 11 value 774.971926
#> iter 12 value 774.971892
#> iter 12 value 774.971892
#> iter 12 value 774.971892
#> final value 774.971892
#> converged
#> This is Run number 75
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.09634736 3.1187256 -0.4536526 -10.0812744 1
#> 2 1 -3.10 -5.40 1.52204084 3.1867460 -1.5779592 -2.2132540 1
#> 3 1 -14.60 -12.20 -0.28918310 0.1987137 -14.8891831 -12.0012863 2
#> 4 1 -14.20 -0.55 0.74360324 0.3270406 -13.4563968 -0.2229594 2
#> 5 1 -5.40 -3.30 0.81764730 0.1156045 -4.5823527 -3.1843955 2
#> 6 1 -4.10 -2.55 -0.32318087 0.7763637 -4.4231809 -1.7736363 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6960 -39500 6725
#> initial value 998.131940
#> iter 2 value 814.172480
#> iter 3 value 805.850459
#> iter 4 value 801.986424
#> iter 5 value 759.989962
#> iter 6 value 749.225126
#> iter 7 value 747.726049
#> iter 8 value 747.692119
#> iter 9 value 747.691810
#> iter 10 value 747.691770
#> iter 10 value 747.691764
#> iter 10 value 747.691758
#> final value 747.691758
#> converged
#> This is Run number 76
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 4.66261377 -0.140416358 4.112614 -13.3404164 1
#> 2 1 -3.10 -5.40 0.37423822 0.332618075 -2.725762 -5.0673819 1
#> 3 1 -14.60 -12.20 -0.07026226 0.179211480 -14.670262 -12.0207885 2
#> 4 1 -14.20 -0.55 0.10156580 0.327088411 -14.098434 -0.2229116 2
#> 5 1 -5.40 -3.30 -0.30987942 0.001117748 -5.709879 -3.2988823 2
#> 6 1 -4.10 -2.55 3.09106534 -0.392998886 -1.008935 -2.9429989 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6340 -35875 6625
#> initial value 998.131940
#> iter 2 value 865.351334
#> iter 3 value 862.462452
#> iter 4 value 860.518874
#> iter 5 value 806.596823
#> iter 6 value 796.683111
#> iter 7 value 794.956216
#> iter 8 value 794.920147
#> iter 9 value 794.920096
#> iter 10 value 794.920068
#> iter 11 value 794.920016
#> iter 12 value 794.919983
#> iter 12 value 794.919983
#> iter 12 value 794.919983
#> final value 794.919983
#> converged
#> This is Run number 77
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.2232675 -1.48029026 0.6732675 -14.680290 1
#> 2 1 -3.10 -5.40 -0.1463083 0.09360380 -3.2463083 -5.306396 1
#> 3 1 -14.60 -12.20 -0.6224007 -0.23664342 -15.2224007 -12.436643 2
#> 4 1 -14.20 -0.55 1.5989813 1.91157672 -12.6010187 1.361577 2
#> 5 1 -5.40 -3.30 1.2364311 -0.05705427 -4.1635689 -3.357054 2
#> 6 1 -4.10 -2.55 -1.0080657 -0.60132903 -5.1080657 -3.151329 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6980 -37375 6400
#> initial value 998.131940
#> iter 2 value 846.768100
#> iter 3 value 842.887478
#> iter 4 value 841.675935
#> iter 5 value 792.446547
#> iter 6 value 781.843249
#> iter 7 value 780.118010
#> iter 8 value 780.078626
#> iter 9 value 780.078602
#> iter 10 value 780.078584
#> iter 11 value 780.078527
#> iter 12 value 780.078464
#> iter 12 value 780.078464
#> iter 12 value 780.078464
#> final value 780.078464
#> converged
#> This is Run number 78
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.23524554 2.1115576 -0.7852455 -11.088442 1
#> 2 1 -3.10 -5.40 0.78640339 2.5098191 -2.3135966 -2.890181 1
#> 3 1 -14.60 -12.20 0.03445763 0.2951223 -14.5655424 -11.904878 2
#> 4 1 -14.20 -0.55 -0.18722015 -0.4711959 -14.3872202 -1.021196 2
#> 5 1 -5.40 -3.30 0.64555430 -1.1662123 -4.7544457 -4.466212 2
#> 6 1 -4.10 -2.55 -0.23018314 -0.6557187 -4.3301831 -3.205719 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6440 -35100 6500
#> initial value 998.131940
#> iter 2 value 875.417076
#> iter 3 value 874.134273
#> iter 4 value 873.245959
#> iter 5 value 817.122574
#> iter 6 value 807.553487
#> iter 7 value 805.790869
#> iter 8 value 805.753679
#> iter 9 value 805.753602
#> iter 10 value 805.753570
#> iter 11 value 805.753517
#> iter 12 value 805.753480
#> iter 12 value 805.753480
#> iter 12 value 805.753480
#> final value 805.753480
#> converged
#> This is Run number 79
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.4388143 2.7735895 -0.1111857 -10.4264105 1
#> 2 1 -3.10 -5.40 0.8303081 -0.8307853 -2.2696919 -6.2307853 1
#> 3 1 -14.60 -12.20 -1.0927741 -0.2014105 -15.6927741 -12.4014105 2
#> 4 1 -14.20 -0.55 2.1756121 1.2297422 -12.0243879 0.6797422 2
#> 5 1 -5.40 -3.30 -1.1431203 -0.6265264 -6.5431203 -3.9265264 2
#> 6 1 -4.10 -2.55 -0.5495722 -0.8059583 -4.6495722 -3.3559583 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6600 -35600 5825
#> initial value 998.131940
#> iter 2 value 873.056836
#> iter 3 value 871.128962
#> iter 4 value 869.519284
#> iter 5 value 816.064444
#> iter 6 value 806.348682
#> iter 7 value 804.392195
#> iter 8 value 804.344386
#> iter 9 value 804.344265
#> iter 10 value 804.344239
#> iter 11 value 804.344195
#> iter 12 value 804.344162
#> iter 12 value 804.344162
#> iter 12 value 804.344162
#> final value 804.344162
#> converged
#> This is Run number 80
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 4.6593869 -1.4349352 4.109387 -14.6349352 1
#> 2 1 -3.10 -5.40 1.0124723 0.8554177 -2.087528 -4.5445823 1
#> 3 1 -14.60 -12.20 0.9371386 2.1880602 -13.662861 -10.0119398 2
#> 4 1 -14.20 -0.55 -0.8820371 -0.1461331 -15.082037 -0.6961331 2
#> 5 1 -5.40 -3.30 0.2815413 0.9416536 -5.118459 -2.3583464 2
#> 6 1 -4.10 -2.55 0.2577118 0.1069283 -3.842288 -2.4430717 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6940 -37525 6400
#> initial value 998.131940
#> iter 2 value 844.758620
#> iter 3 value 840.514553
#> iter 4 value 838.972799
#> iter 5 value 790.292470
#> iter 6 value 779.655116
#> iter 7 value 777.944013
#> iter 8 value 777.905059
#> iter 9 value 777.905011
#> iter 10 value 777.904988
#> iter 11 value 777.904951
#> iter 12 value 777.904906
#> iter 12 value 777.904906
#> iter 12 value 777.904906
#> final value 777.904906
#> converged
#> This is Run number 81
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.3994233 0.3748806 -0.1505767 -12.8251194 1
#> 2 1 -3.10 -5.40 -0.5965326 1.0316359 -3.6965326 -4.3683641 1
#> 3 1 -14.60 -12.20 1.3168948 1.8693030 -13.2831052 -10.3306970 2
#> 4 1 -14.20 -0.55 1.2762732 1.1563737 -12.9237268 0.6063737 2
#> 5 1 -5.40 -3.30 -0.9367026 1.2181986 -6.3367026 -2.0818014 2
#> 6 1 -4.10 -2.55 1.4158075 0.2764117 -2.6841925 -2.2735883 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6440 -37350 5500
#> initial value 998.131940
#> iter 2 value 852.281134
#> iter 3 value 846.114262
#> iter 4 value 839.517634
#> iter 5 value 793.648675
#> iter 6 value 783.256905
#> iter 7 value 781.307678
#> iter 8 value 781.252734
#> iter 9 value 781.252620
#> iter 9 value 781.252616
#> iter 9 value 781.252616
#> final value 781.252616
#> converged
#> This is Run number 82
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.1760983 1.4635329 -0.3739017 -11.7364671 1
#> 2 1 -3.10 -5.40 0.9951825 0.6558669 -2.1048175 -4.7441331 1
#> 3 1 -14.60 -12.20 0.1368179 -0.8199533 -14.4631821 -13.0199533 2
#> 4 1 -14.20 -0.55 3.2977374 1.4209508 -10.9022626 0.8709508 2
#> 5 1 -5.40 -3.30 2.5033172 -0.1466480 -2.8966828 -3.4466480 1
#> 6 1 -4.10 -2.55 -0.4820030 -0.3223504 -4.5820030 -2.8723504 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7240 -35875 5775
#> initial value 998.131940
#> iter 2 value 869.366693
#> iter 3 value 868.138972
#> iter 4 value 868.033957
#> iter 5 value 815.167320
#> iter 6 value 805.304024
#> iter 7 value 803.280486
#> iter 8 value 803.227593
#> iter 9 value 803.227421
#> iter 9 value 803.227413
#> iter 9 value 803.227413
#> final value 803.227413
#> converged
#> This is Run number 83
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.740467694 -0.5495086 0.1904677 -13.749509 1
#> 2 1 -3.10 -5.40 -0.863173591 -1.0158537 -3.9631736 -6.415854 1
#> 3 1 -14.60 -12.20 0.303034073 0.6273732 -14.2969659 -11.572627 2
#> 4 1 -14.20 -0.55 0.588189793 5.0890859 -13.6118102 4.539086 2
#> 5 1 -5.40 -3.30 0.638589872 0.4839735 -4.7614101 -2.816027 2
#> 6 1 -4.10 -2.55 -0.006577028 -1.5159665 -4.1065770 -4.065966 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6740 -37600 6450
#> initial value 998.131940
#> iter 2 value 843.590038
#> iter 3 value 838.577070
#> iter 4 value 836.011028
#> iter 5 value 787.794984
#> iter 6 value 777.192636
#> iter 7 value 775.505704
#> iter 8 value 775.467853
#> iter 9 value 775.467805
#> iter 10 value 775.467773
#> iter 11 value 775.467749
#> iter 12 value 775.467718
#> iter 12 value 775.467718
#> iter 12 value 775.467718
#> final value 775.467718
#> converged
#> This is Run number 84
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.5333819 -0.6170075 -0.01661809 -13.8170075 1
#> 2 1 -3.10 -5.40 0.1157722 0.2717886 -2.98422783 -5.1282114 1
#> 3 1 -14.60 -12.20 0.1032979 0.1649664 -14.49670208 -12.0350336 2
#> 4 1 -14.20 -0.55 1.7446775 0.2004144 -12.45532255 -0.3495856 2
#> 5 1 -5.40 -3.30 -0.1261805 0.3876319 -5.52618047 -2.9123681 2
#> 6 1 -4.10 -2.55 0.6622697 -1.2293223 -3.43773032 -3.7793223 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6720 -36900 5650
#> initial value 998.131940
#> iter 2 value 857.409526
#> iter 3 value 853.535981
#> iter 4 value 850.391190
#> iter 5 value 801.487471
#> iter 6 value 791.188032
#> iter 7 value 789.223597
#> iter 8 value 789.170966
#> iter 9 value 789.170852
#> iter 10 value 789.170835
#> iter 11 value 789.170809
#> iter 12 value 789.170784
#> iter 12 value 789.170784
#> iter 12 value 789.170784
#> final value 789.170784
#> converged
#> This is Run number 85
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.8624844 1.47679323 2.312484 -11.7232068 1
#> 2 1 -3.10 -5.40 1.4035362 -0.26640310 -1.696464 -5.6664031 1
#> 3 1 -14.60 -12.20 1.8433913 -0.64777737 -12.756609 -12.8477774 1
#> 4 1 -14.20 -0.55 -0.8668889 0.72666606 -15.066889 0.1766661 2
#> 5 1 -5.40 -3.30 -0.1880064 -0.03667056 -5.588006 -3.3366706 2
#> 6 1 -4.10 -2.55 -1.2807857 -0.23580759 -5.380786 -2.7858076 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7020 -37825 5100
#> initial value 998.131940
#> iter 2 value 847.355546
#> iter 3 value 842.685196
#> iter 4 value 838.575142
#> iter 5 value 793.726220
#> iter 6 value 783.127105
#> iter 7 value 781.021670
#> iter 8 value 780.955922
#> iter 9 value 780.955726
#> iter 9 value 780.955722
#> iter 9 value 780.955722
#> final value 780.955722
#> converged
#> This is Run number 86
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.08867906 1.77491518 -0.4613209 -11.4250848 1
#> 2 1 -3.10 -5.40 2.34348343 0.17870946 -0.7565166 -5.2212905 1
#> 3 1 -14.60 -12.20 -0.25715638 0.13442514 -14.8571564 -12.0655749 2
#> 4 1 -14.20 -0.55 -0.79535285 0.68816179 -14.9953528 0.1381618 2
#> 5 1 -5.40 -3.30 1.54468200 -0.03914253 -3.8553180 -3.3391425 2
#> 6 1 -4.10 -2.55 2.06130102 0.05184902 -2.0386990 -2.4981510 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7420 -37125 5600
#> initial value 998.131940
#> iter 2 value 854.011929
#> iter 3 value 851.615495
#> iter 4 value 851.150634
#> iter 5 value 802.187436
#> iter 6 value 791.705520
#> iter 7 value 789.670515
#> iter 8 value 789.612812
#> iter 9 value 789.612646
#> iter 10 value 789.612634
#> iter 11 value 789.612600
#> iter 12 value 789.612548
#> iter 12 value 789.612548
#> iter 12 value 789.612548
#> final value 789.612548
#> converged
#> This is Run number 87
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.4597893 -0.8283012 -1.009789 -14.0283012 1
#> 2 1 -3.10 -5.40 -0.6587676 -1.3765755 -3.758768 -6.7765755 1
#> 3 1 -14.60 -12.20 -0.3655874 -1.2351958 -14.965587 -13.4351958 2
#> 4 1 -14.20 -0.55 1.2706433 -0.2990022 -12.929357 -0.8490022 2
#> 5 1 -5.40 -3.30 1.1424024 1.1312219 -4.257598 -2.1687781 2
#> 6 1 -4.10 -2.55 -0.5632015 2.1507338 -4.663202 -0.3992662 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6960 -38175 6300
#> initial value 998.131940
#> iter 2 value 836.245602
#> iter 3 value 830.881999
#> iter 4 value 828.399873
#> iter 5 value 782.214039
#> iter 6 value 771.414790
#> iter 7 value 769.744919
#> iter 8 value 769.706112
#> iter 8 value 769.706108
#> final value 769.706108
#> converged
#> This is Run number 88
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.60213445 1.6504753 0.05213445 -11.549525 1
#> 2 1 -3.10 -5.40 0.72063404 0.8033587 -2.37936596 -4.596641 1
#> 3 1 -14.60 -12.20 -0.08246296 1.2449144 -14.68246296 -10.955086 2
#> 4 1 -14.20 -0.55 1.76900365 1.9579270 -12.43099635 1.407927 2
#> 5 1 -5.40 -3.30 1.08997275 1.8610937 -4.31002725 -1.438906 2
#> 6 1 -4.10 -2.55 -0.28085846 0.6428674 -4.38085846 -1.907133 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6580 -36525 6375
#> initial value 998.131940
#> iter 2 value 858.457603
#> iter 3 value 855.006044
#> iter 4 value 852.991951
#> iter 5 value 801.416893
#> iter 6 value 791.206847
#> iter 7 value 789.436533
#> iter 8 value 789.396480
#> iter 9 value 789.396424
#> iter 10 value 789.396398
#> iter 11 value 789.396350
#> iter 12 value 789.396316
#> iter 12 value 789.396316
#> iter 12 value 789.396316
#> final value 789.396316
#> converged
#> This is Run number 89
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.1677418 1.4626584 0.6177418 -11.7373416 1
#> 2 1 -3.10 -5.40 1.5652340 1.6970691 -1.5347660 -3.7029309 1
#> 3 1 -14.60 -12.20 -0.4291350 0.4931609 -15.0291350 -11.7068391 2
#> 4 1 -14.20 -0.55 -0.5729715 -0.4471777 -14.7729715 -0.9971777 2
#> 5 1 -5.40 -3.30 -0.4811021 0.2366267 -5.8811021 -3.0633733 2
#> 6 1 -4.10 -2.55 1.5124808 -1.5094442 -2.5875192 -4.0594442 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6520 -36650 5500
#> initial value 998.131940
#> iter 2 value 861.548664
#> iter 3 value 857.263555
#> iter 4 value 852.901182
#> iter 5 value 803.995689
#> iter 6 value 793.861365
#> iter 7 value 791.842921
#> iter 8 value 791.788096
#> iter 9 value 791.787964
#> iter 9 value 791.787953
#> iter 9 value 791.787953
#> final value 791.787953
#> converged
#> This is Run number 90
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.6657224 0.8287880 1.115722 -12.37121204 1
#> 2 1 -3.10 -5.40 0.6673192 2.0223999 -2.432681 -3.37760009 1
#> 3 1 -14.60 -12.20 0.2764894 0.1447055 -14.323511 -12.05529453 2
#> 4 1 -14.20 -0.55 -1.2012768 0.5131352 -15.401277 -0.03686479 2
#> 5 1 -5.40 -3.30 1.4912732 -0.1454775 -3.908727 -3.44547749 2
#> 6 1 -4.10 -2.55 0.6649373 0.2877587 -3.435063 -2.26224132 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6640 -36775 6800
#> initial value 998.131940
#> iter 2 value 852.660095
#> iter 3 value 848.882736
#> iter 4 value 847.467081
#> iter 5 value 795.812399
#> iter 6 value 785.479228
#> iter 7 value 783.804568
#> iter 8 value 783.770325
#> iter 9 value 783.770270
#> iter 10 value 783.770235
#> iter 11 value 783.770206
#> iter 12 value 783.770166
#> iter 12 value 783.770166
#> iter 12 value 783.770166
#> final value 783.770166
#> converged
#> This is Run number 91
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.416082768 0.1862994 -0.1339172 -13.0137006 1
#> 2 1 -3.10 -5.40 -0.568210821 1.5918296 -3.6682108 -3.8081704 1
#> 3 1 -14.60 -12.20 -0.948000846 -0.2868767 -15.5480008 -12.4868767 2
#> 4 1 -14.20 -0.55 -0.008939369 0.3489111 -14.2089394 -0.2010889 2
#> 5 1 -5.40 -3.30 -1.073512560 1.8425228 -6.4735126 -1.4574772 2
#> 6 1 -4.10 -2.55 -0.416006855 1.7537197 -4.5160069 -0.7962803 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7320 -34675 5475
#> initial value 998.131940
#> iter 2 value 885.032660
#> iter 3 value 884.933198
#> iter 4 value 884.903644
#> iter 5 value 829.392503
#> iter 6 value 820.443008
#> iter 7 value 818.355541
#> iter 8 value 818.303470
#> iter 9 value 818.303262
#> iter 9 value 818.303255
#> iter 9 value 818.303255
#> final value 818.303255
#> converged
#> This is Run number 92
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.3734566 -1.1077575 -0.1765434 -14.3077575 1
#> 2 1 -3.10 -5.40 0.4989488 -0.1685852 -2.6010512 -5.5685852 1
#> 3 1 -14.60 -12.20 1.4119602 0.9727049 -13.1880398 -11.2272951 2
#> 4 1 -14.20 -0.55 0.1897250 -0.1430113 -14.0102750 -0.6930113 2
#> 5 1 -5.40 -3.30 -1.4901944 1.1095776 -6.8901944 -2.1904224 2
#> 6 1 -4.10 -2.55 -0.7119322 5.0664311 -4.8119322 2.5164311 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6740 -34650 5675
#> initial value 998.131940
#> iter 2 value 884.933105
#> iter 3 value 884.582230
#> iter 4 value 884.111189
#> iter 5 value 828.156382
#> iter 6 value 818.970342
#> iter 7 value 816.960219
#> iter 8 value 816.912262
#> iter 9 value 816.912108
#> iter 10 value 816.912081
#> iter 11 value 816.912031
#> iter 12 value 816.911988
#> iter 12 value 816.911988
#> iter 12 value 816.911988
#> final value 816.911988
#> converged
#> This is Run number 93
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.14373310 -0.2979953 -0.69373310 -13.4979953 1
#> 2 1 -3.10 -5.40 3.03166353 -0.3161766 -0.06833647 -5.7161766 1
#> 3 1 -14.60 -12.20 -0.06045617 4.4699949 -14.66045617 -7.7300051 2
#> 4 1 -14.20 -0.55 0.77673824 1.1577815 -13.42326176 0.6077815 2
#> 5 1 -5.40 -3.30 1.20801207 2.8917625 -4.19198793 -0.4082375 2
#> 6 1 -4.10 -2.55 -0.14276872 -0.6576289 -4.24276872 -3.2076289 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6800 -37950 6750
#> initial value 998.131940
#> iter 2 value 836.898184
#> iter 3 value 831.308600
#> iter 4 value 829.100092
#> iter 5 value 781.432302
#> iter 6 value 770.756092
#> iter 7 value 769.144851
#> iter 8 value 769.111450
#> iter 9 value 769.111392
#> iter 10 value 769.111341
#> iter 11 value 769.111288
#> iter 11 value 769.111279
#> iter 11 value 769.111279
#> final value 769.111279
#> converged
#> This is Run number 94
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.29009283 -0.3124680 -0.2599072 -13.512468 1
#> 2 1 -3.10 -5.40 1.96127790 -0.2601896 -1.1387221 -5.660190 1
#> 3 1 -14.60 -12.20 3.54490983 -0.8099415 -11.0550902 -13.009942 1
#> 4 1 -14.20 -0.55 0.48485974 -1.0550745 -13.7151403 -1.605074 2
#> 5 1 -5.40 -3.30 0.08657006 -0.6461230 -5.3134299 -3.946123 2
#> 6 1 -4.10 -2.55 -0.45236115 0.6791406 -4.5523612 -1.870859 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6020 -33475 6150
#> initial value 998.131940
#> iter 2 value 895.718606
#> iter 3 value 883.355812
#> iter 4 value 882.461820
#> iter 5 value 834.094480
#> iter 6 value 826.516185
#> iter 7 value 824.979995
#> iter 8 value 824.944102
#> iter 9 value 824.943850
#> iter 10 value 824.943762
#> iter 11 value 824.943647
#> iter 12 value 824.943562
#> iter 12 value 824.943562
#> iter 12 value 824.943562
#> final value 824.943562
#> converged
#> This is Run number 95
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.06876518 -1.33462490 -0.4812348 -14.5346249 1
#> 2 1 -3.10 -5.40 -1.19230525 -1.05929370 -4.2923052 -6.4592937 1
#> 3 1 -14.60 -12.20 1.24335732 -0.33069912 -13.3566427 -12.5306991 2
#> 4 1 -14.20 -0.55 1.79028228 -0.06881787 -12.4097177 -0.6188179 2
#> 5 1 -5.40 -3.30 2.01650352 1.65293931 -3.3834965 -1.6470607 2
#> 6 1 -4.10 -2.55 -0.88277994 1.46758130 -4.9827799 -1.0824187 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6100 -35225 7275
#> initial value 998.131940
#> iter 2 value 869.337169
#> iter 3 value 867.211587
#> iter 4 value 865.857019
#> iter 5 value 808.777834
#> iter 6 value 799.148111
#> iter 7 value 797.525317
#> iter 8 value 797.496887
#> iter 9 value 797.496837
#> iter 10 value 797.496801
#> iter 11 value 797.496774
#> iter 12 value 797.496740
#> iter 12 value 797.496740
#> iter 12 value 797.496740
#> final value 797.496740
#> converged
#> This is Run number 96
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.1982611 0.3910663 -0.7482611 -12.808934 1
#> 2 1 -3.10 -5.40 -0.5851311 2.8324663 -3.6851311 -2.567534 2
#> 3 1 -14.60 -12.20 -1.2513373 -1.0461566 -15.8513373 -13.246157 2
#> 4 1 -14.20 -0.55 0.3883240 0.1319360 -13.8116760 -0.418064 2
#> 5 1 -5.40 -3.30 -0.1275205 -0.5395253 -5.5275205 -3.839525 2
#> 6 1 -4.10 -2.55 -0.4888807 0.7294949 -4.5888807 -1.820505 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6860 -35225 5300
#> initial value 998.131940
#> iter 2 value 880.006373
#> iter 3 value 879.008672
#> iter 4 value 878.102775
#> iter 5 value 824.291241
#> iter 6 value 814.892392
#> iter 7 value 812.710285
#> iter 8 value 812.653529
#> iter 9 value 812.653333
#> iter 10 value 812.653310
#> iter 11 value 812.653271
#> iter 12 value 812.653233
#> iter 12 value 812.653233
#> iter 12 value 812.653233
#> final value 812.653233
#> converged
#> This is Run number 97
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.7394139 -0.19790089 1.189414 -13.397901 1
#> 2 1 -3.10 -5.40 0.3046723 0.85053947 -2.795328 -4.549461 1
#> 3 1 -14.60 -12.20 0.1684380 4.94206542 -14.431562 -7.257935 2
#> 4 1 -14.20 -0.55 -0.3123428 -0.09282504 -14.512343 -0.642825 2
#> 5 1 -5.40 -3.30 -0.1252146 -1.08871694 -5.525215 -4.388717 2
#> 6 1 -4.10 -2.55 -1.0462387 -0.08418343 -5.146239 -2.634183 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5300 -33125 6575
#> initial value 998.131940
#> iter 2 value 896.952184
#> iter 3 value 896.232182
#> iter 4 value 892.536924
#> iter 5 value 832.105431
#> iter 6 value 823.729501
#> iter 7 value 822.173055
#> iter 8 value 822.147133
#> iter 9 value 822.147095
#> iter 10 value 822.147074
#> iter 11 value 822.147031
#> iter 12 value 822.147008
#> iter 12 value 822.147008
#> iter 12 value 822.147008
#> final value 822.147008
#> converged
#> This is Run number 98
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.02530875 -0.86831554 0.475308754 -14.068316 1
#> 2 1 -3.10 -5.40 3.10771687 -1.45659686 0.007716869 -6.856597 1
#> 3 1 -14.60 -12.20 -0.07452353 2.28725394 -14.674523529 -9.912746 2
#> 4 1 -14.20 -0.55 1.24289951 2.73402819 -12.957100486 2.184028 2
#> 5 1 -5.40 -3.30 0.36376194 1.13449169 -5.036238056 -2.165508 2
#> 6 1 -4.10 -2.55 1.35595423 0.01680496 -2.744045768 -2.533195 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6640 -37925 7000
#> initial value 998.131940
#> iter 2 value 835.808854
#> iter 3 value 829.629691
#> iter 4 value 827.026388
#> iter 5 value 779.020130
#> iter 6 value 768.430870
#> iter 7 value 766.848388
#> iter 8 value 766.817131
#> iter 9 value 766.817046
#> iter 10 value 766.816991
#> iter 11 value 766.816943
#> iter 11 value 766.816939
#> iter 11 value 766.816939
#> final value 766.816939
#> converged
#> This is Run number 99
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.5235644 -0.01254791 -1.073564 -13.2125479 1
#> 2 1 -3.10 -5.40 -0.5823341 3.06246673 -3.682334 -2.3375333 2
#> 3 1 -14.60 -12.20 3.2952334 0.87366963 -11.304767 -11.3263304 1
#> 4 1 -14.20 -0.55 1.3231192 1.30873112 -12.876881 0.7587311 2
#> 5 1 -5.40 -3.30 1.5224868 -0.30267503 -3.877513 -3.6026750 2
#> 6 1 -4.10 -2.55 -0.1969594 -0.57454161 -4.296959 -3.1245416 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5920 -36275 6100
#> initial value 998.131940
#> iter 2 value 863.366534
#> iter 3 value 857.516043
#> iter 4 value 850.762654
#> iter 5 value 800.758063
#> iter 6 value 790.804246
#> iter 7 value 788.997674
#> iter 8 value 788.955263
#> iter 9 value 788.955209
#> iter 9 value 788.955199
#> iter 9 value 788.955199
#> final value 788.955199
#> converged
#> This is Run number 100
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.9919254 1.8474693 -1.541925 -11.3525307 1
#> 2 1 -3.10 -5.40 -0.2164087 -0.3161669 -3.316409 -5.7161669 1
#> 3 1 -14.60 -12.20 0.4093091 0.2958403 -14.190691 -11.9041597 2
#> 4 1 -14.20 -0.55 1.0906921 -0.4499593 -13.109308 -0.9999593 2
#> 5 1 -5.40 -3.30 1.5760140 0.5817732 -3.823986 -2.7182268 2
#> 6 1 -4.10 -2.55 0.6966979 0.8885055 -3.403302 -1.6614945 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6980 -38350 6075
#> initial value 998.131940
#> iter 2 value 834.991812
#> iter 3 value 829.391844
#> iter 4 value 826.291767
#> iter 5 value 781.216171
#> iter 6 value 770.371043
#> iter 7 value 768.672913
#> iter 8 value 768.631040
#> iter 9 value 768.630999
#> iter 10 value 768.630963
#> iter 10 value 768.630955
#> iter 11 value 768.630943
#> iter 12 value 768.630931
#> iter 12 value 768.630930
#> iter 12 value 768.630929
#> final value 768.630929
#> converged
#> This is Run number 101
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.1148081 0.95900375 0.5648081 -12.2409963 1
#> 2 1 -3.10 -5.40 3.2353194 2.94235524 0.1353194 -2.4576448 1
#> 3 1 -14.60 -12.20 1.5984965 -0.61760449 -13.0015035 -12.8176045 2
#> 4 1 -14.20 -0.55 0.9229698 0.01266454 -13.2770302 -0.5373355 2
#> 5 1 -5.40 -3.30 1.2853628 -0.41524452 -4.1146372 -3.7152445 2
#> 6 1 -4.10 -2.55 -0.9843743 -0.42495897 -5.0843743 -2.9749590 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7180 -36850 4750
#> initial value 998.131940
#> iter 2 value 861.967188
#> iter 3 value 859.316609
#> iter 4 value 857.107416
#> iter 5 value 809.073793
#> iter 6 value 798.999856
#> iter 7 value 796.560598
#> iter 8 value 796.483236
#> iter 9 value 796.482911
#> iter 9 value 796.482910
#> iter 9 value 796.482910
#> final value 796.482910
#> converged
#> This is Run number 102
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.9842438 0.79820859 -1.534244 -12.4017914 1
#> 2 1 -3.10 -5.40 0.5014180 2.43723388 -2.598582 -2.9627661 1
#> 3 1 -14.60 -12.20 0.4482750 -0.34121491 -14.151725 -12.5412149 2
#> 4 1 -14.20 -0.55 4.4008740 -0.06848879 -9.799126 -0.6184888 2
#> 5 1 -5.40 -3.30 3.0320457 -1.82350889 -2.367954 -5.1235089 1
#> 6 1 -4.10 -2.55 1.3958157 -0.78447327 -2.704184 -3.3344733 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6960 -37200 5850
#> initial value 998.131940
#> iter 2 value 852.196628
#> iter 3 value 848.637167
#> iter 4 value 846.740171
#> iter 5 value 797.987182
#> iter 6 value 787.493886
#> iter 7 value 785.601935
#> iter 8 value 785.552487
#> iter 9 value 785.552396
#> iter 10 value 785.552379
#> iter 11 value 785.552343
#> iter 12 value 785.552305
#> iter 12 value 785.552305
#> iter 12 value 785.552305
#> final value 785.552305
#> converged
#> This is Run number 103
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.2668078 0.008180767 0.7168078 -13.1918192 1
#> 2 1 -3.10 -5.40 0.4833437 1.961413222 -2.6166563 -3.4385868 1
#> 3 1 -14.60 -12.20 0.5724081 -1.038902570 -14.0275919 -13.2389026 2
#> 4 1 -14.20 -0.55 2.5009925 0.449758831 -11.6990075 -0.1002412 2
#> 5 1 -5.40 -3.30 -0.2783942 1.479049094 -5.6783942 -1.8209509 2
#> 6 1 -4.10 -2.55 -0.3921660 0.920213566 -4.4921660 -1.6297864 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5880 -35250 5650
#> initial value 998.131940
#> iter 2 value 878.375582
#> iter 3 value 874.212307
#> iter 4 value 868.339425
#> iter 5 value 815.931126
#> iter 6 value 806.499188
#> iter 7 value 804.557270
#> iter 8 value 804.511171
#> iter 9 value 804.511073
#> iter 9 value 804.511065
#> iter 9 value 804.511065
#> final value 804.511065
#> converged
#> This is Run number 104
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.6372441 0.7604791 -1.187244073 -12.4395209 1
#> 2 1 -3.10 -5.40 3.1038431 0.3466701 0.003843072 -5.0533299 1
#> 3 1 -14.60 -12.20 1.0245636 -0.5202914 -13.575436383 -12.7202914 2
#> 4 1 -14.20 -0.55 0.4468420 -0.2783596 -13.753158032 -0.8283596 2
#> 5 1 -5.40 -3.30 1.5846047 -0.7294499 -3.815395323 -4.0294499 1
#> 6 1 -4.10 -2.55 0.7266317 0.5286660 -3.373368347 -2.0213340 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6360 -36350 5575
#> initial value 998.131940
#> iter 2 value 865.100668
#> iter 3 value 860.777043
#> iter 4 value 856.039456
#> iter 5 value 806.300268
#> iter 6 value 796.306744
#> iter 7 value 794.313286
#> iter 8 value 794.260953
#> iter 9 value 794.260833
#> iter 9 value 794.260822
#> iter 9 value 794.260822
#> final value 794.260822
#> converged
#> This is Run number 105
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -1.62668404 1.3702156 -2.176684 -11.829784 1
#> 2 1 -3.10 -5.40 -0.12975849 1.2298738 -3.229758 -4.170126 1
#> 3 1 -14.60 -12.20 -1.35935644 0.3604746 -15.959356 -11.839525 2
#> 4 1 -14.20 -0.55 0.07118895 1.6447941 -14.128811 1.094794 2
#> 5 1 -5.40 -3.30 0.85033101 1.6086740 -4.549669 -1.691326 2
#> 6 1 -4.10 -2.55 -0.10800118 -0.6166891 -4.208001 -3.166689 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6980 -37775 5200
#> initial value 998.131940
#> iter 2 value 847.609730
#> iter 3 value 842.918009
#> iter 4 value 838.869117
#> iter 5 value 793.686307
#> iter 6 value 783.089151
#> iter 7 value 781.024902
#> iter 8 value 780.961959
#> iter 9 value 780.961788
#> iter 9 value 780.961782
#> iter 9 value 780.961782
#> final value 780.961782
#> converged
#> This is Run number 106
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 5.0624159 -1.0325833 4.512416 -14.2325833 1
#> 2 1 -3.10 -5.40 1.5923150 0.3711500 -1.507685 -5.0288500 1
#> 3 1 -14.60 -12.20 2.0081735 4.3062538 -12.591826 -7.8937462 2
#> 4 1 -14.20 -0.55 0.8920776 1.0321599 -13.307922 0.4821599 2
#> 5 1 -5.40 -3.30 -0.8638068 0.2008686 -6.263807 -3.0991314 2
#> 6 1 -4.10 -2.55 -1.3390726 0.1598988 -5.439073 -2.3901012 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6720 -38025 6575
#> initial value 998.131940
#> iter 2 value 836.944846
#> iter 3 value 830.964025
#> iter 4 value 827.839155
#> iter 5 value 780.971422
#> iter 6 value 770.292224
#> iter 7 value 768.663675
#> iter 8 value 768.628144
#> iter 9 value 768.628101
#> iter 10 value 768.628065
#> iter 11 value 768.628018
#> iter 12 value 768.628003
#> iter 12 value 768.628003
#> iter 12 value 768.628003
#> final value 768.628003
#> converged
#> This is Run number 107
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.1441828 1.4118489 -0.6941828 -11.788151 1
#> 2 1 -3.10 -5.40 0.8596584 -0.4937231 -2.2403416 -5.893723 1
#> 3 1 -14.60 -12.20 1.4893418 0.3400608 -13.1106582 -11.859939 2
#> 4 1 -14.20 -0.55 0.6330411 4.0104077 -13.5669589 3.460408 2
#> 5 1 -5.40 -3.30 2.6612552 -0.4043378 -2.7387448 -3.704338 1
#> 6 1 -4.10 -2.55 -0.3926683 -1.1468468 -4.4926683 -3.696847 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6520 -37200 6475
#> initial value 998.131940
#> iter 2 value 849.013793
#> iter 3 value 844.024151
#> iter 4 value 840.837945
#> iter 5 value 791.543003
#> iter 6 value 781.112082
#> iter 7 value 779.408159
#> iter 8 value 779.370247
#> iter 9 value 779.370211
#> iter 9 value 779.370209
#> iter 9 value 779.370209
#> final value 779.370209
#> converged
#> This is Run number 108
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.54957356 -1.2610514 1.999574 -14.4610514 1
#> 2 1 -3.10 -5.40 1.12970501 -0.8604095 -1.970295 -6.2604095 1
#> 3 1 -14.60 -12.20 0.61879532 2.8283112 -13.981205 -9.3716888 2
#> 4 1 -14.20 -0.55 0.08111534 0.3734563 -14.118885 -0.1765437 2
#> 5 1 -5.40 -3.30 0.90827359 0.6781927 -4.491726 -2.6218073 2
#> 6 1 -4.10 -2.55 1.84651637 2.9089385 -2.253484 0.3589385 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6420 -36125 5750
#> initial value 998.131940
#> iter 2 value 867.039913
#> iter 3 value 863.552851
#> iter 4 value 860.071890
#> iter 5 value 808.877647
#> iter 6 value 798.946838
#> iter 7 value 796.998444
#> iter 8 value 796.949502
#> iter 9 value 796.949396
#> iter 10 value 796.949377
#> iter 11 value 796.949348
#> iter 12 value 796.949325
#> iter 12 value 796.949325
#> iter 12 value 796.949325
#> final value 796.949325
#> converged
#> This is Run number 109
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.9438752 0.35898297 -1.493875 -12.8410170 1
#> 2 1 -3.10 -5.40 -0.7324869 0.05214339 -3.832487 -5.3478566 1
#> 3 1 -14.60 -12.20 0.3258005 0.12526822 -14.274199 -12.0747318 2
#> 4 1 -14.20 -0.55 -0.3117984 0.71717250 -14.511798 0.1671725 2
#> 5 1 -5.40 -3.30 0.7944007 1.38680871 -4.605599 -1.9131913 2
#> 6 1 -4.10 -2.55 -0.4108781 -0.52130508 -4.510878 -3.0713051 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6600 -35925 6150
#> initial value 998.131940
#> iter 2 value 867.311456
#> iter 3 value 864.947871
#> iter 4 value 863.423880
#> iter 5 value 810.322415
#> iter 6 value 800.390260
#> iter 7 value 798.536730
#> iter 8 value 798.493294
#> iter 9 value 798.493205
#> iter 10 value 798.493187
#> iter 11 value 798.493139
#> iter 12 value 798.493094
#> iter 12 value 798.493094
#> iter 12 value 798.493094
#> final value 798.493094
#> converged
#> This is Run number 110
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.4895202 1.618107055 -0.06047983 -11.5818929 1
#> 2 1 -3.10 -5.40 0.6830684 0.454278909 -2.41693160 -4.9457211 1
#> 3 1 -14.60 -12.20 0.4985343 -0.007976485 -14.10146573 -12.2079765 2
#> 4 1 -14.20 -0.55 -0.1344409 -0.878828074 -14.33444088 -1.4288281 2
#> 5 1 -5.40 -3.30 -0.1704911 1.647075265 -5.57049108 -1.6529247 2
#> 6 1 -4.10 -2.55 1.1140917 2.150440693 -2.98590831 -0.3995593 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6740 -37475 7300
#> initial value 998.131940
#> iter 2 value 840.061815
#> iter 3 value 834.953684
#> iter 4 value 833.839483
#> iter 5 value 783.553282
#> iter 6 value 773.042458
#> iter 7 value 771.467124
#> iter 8 value 771.439044
#> iter 9 value 771.438947
#> iter 10 value 771.438889
#> iter 11 value 771.438836
#> iter 11 value 771.438833
#> iter 11 value 771.438833
#> final value 771.438833
#> converged
#> This is Run number 111
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.48821473 1.42149753 -0.06178527 -11.7785025 1
#> 2 1 -3.10 -5.40 0.62984315 0.82505576 -2.47015685 -4.5749442 1
#> 3 1 -14.60 -12.20 0.75214479 -0.89872446 -13.84785521 -13.0987245 2
#> 4 1 -14.20 -0.55 0.82802999 0.03421718 -13.37197001 -0.5157828 2
#> 5 1 -5.40 -3.30 -0.91992118 1.26698198 -6.31992118 -2.0330180 2
#> 6 1 -4.10 -2.55 0.03192044 1.40438318 -4.06807956 -1.1456168 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6500 -37775 5950
#> initial value 998.131940
#> iter 2 value 844.089224
#> iter 3 value 837.577428
#> iter 4 value 831.779952
#> iter 5 value 786.131450
#> iter 6 value 775.556628
#> iter 7 value 773.789445
#> iter 8 value 773.744179
#> iter 9 value 773.744143
#> iter 9 value 773.744139
#> iter 9 value 773.744139
#> final value 773.744139
#> converged
#> This is Run number 112
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.4703375 0.7795623 -0.0796625 -12.420438 1
#> 2 1 -3.10 -5.40 2.0229591 3.1261411 -1.0770409 -2.273859 1
#> 3 1 -14.60 -12.20 0.6634758 0.5419221 -13.9365242 -11.658078 2
#> 4 1 -14.20 -0.55 -0.5239207 2.3898967 -14.7239207 1.839897 2
#> 5 1 -5.40 -3.30 1.5275020 -1.1457410 -3.8724980 -4.445741 1
#> 6 1 -4.10 -2.55 1.5242035 1.0012487 -2.5757965 -1.548751 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7480 -37400 6125
#> initial value 998.131940
#> iter 2 value 847.426708
#> iter 3 value 844.503958
#> iter 4 value 844.349382
#> iter 5 value 795.487971
#> iter 6 value 784.817114
#> iter 7 value 783.012092
#> iter 8 value 782.966999
#> iter 9 value 782.966919
#> iter 10 value 782.966888
#> iter 11 value 782.966844
#> iter 12 value 782.966803
#> iter 12 value 782.966803
#> iter 12 value 782.966803
#> final value 782.966803
#> converged
#> This is Run number 113
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.99197638 0.1611396 0.44197638 -13.0388604 1
#> 2 1 -3.10 -5.40 3.11179005 2.3576831 0.01179005 -3.0423169 1
#> 3 1 -14.60 -12.20 0.88231868 0.9632735 -13.71768132 -11.2367265 2
#> 4 1 -14.20 -0.55 0.06503794 -0.4357277 -14.13496206 -0.9857277 2
#> 5 1 -5.40 -3.30 -0.82647370 1.1515784 -6.22647370 -2.1484216 2
#> 6 1 -4.10 -2.55 -0.47289628 1.9101671 -4.57289628 -0.6398329 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6040 -34675 6875
#> initial value 998.131940
#> iter 2 value 878.295281
#> iter 3 value 876.996981
#> iter 4 value 875.482247
#> iter 5 value 817.643909
#> iter 6 value 808.309376
#> iter 7 value 806.647993
#> iter 8 value 806.616923
#> iter 9 value 806.616871
#> iter 10 value 806.616842
#> iter 11 value 806.616789
#> iter 12 value 806.616757
#> iter 12 value 806.616757
#> iter 12 value 806.616757
#> final value 806.616757
#> converged
#> This is Run number 114
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.26121553 0.1950558 -0.8112155 -13.00494416 1
#> 2 1 -3.10 -5.40 0.30776268 1.9964375 -2.7922373 -3.40356246 1
#> 3 1 -14.60 -12.20 -0.18931294 2.1097607 -14.7893129 -10.09023930 2
#> 4 1 -14.20 -0.55 0.91156595 0.5137316 -13.2884341 -0.03626837 2
#> 5 1 -5.40 -3.30 -0.15851326 0.2268327 -5.5585133 -3.07316726 2
#> 6 1 -4.10 -2.55 0.04778655 -0.1474703 -4.0522134 -2.69747033 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6400 -38200 5800
#> initial value 998.131940
#> iter 2 value 838.929417
#> iter 3 value 830.739788
#> iter 4 value 822.417715
#> iter 5 value 779.408878
#> iter 6 value 768.781831
#> iter 7 value 767.033514
#> iter 8 value 766.985929
#> iter 9 value 766.985898
#> iter 9 value 766.985891
#> iter 9 value 766.985887
#> final value 766.985887
#> converged
#> This is Run number 115
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.2835563 1.370901702 -0.2664437 -11.8290983 1
#> 2 1 -3.10 -5.40 -0.5062297 1.321439825 -3.6062297 -4.0785602 1
#> 3 1 -14.60 -12.20 1.3414764 -0.174751520 -13.2585236 -12.3747515 2
#> 4 1 -14.20 -0.55 2.2969767 -0.008904122 -11.9030233 -0.5589041 2
#> 5 1 -5.40 -3.30 0.6818900 0.217562002 -4.7181100 -3.0824380 2
#> 6 1 -4.10 -2.55 1.0214913 0.030308622 -3.0785087 -2.5196914 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6440 -35275 4925
#> initial value 998.131940
#> iter 2 value 881.422016
#> iter 3 value 878.847787
#> iter 4 value 875.236691
#> iter 5 value 823.182449
#> iter 6 value 813.880828
#> iter 7 value 811.602552
#> iter 8 value 811.541816
#> iter 9 value 811.541612
#> iter 9 value 811.541610
#> iter 9 value 811.541610
#> final value 811.541610
#> converged
#> This is Run number 116
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.7876673 0.6629265 1.237667 -12.5370735 1
#> 2 1 -3.10 -5.40 1.2719215 1.6251585 -1.828078 -3.7748415 1
#> 3 1 -14.60 -12.20 -0.3184970 1.3074020 -14.918497 -10.8925980 2
#> 4 1 -14.20 -0.55 0.4359348 0.3663921 -13.764065 -0.1836079 2
#> 5 1 -5.40 -3.30 2.5920864 -0.9846916 -2.807914 -4.2846916 1
#> 6 1 -4.10 -2.55 1.0148651 3.5008745 -3.085135 0.9508745 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6460 -35975 6650
#> initial value 998.131940
#> iter 2 value 863.903833
#> iter 3 value 861.162111
#> iter 4 value 859.675069
#> iter 5 value 805.883040
#> iter 6 value 795.898007
#> iter 7 value 794.172002
#> iter 8 value 794.135846
#> iter 9 value 794.135793
#> iter 10 value 794.135765
#> iter 11 value 794.135711
#> iter 12 value 794.135676
#> iter 12 value 794.135676
#> iter 12 value 794.135676
#> final value 794.135676
#> converged
#> This is Run number 117
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.258293017 -0.8260081 -0.808293 -14.026008 1
#> 2 1 -3.10 -5.40 0.144956658 1.6416443 -2.955043 -3.758356 1
#> 3 1 -14.60 -12.20 0.346587232 -0.8957318 -14.253413 -13.095732 2
#> 4 1 -14.20 -0.55 1.377651960 1.9381877 -12.822348 1.388188 2
#> 5 1 -5.40 -3.30 -0.001626954 1.0174979 -5.401627 -2.282502 2
#> 6 1 -4.10 -2.55 0.968436382 1.1207324 -3.131564 -1.429268 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6120 -35375 5900
#> initial value 998.131940
#> iter 2 value 875.574529
#> iter 3 value 872.505205
#> iter 4 value 868.739210
#> iter 5 value 815.315078
#> iter 6 value 805.756697
#> iter 7 value 803.871935
#> iter 8 value 803.828404
#> iter 9 value 803.828317
#> iter 10 value 803.828295
#> iter 11 value 803.828262
#> iter 12 value 803.828241
#> iter 12 value 803.828241
#> iter 12 value 803.828241
#> final value 803.828241
#> converged
#> This is Run number 118
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.2917422 0.79957423 0.7417422 -12.40042577 1
#> 2 1 -3.10 -5.40 0.2159123 -0.23867061 -2.8840877 -5.63867061 1
#> 3 1 -14.60 -12.20 0.3534358 0.45962903 -14.2465642 -11.74037097 2
#> 4 1 -14.20 -0.55 1.8140587 0.08644094 -12.3859413 -0.46355906 2
#> 5 1 -5.40 -3.30 0.1031037 0.97868315 -5.2968963 -2.32131685 2
#> 6 1 -4.10 -2.55 0.5627233 2.50656525 -3.5372767 -0.04343475 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7040 -36300 5050
#> initial value 998.131940
#> iter 2 value 867.842995
#> iter 3 value 865.714554
#> iter 4 value 864.057785
#> iter 5 value 813.788036
#> iter 6 value 803.890282
#> iter 7 value 801.587781
#> iter 8 value 801.520600
#> iter 9 value 801.520352
#> iter 9 value 801.520342
#> iter 9 value 801.520342
#> final value 801.520342
#> converged
#> This is Run number 119
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.1970205 1.6475968 -0.3529795 -11.552403 1
#> 2 1 -3.10 -5.40 -1.2115509 -1.0297862 -4.3115509 -6.429786 1
#> 3 1 -14.60 -12.20 -0.3190350 -0.2668385 -14.9190350 -12.466839 2
#> 4 1 -14.20 -0.55 -1.2770336 1.6955384 -15.4770336 1.145538 2
#> 5 1 -5.40 -3.30 -0.1659048 -0.7417034 -5.5659048 -4.041703 2
#> 6 1 -4.10 -2.55 0.2422806 -0.3991996 -3.8577194 -2.949200 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6600 -36875 5075
#> initial value 998.131940
#> iter 2 value 860.608738
#> iter 3 value 855.877030
#> iter 4 value 850.550899
#> iter 5 value 803.418604
#> iter 6 value 793.273989
#> iter 7 value 791.085192
#> iter 8 value 791.019613
#> iter 9 value 791.019396
#> iter 9 value 791.019396
#> iter 9 value 791.019396
#> final value 791.019396
#> converged
#> This is Run number 120
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -1.0213873438 1.7215055 -1.571387 -11.4784945 1
#> 2 1 -3.10 -5.40 -0.0007803167 0.7745181 -3.100780 -4.6254819 1
#> 3 1 -14.60 -12.20 -0.4616259265 1.3806582 -15.061626 -10.8193418 2
#> 4 1 -14.20 -0.55 -0.8933699784 0.3749922 -15.093370 -0.1750078 2
#> 5 1 -5.40 -3.30 3.7680564337 -0.9901512 -1.631944 -4.2901512 1
#> 6 1 -4.10 -2.55 1.2898227702 0.7184945 -2.810177 -1.8315055 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6800 -35825 5075
#> initial value 998.131940
#> iter 2 value 873.866443
#> iter 3 value 871.767585
#> iter 4 value 869.629481
#> iter 5 value 818.179052
#> iter 6 value 808.529453
#> iter 7 value 806.261079
#> iter 8 value 806.198066
#> iter 9 value 806.197847
#> iter 9 value 806.197836
#> iter 9 value 806.197836
#> final value 806.197836
#> converged
#> This is Run number 121
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.4453981 -0.47952892 0.8953981 -13.679529 1
#> 2 1 -3.10 -5.40 -0.1361666 -0.06185457 -3.2361666 -5.461855 1
#> 3 1 -14.60 -12.20 -0.4661038 0.36524208 -15.0661038 -11.834758 2
#> 4 1 -14.20 -0.55 0.9744814 -0.01142696 -13.2255186 -0.561427 2
#> 5 1 -5.40 -3.30 2.6858455 0.93034167 -2.7141545 -2.369658 2
#> 6 1 -4.10 -2.55 0.9802541 -0.47188837 -3.1197459 -3.021888 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7060 -37175 5950
#> initial value 998.131940
#> iter 2 value 851.905498
#> iter 3 value 848.651390
#> iter 4 value 847.373862
#> iter 5 value 798.214991
#> iter 6 value 787.698839
#> iter 7 value 785.828058
#> iter 8 value 785.779984
#> iter 9 value 785.779896
#> iter 9 value 785.779884
#> iter 9 value 785.779884
#> final value 785.779884
#> converged
#> This is Run number 122
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 4.9084202 1.5070023 4.358420 -11.6929977 1
#> 2 1 -3.10 -5.40 1.1716420 -0.1199290 -1.928358 -5.5199290 1
#> 3 1 -14.60 -12.20 -0.3512513 0.2988406 -14.951251 -11.9011594 2
#> 4 1 -14.20 -0.55 -0.4467806 1.4382965 -14.646781 0.8882965 2
#> 5 1 -5.40 -3.30 1.8733005 0.8531553 -3.526700 -2.4468447 2
#> 6 1 -4.10 -2.55 2.7589675 2.4405327 -1.341032 -0.1094673 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6860 -36425 5775
#> initial value 998.131940
#> iter 2 value 862.834947
#> iter 3 value 860.256346
#> iter 4 value 858.740367
#> iter 5 value 807.674494
#> iter 6 value 797.538006
#> iter 7 value 795.566536
#> iter 8 value 795.515330
#> iter 9 value 795.515204
#> iter 10 value 795.515182
#> iter 11 value 795.515143
#> iter 12 value 795.515107
#> iter 12 value 795.515107
#> iter 12 value 795.515107
#> final value 795.515107
#> converged
#> This is Run number 123
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.2012975 0.1058175 1.651298 -13.0941825 1
#> 2 1 -3.10 -5.40 -1.2515081 0.1583907 -4.351508 -5.2416093 1
#> 3 1 -14.60 -12.20 0.3188797 -1.3551924 -14.281120 -13.5551924 2
#> 4 1 -14.20 -0.55 -0.9049926 1.5362406 -15.104993 0.9862406 2
#> 5 1 -5.40 -3.30 0.5216791 -0.1659521 -4.878321 -3.4659521 2
#> 6 1 -4.10 -2.55 1.9772237 2.6834925 -2.122776 0.1334925 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6760 -37550 6525
#> initial value 998.131940
#> iter 2 value 843.825738
#> iter 3 value 838.968100
#> iter 4 value 836.721894
#> iter 5 value 788.131647
#> iter 6 value 777.537914
#> iter 7 value 775.860286
#> iter 8 value 775.823382
#> iter 9 value 775.823342
#> iter 10 value 775.823326
#> iter 11 value 775.823273
#> iter 12 value 775.823239
#> iter 12 value 775.823239
#> iter 12 value 775.823239
#> final value 775.823239
#> converged
#> This is Run number 124
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.6169356 -1.3670766 -1.166936 -14.5670766 1
#> 2 1 -3.10 -5.40 -0.3417644 4.5481042 -3.441764 -0.8518958 2
#> 3 1 -14.60 -12.20 1.2387795 -0.4875499 -13.361220 -12.6875499 2
#> 4 1 -14.20 -0.55 -0.6143058 0.1013598 -14.814306 -0.4486402 2
#> 5 1 -5.40 -3.30 0.8287290 -0.1613953 -4.571271 -3.4613953 2
#> 6 1 -4.10 -2.55 1.2982477 0.5988064 -2.801752 -1.9511936 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6280 -36075 6350
#> initial value 998.131940
#> iter 2 value 864.465331
#> iter 3 value 860.886047
#> iter 4 value 857.847459
#> iter 5 value 805.326931
#> iter 6 value 795.365469
#> iter 7 value 793.590573
#> iter 8 value 793.551198
#> iter 9 value 793.551143
#> iter 9 value 793.551131
#> iter 9 value 793.551131
#> final value 793.551131
#> converged
#> This is Run number 125
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.9683958 0.862947623 2.418396 -12.3370524 1
#> 2 1 -3.10 -5.40 -0.4971216 0.002933914 -3.597122 -5.3970661 1
#> 3 1 -14.60 -12.20 -0.4369105 -1.068231551 -15.036911 -13.2682316 2
#> 4 1 -14.20 -0.55 -0.2447842 -0.282961574 -14.444784 -0.8329616 2
#> 5 1 -5.40 -3.30 1.8655978 -0.312733375 -3.534402 -3.6127334 1
#> 6 1 -4.10 -2.55 0.4146401 -0.686578852 -3.685360 -3.2365789 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6620 -35775 5850
#> initial value 998.131940
#> iter 2 value 870.771933
#> iter 3 value 868.622566
#> iter 4 value 866.930225
#> iter 5 value 813.944045
#> iter 6 value 804.133892
#> iter 7 value 802.186127
#> iter 8 value 802.138248
#> iter 9 value 802.138131
#> iter 10 value 802.138105
#> iter 11 value 802.138063
#> iter 12 value 802.138029
#> iter 12 value 802.138029
#> iter 12 value 802.138029
#> final value 802.138029
#> converged
#> This is Run number 126
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.4155221 -0.04145355 -0.9655221 -13.2414536 1
#> 2 1 -3.10 -5.40 0.7997304 0.53125410 -2.3002696 -4.8687459 1
#> 3 1 -14.60 -12.20 -0.8186540 2.02119179 -15.4186540 -10.1788082 2
#> 4 1 -14.20 -0.55 3.1051972 -0.42328468 -11.0948028 -0.9732847 2
#> 5 1 -5.40 -3.30 -1.4194145 1.77799839 -6.8194145 -1.5220016 2
#> 6 1 -4.10 -2.55 0.8424762 0.83878348 -3.2575238 -1.7112165 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 8040 -39050 5475
#> initial value 998.131940
#> iter 2 value 826.584761
#> iter 3 value 822.877355
#> iter 4 value 822.560134
#> iter 5 value 779.828137
#> iter 6 value 768.613095
#> iter 7 value 766.796764
#> iter 8 value 766.744007
#> iter 9 value 766.743931
#> iter 10 value 766.743909
#> iter 11 value 766.743880
#> iter 12 value 766.743846
#> iter 12 value 766.743846
#> iter 12 value 766.743846
#> final value 766.743846
#> converged
#> This is Run number 127
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.004352858 -0.4406759 -0.5456471 -13.64067586 1
#> 2 1 -3.10 -5.40 -0.016260560 3.2920360 -3.1162606 -2.10796400 2
#> 3 1 -14.60 -12.20 -0.281850898 1.2900028 -14.8818509 -10.90999724 2
#> 4 1 -14.20 -0.55 -0.095987795 1.0451764 -14.2959878 0.49517636 2
#> 5 1 -5.40 -3.30 1.014622728 3.3736669 -4.3853773 0.07366686 2
#> 6 1 -4.10 -2.55 2.734467489 0.9849663 -1.3655325 -1.56503375 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6100 -35500 6925
#> initial value 998.131940
#> iter 2 value 868.224007
#> iter 3 value 865.446630
#> iter 4 value 863.280954
#> iter 5 value 807.817242
#> iter 6 value 798.095635
#> iter 7 value 796.426430
#> iter 8 value 796.394473
#> iter 8 value 796.394470
#> final value 796.394470
#> converged
#> This is Run number 128
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.93147589 -0.6666445 -1.481476 -13.866645 1
#> 2 1 -3.10 -5.40 0.06311187 2.0324295 -3.036888 -3.367571 1
#> 3 1 -14.60 -12.20 1.35009725 -0.1971302 -13.249903 -12.397130 2
#> 4 1 -14.20 -0.55 0.92898718 -0.6660135 -13.271013 -1.216014 2
#> 5 1 -5.40 -3.30 1.95945296 -1.0809040 -3.440547 -4.380904 1
#> 6 1 -4.10 -2.55 2.64233168 -0.4198240 -1.457668 -2.969824 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7020 -37350 5400
#> initial value 998.131940
#> iter 2 value 852.428974
#> iter 3 value 848.728317
#> iter 4 value 846.125561
#> iter 5 value 798.759219
#> iter 6 value 788.274771
#> iter 7 value 786.230278
#> iter 8 value 786.171198
#> iter 9 value 786.171045
#> iter 10 value 786.171031
#> iter 11 value 786.171009
#> iter 12 value 786.170983
#> iter 12 value 786.170983
#> iter 12 value 786.170983
#> final value 786.170983
#> converged
#> This is Run number 129
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.0350207 2.2971976 0.4850207 -10.9028024 1
#> 2 1 -3.10 -5.40 1.4400699 0.3360683 -1.6599301 -5.0639317 1
#> 3 1 -14.60 -12.20 -1.2071056 1.2554627 -15.8071056 -10.9445373 2
#> 4 1 -14.20 -0.55 0.9727764 0.2223873 -13.2272236 -0.3276127 2
#> 5 1 -5.40 -3.30 0.6506277 -0.7816784 -4.7493723 -4.0816784 2
#> 6 1 -4.10 -2.55 2.8263733 0.1651720 -1.2736267 -2.3848280 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7160 -38600 5325
#> initial value 998.131940
#> iter 2 value 835.129575
#> iter 3 value 829.680100
#> iter 4 value 825.584753
#> iter 5 value 782.819260
#> iter 6 value 771.909580
#> iter 7 value 770.018705
#> iter 8 value 769.962006
#> iter 9 value 769.961915
#> iter 9 value 769.961907
#> iter 9 value 769.961907
#> final value 769.961907
#> converged
#> This is Run number 130
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.2799944 1.9656325 -0.2700056 -11.234368 1
#> 2 1 -3.10 -5.40 0.8522748 0.3745742 -2.2477252 -5.025426 1
#> 3 1 -14.60 -12.20 -0.3725867 0.6602070 -14.9725867 -11.539793 2
#> 4 1 -14.20 -0.55 2.9537903 -0.4869293 -11.2462097 -1.036929 2
#> 5 1 -5.40 -3.30 -0.6537146 -0.3892197 -6.0537146 -3.689220 2
#> 6 1 -4.10 -2.55 3.5833104 -0.7035632 -0.5166896 -3.253563 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6760 -36425 5675
#> initial value 998.131940
#> iter 2 value 863.428699
#> iter 3 value 860.541140
#> iter 4 value 858.400144
#> iter 5 value 807.691318
#> iter 6 value 797.588894
#> iter 7 value 795.593744
#> iter 8 value 795.541342
#> iter 9 value 795.541213
#> iter 10 value 795.541192
#> iter 11 value 795.541158
#> iter 12 value 795.541128
#> iter 12 value 795.541128
#> iter 12 value 795.541128
#> final value 795.541128
#> converged
#> This is Run number 131
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.9983062 -0.3670797 -1.548306 -13.567080 1
#> 2 1 -3.10 -5.40 0.4521083 0.2036014 -2.647892 -5.196399 1
#> 3 1 -14.60 -12.20 0.4943178 0.7335683 -14.105682 -11.466432 2
#> 4 1 -14.20 -0.55 1.4999248 -0.8689211 -12.700075 -1.418921 2
#> 5 1 -5.40 -3.30 -0.1511645 0.5241645 -5.551165 -2.775836 2
#> 6 1 -4.10 -2.55 -0.5612329 0.7985882 -4.661233 -1.751412 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6880 -36325 5300
#> initial value 998.131940
#> iter 2 value 866.483027
#> iter 3 value 863.971974
#> iter 4 value 861.932924
#> iter 5 value 811.488943
#> iter 6 value 801.511269
#> iter 7 value 799.348448
#> iter 8 value 799.287927
#> iter 9 value 799.287736
#> iter 10 value 799.287720
#> iter 11 value 799.287694
#> iter 12 value 799.287663
#> iter 12 value 799.287663
#> iter 12 value 799.287663
#> final value 799.287663
#> converged
#> This is Run number 132
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.61965267 -0.1950728 0.06965267 -13.395073 1
#> 2 1 -3.10 -5.40 5.04046224 -1.1639548 1.94046224 -6.563955 1
#> 3 1 -14.60 -12.20 0.01862816 0.2308761 -14.58137184 -11.969124 2
#> 4 1 -14.20 -0.55 0.63250235 4.7133153 -13.56749765 4.163315 2
#> 5 1 -5.40 -3.30 2.61009225 1.5499945 -2.78990775 -1.750005 2
#> 6 1 -4.10 -2.55 -1.12083107 0.7593129 -5.22083107 -1.790687 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6960 -35200 6150
#> initial value 998.131940
#> iter 2 value 875.813994
#> iter 3 value 875.054981
#> iter 4 value 874.967078
#> iter 5 value 819.678073
#> iter 6 value 810.105574
#> iter 7 value 808.233590
#> iter 8 value 808.189880
#> iter 9 value 808.189755
#> iter 10 value 808.189719
#> iter 11 value 808.189671
#> iter 12 value 808.189632
#> iter 12 value 808.189632
#> iter 12 value 808.189632
#> final value 808.189632
#> converged
#> This is Run number 133
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 3.24121290 -0.255099219 2.6912129 -13.45509922 1
#> 2 1 -3.10 -5.40 -0.33708529 1.254773193 -3.4370853 -4.14522681 1
#> 3 1 -14.60 -12.20 -0.41176461 -0.006367495 -15.0117646 -12.20636749 2
#> 4 1 -14.20 -0.55 0.04973029 0.611697428 -14.1502697 0.06169743 2
#> 5 1 -5.40 -3.30 -0.65228670 1.873410626 -6.0522867 -1.42658937 2
#> 6 1 -4.10 -2.55 3.93403336 -1.091020120 -0.1659666 -3.64102012 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6840 -36325 5150
#> initial value 998.131940
#> iter 2 value 867.228567
#> iter 3 value 864.516774
#> iter 4 value 862.002667
#> iter 5 value 811.972034
#> iter 6 value 802.040558
#> iter 7 value 799.817614
#> iter 8 value 799.754125
#> iter 9 value 799.753913
#> iter 9 value 799.753903
#> iter 9 value 799.753903
#> final value 799.753903
#> converged
#> This is Run number 134
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.04028909 -0.09143735 0.4902891 -13.2914374 1
#> 2 1 -3.10 -5.40 -0.08265461 0.98349191 -3.1826546 -4.4165081 1
#> 3 1 -14.60 -12.20 2.66349687 0.57250978 -11.9365031 -11.6274902 2
#> 4 1 -14.20 -0.55 0.38603897 -0.16308366 -13.8139610 -0.7130837 2
#> 5 1 -5.40 -3.30 -0.05195166 0.04551729 -5.4519517 -3.2544827 2
#> 6 1 -4.10 -2.55 2.45463056 1.09649131 -1.6453694 -1.4535087 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7300 -37275 5575
#> initial value 998.131940
#> iter 2 value 852.277978
#> iter 3 value 849.474496
#> iter 4 value 848.517368
#> iter 5 value 800.133614
#> iter 6 value 789.603088
#> iter 7 value 787.587255
#> iter 8 value 787.530201
#> iter 9 value 787.530050
#> iter 10 value 787.530035
#> iter 11 value 787.530002
#> iter 12 value 787.529960
#> iter 12 value 787.529960
#> iter 12 value 787.529960
#> final value 787.529960
#> converged
#> This is Run number 135
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.5243167 -0.49448707 1.9743167 -13.6944871 1
#> 2 1 -3.10 -5.40 2.4356483 2.80506315 -0.6643517 -2.5949368 1
#> 3 1 -14.60 -12.20 -0.8661444 0.36360302 -15.4661444 -11.8363970 2
#> 4 1 -14.20 -0.55 4.7103643 -0.16938606 -9.4896357 -0.7193861 2
#> 5 1 -5.40 -3.30 1.0527973 1.30438464 -4.3472027 -1.9956154 2
#> 6 1 -4.10 -2.55 0.8602860 -0.01910393 -3.2397140 -2.5691039 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6740 -37625 5875
#> initial value 998.131940
#> iter 2 value 846.446838
#> iter 3 value 841.327767
#> iter 4 value 837.506066
#> iter 5 value 790.714893
#> iter 6 value 780.120914
#> iter 7 value 778.300144
#> iter 8 value 778.252955
#> iter 9 value 778.252899
#> iter 9 value 778.252887
#> iter 9 value 778.252887
#> final value 778.252887
#> converged
#> This is Run number 136
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.01105716 0.8341730 -0.5610572 -12.3658270 1
#> 2 1 -3.10 -5.40 0.04932407 0.8372689 -3.0506759 -4.5627311 1
#> 3 1 -14.60 -12.20 -0.19700042 -0.2034370 -14.7970004 -12.4034370 2
#> 4 1 -14.20 -0.55 0.42918442 -0.1754201 -13.7708156 -0.7254201 2
#> 5 1 -5.40 -3.30 -1.08151022 0.6969772 -6.4815102 -2.6030228 2
#> 6 1 -4.10 -2.55 2.21586831 1.2755115 -1.8841317 -1.2744885 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6420 -37825 5925
#> initial value 998.131940
#> iter 2 value 843.553907
#> iter 3 value 836.492038
#> iter 4 value 829.791808
#> iter 5 value 784.717639
#> iter 6 value 774.155461
#> iter 7 value 772.392363
#> iter 8 value 772.346669
#> iter 9 value 772.346634
#> iter 9 value 772.346631
#> iter 9 value 772.346631
#> final value 772.346631
#> converged
#> This is Run number 137
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.70308260 -0.5636452 -1.253083 -13.763645 1
#> 2 1 -3.10 -5.40 5.16442167 0.6968620 2.064422 -4.703138 1
#> 3 1 -14.60 -12.20 -0.60977824 -0.1012917 -15.209778 -12.301292 2
#> 4 1 -14.20 -0.55 3.24980492 1.6178302 -10.950195 1.067830 2
#> 5 1 -5.40 -3.30 0.44584258 2.0849306 -4.954157 -1.215069 2
#> 6 1 -4.10 -2.55 -0.04605961 -0.1870332 -4.146060 -2.737033 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6160 -36000 6250
#> initial value 998.131940
#> iter 2 value 865.999012
#> iter 3 value 862.054926
#> iter 4 value 858.170794
#> iter 5 value 805.920298
#> iter 6 value 796.022990
#> iter 7 value 794.231430
#> iter 8 value 794.191193
#> iter 9 value 794.191136
#> iter 10 value 794.191118
#> iter 11 value 794.191081
#> iter 12 value 794.191053
#> iter 12 value 794.191053
#> iter 12 value 794.191053
#> final value 794.191053
#> converged
#> This is Run number 138
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.3564967 0.4625183 0.8064967 -12.73748165 1
#> 2 1 -3.10 -5.40 1.0322293 2.0518095 -2.0677707 -3.34819047 1
#> 3 1 -14.60 -12.20 0.1211711 0.8337960 -14.4788289 -11.36620403 2
#> 4 1 -14.20 -0.55 0.8816594 0.4955366 -13.3183406 -0.05446338 2
#> 5 1 -5.40 -3.30 0.6677161 -2.1027891 -4.7322839 -5.40278907 1
#> 6 1 -4.10 -2.55 1.5026217 -0.2540588 -2.5973783 -2.80405877 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6900 -37000 6050
#> initial value 998.131940
#> iter 2 value 853.837049
#> iter 3 value 850.447406
#> iter 4 value 848.833965
#> iter 5 value 799.082012
#> iter 6 value 788.651884
#> iter 7 value 786.807571
#> iter 8 value 786.761691
#> iter 9 value 786.761613
#> iter 9 value 786.761603
#> iter 9 value 786.761603
#> final value 786.761603
#> converged
#> This is Run number 139
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.25741035 0.4053828 -0.8074104 -12.7946172 1
#> 2 1 -3.10 -5.40 5.99124367 1.0486595 2.8912437 -4.3513405 1
#> 3 1 -14.60 -12.20 3.83056673 0.3717909 -10.7694333 -11.8282091 1
#> 4 1 -14.20 -0.55 0.43192788 -0.1818204 -13.7680721 -0.7318204 2
#> 5 1 -5.40 -3.30 -1.22525354 0.7631768 -6.6252535 -2.5368232 2
#> 6 1 -4.10 -2.55 -0.02348668 0.3158118 -4.1234867 -2.2341882 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6500 -36425 6100
#> initial value 998.131940
#> iter 2 value 861.326485
#> iter 3 value 857.737542
#> iter 4 value 854.953304
#> iter 5 value 803.783129
#> iter 6 value 793.656861
#> iter 7 value 791.818619
#> iter 8 value 791.774764
#> iter 9 value 791.774692
#> iter 10 value 791.774673
#> iter 11 value 791.774633
#> iter 12 value 791.774600
#> iter 12 value 791.774600
#> iter 12 value 791.774600
#> final value 791.774600
#> converged
#> This is Run number 140
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.11821684 3.3335800 0.5682168 -9.866420 1
#> 2 1 -3.10 -5.40 -0.22701880 0.4710148 -3.3270188 -4.928985 1
#> 3 1 -14.60 -12.20 -0.31345245 2.6258519 -14.9134524 -9.574148 2
#> 4 1 -14.20 -0.55 -1.11688631 3.1828280 -15.3168863 2.632828 2
#> 5 1 -5.40 -3.30 1.97146097 0.7784067 -3.4285390 -2.521593 2
#> 6 1 -4.10 -2.55 0.03606356 -0.4782386 -4.0639364 -3.028239 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5920 -36650 7950
#> initial value 998.131940
#> iter 2 value 847.008593
#> iter 3 value 840.947440
#> iter 4 value 837.850269
#> iter 5 value 784.381259
#> iter 6 value 774.384269
#> iter 7 value 772.805039
#> iter 8 value 772.778447
#> iter 9 value 772.778355
#> iter 10 value 772.778320
#> iter 11 value 772.778292
#> iter 11 value 772.778288
#> iter 11 value 772.778288
#> final value 772.778288
#> converged
#> This is Run number 141
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.3688783 2.19739376 -0.9188783 -11.002606 1
#> 2 1 -3.10 -5.40 0.6618690 0.77726032 -2.4381310 -4.622740 1
#> 3 1 -14.60 -12.20 1.6739780 -1.19895993 -12.9260220 -13.398960 1
#> 4 1 -14.20 -0.55 1.8429383 2.74825124 -12.3570617 2.198251 2
#> 5 1 -5.40 -3.30 0.3066316 0.07843029 -5.0933684 -3.221570 2
#> 6 1 -4.10 -2.55 1.9594571 -0.39533655 -2.1405429 -2.945337 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6840 -38375 6600
#> initial value 998.131940
#> iter 2 value 831.727114
#> iter 3 value 825.450644
#> iter 4 value 822.535700
#> iter 5 value 776.690463
#> iter 6 value 765.925671
#> iter 7 value 764.327872
#> iter 8 value 764.293286
#> iter 9 value 764.293219
#> iter 10 value 764.293168
#> iter 11 value 764.293120
#> iter 11 value 764.293116
#> iter 11 value 764.293116
#> final value 764.293116
#> converged
#> This is Run number 142
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.25701507 0.58023700 -0.2929849 -12.61976300 1
#> 2 1 -3.10 -5.40 -0.88717839 2.70407970 -3.9871784 -2.69592030 2
#> 3 1 -14.60 -12.20 -0.04426961 0.59204833 -14.6442696 -11.60795167 2
#> 4 1 -14.20 -0.55 0.27185636 0.51125007 -13.9281436 -0.03874993 2
#> 5 1 -5.40 -3.30 2.44111568 0.01705813 -2.9588843 -3.28294187 1
#> 6 1 -4.10 -2.55 0.32839760 -0.07620751 -3.7716024 -2.62620751 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6840 -36850 6350
#> initial value 998.131940
#> iter 2 value 854.188087
#> iter 3 value 850.869189
#> iter 4 value 849.589877
#> iter 5 value 798.835533
#> iter 6 value 788.445691
#> iter 7 value 786.674318
#> iter 8 value 786.633404
#> iter 9 value 786.633345
#> iter 10 value 786.633317
#> iter 11 value 786.633267
#> iter 12 value 786.633230
#> iter 12 value 786.633230
#> iter 12 value 786.633230
#> final value 786.633230
#> converged
#> This is Run number 143
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.5461316 1.01923131 -0.003868356 -12.1807687 1
#> 2 1 -3.10 -5.40 -0.9051786 0.06571833 -4.005178564 -5.3342817 1
#> 3 1 -14.60 -12.20 0.6924690 -1.22951576 -13.907531024 -13.4295158 2
#> 4 1 -14.20 -0.55 -0.2254366 -0.36339121 -14.425436635 -0.9133912 2
#> 5 1 -5.40 -3.30 3.2789358 1.49135250 -2.121064231 -1.8086475 2
#> 6 1 -4.10 -2.55 0.5043155 -0.93881387 -3.595684455 -3.4888139 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6080 -35950 6250
#> initial value 998.131940
#> iter 2 value 866.636791
#> iter 3 value 862.462449
#> iter 4 value 858.116269
#> iter 5 value 805.903482
#> iter 6 value 796.042441
#> iter 7 value 794.254992
#> iter 8 value 794.215043
#> iter 9 value 794.214988
#> iter 10 value 794.214971
#> iter 11 value 794.214936
#> iter 12 value 794.214911
#> iter 12 value 794.214911
#> iter 12 value 794.214911
#> final value 794.214911
#> converged
#> This is Run number 144
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.8696055 -1.1626581 2.319605 -14.3626581 1
#> 2 1 -3.10 -5.40 -0.7541940 5.1255370 -3.854194 -0.2744630 2
#> 3 1 -14.60 -12.20 0.4226706 1.7571998 -14.177329 -10.4428002 2
#> 4 1 -14.20 -0.55 0.3717247 0.2060559 -13.828275 -0.3439441 2
#> 5 1 -5.40 -3.30 0.8270661 1.0432857 -4.572934 -2.2567143 2
#> 6 1 -4.10 -2.55 0.7583447 -0.2517304 -3.341655 -2.8017304 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6180 -34125 5200
#> initial value 998.131940
#> iter 2 value 893.453162
#> iter 3 value 892.192599
#> iter 4 value 889.478162
#> iter 5 value 833.737650
#> iter 6 value 824.993911
#> iter 7 value 822.944400
#> iter 8 value 822.897868
#> iter 9 value 822.897742
#> iter 10 value 822.897723
#> iter 11 value 822.897696
#> iter 12 value 822.897675
#> iter 12 value 822.897675
#> iter 12 value 822.897675
#> final value 822.897675
#> converged
#> This is Run number 145
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.2851323 0.9446975 -0.8351323 -12.255303 1
#> 2 1 -3.10 -5.40 1.1544719 0.1377502 -1.9455281 -5.262250 1
#> 3 1 -14.60 -12.20 0.1757897 0.1189227 -14.4242103 -12.081077 2
#> 4 1 -14.20 -0.55 1.5723075 -0.9129793 -12.6276925 -1.462979 2
#> 5 1 -5.40 -3.30 -1.0201070 0.4048521 -6.4201070 -2.895148 2
#> 6 1 -4.10 -2.55 0.8174122 0.7824634 -3.2825878 -1.767537 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7420 -37075 4925
#> initial value 998.131940
#> iter 2 value 857.944841
#> iter 3 value 855.676486
#> iter 4 value 854.538189
#> iter 5 value 806.525042
#> iter 6 value 796.266128
#> iter 7 value 793.903810
#> iter 8 value 793.829015
#> iter 9 value 793.828711
#> iter 9 value 793.828705
#> iter 9 value 793.828705
#> final value 793.828705
#> converged
#> This is Run number 146
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.7461188 0.7404469 -1.296119 -12.4595531 1
#> 2 1 -3.10 -5.40 -1.3409378 0.8253670 -4.440938 -4.5746330 1
#> 3 1 -14.60 -12.20 0.7070241 -0.8542990 -13.892976 -13.0542990 2
#> 4 1 -14.20 -0.55 -0.2960245 -0.5858035 -14.496025 -1.1358035 2
#> 5 1 -5.40 -3.30 2.4656523 1.6333945 -2.934348 -1.6666055 2
#> 6 1 -4.10 -2.55 0.4611995 3.4468518 -3.638801 0.8968518 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7460 -38475 6225
#> initial value 998.131940
#> iter 2 value 831.849224
#> iter 3 value 827.360299
#> iter 4 value 826.604751
#> iter 5 value 781.042892
#> iter 6 value 770.046149
#> iter 7 value 768.381761
#> iter 8 value 768.342784
#> iter 9 value 768.342738
#> iter 10 value 768.342715
#> iter 11 value 768.342659
#> iter 12 value 768.342618
#> iter 12 value 768.342618
#> iter 12 value 768.342618
#> final value 768.342618
#> converged
#> This is Run number 147
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.1996774 -0.1139608 -0.3503226 -13.313961 1
#> 2 1 -3.10 -5.40 2.6182905 1.4352772 -0.4817095 -3.964723 1
#> 3 1 -14.60 -12.20 1.7214160 1.0003790 -12.8785840 -11.199621 2
#> 4 1 -14.20 -0.55 1.6502914 -0.8426590 -12.5497086 -1.392659 2
#> 5 1 -5.40 -3.30 0.9802141 0.5315024 -4.4197859 -2.768498 2
#> 6 1 -4.10 -2.55 -0.3742015 1.1501259 -4.4742015 -1.399874 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6660 -36025 7150
#> initial value 998.131940
#> iter 2 value 860.079376
#> iter 3 value 857.557908
#> iter 4 value 857.164474
#> iter 5 value 802.568674
#> iter 6 value 792.484792
#> iter 7 value 790.847788
#> iter 8 value 790.817601
#> iter 9 value 790.817585
#> iter 10 value 790.817566
#> iter 11 value 790.817511
#> iter 12 value 790.817439
#> iter 12 value 790.817439
#> iter 12 value 790.817439
#> final value 790.817439
#> converged
#> This is Run number 148
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.7876935 -0.3032079 0.2376935 -13.503208 1
#> 2 1 -3.10 -5.40 -0.5755507 -0.4948218 -3.6755507 -5.894822 1
#> 3 1 -14.60 -12.20 0.6826174 2.8102543 -13.9173826 -9.389746 2
#> 4 1 -14.20 -0.55 4.2352937 1.9578420 -9.9647063 1.407842 2
#> 5 1 -5.40 -3.30 0.6785231 0.5858465 -4.7214769 -2.714154 2
#> 6 1 -4.10 -2.55 -0.9002395 0.1450818 -5.0002395 -2.404918 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6580 -37800 6100
#> initial value 998.131940
#> iter 2 value 842.890837
#> iter 3 value 836.772207
#> iter 4 value 831.978477
#> iter 5 value 785.758983
#> iter 6 value 775.151298
#> iter 7 value 773.418191
#> iter 8 value 773.375512
#> iter 9 value 773.375484
#> iter 10 value 773.375470
#> iter 11 value 773.375442
#> iter 12 value 773.375420
#> iter 12 value 773.375420
#> iter 12 value 773.375420
#> final value 773.375420
#> converged
#> This is Run number 149
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.78376713 -0.2911807 0.2337671 -13.4911807 1
#> 2 1 -3.10 -5.40 0.35696751 -0.1206482 -2.7430325 -5.5206482 1
#> 3 1 -14.60 -12.20 -0.06969945 -0.2573338 -14.6696994 -12.4573338 2
#> 4 1 -14.20 -0.55 -0.53240547 0.3613679 -14.7324055 -0.1886321 2
#> 5 1 -5.40 -3.30 3.22674162 0.5419758 -2.1732584 -2.7580242 1
#> 6 1 -4.10 -2.55 0.49289538 1.2477160 -3.6071046 -1.3022840 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6280 -34575 5325
#> initial value 998.131940
#> iter 2 value 887.785405
#> iter 3 value 886.240943
#> iter 4 value 883.619958
#> iter 5 value 828.696778
#> iter 6 value 819.667716
#> iter 7 value 817.610934
#> iter 8 value 817.562402
#> iter 9 value 817.562267
#> iter 10 value 817.562247
#> iter 11 value 817.562217
#> iter 12 value 817.562194
#> iter 12 value 817.562194
#> iter 12 value 817.562194
#> final value 817.562194
#> converged
#> This is Run number 150
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.4827529 1.663345 0.9327529 -11.536655 1
#> 2 1 -3.10 -5.40 1.4624753 1.176314 -1.6375247 -4.223686 1
#> 3 1 -14.60 -12.20 1.7734748 -0.391327 -12.8265252 -12.591327 2
#> 4 1 -14.20 -0.55 2.9152607 3.804608 -11.2847393 3.254608 2
#> 5 1 -5.40 -3.30 -1.1555053 1.202072 -6.5555053 -2.097928 2
#> 6 1 -4.10 -2.55 -0.5556288 3.332954 -4.6556288 0.782954 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6700 -35625 5025
#> initial value 998.131940
#> iter 2 value 876.615219
#> iter 3 value 874.479605
#> iter 4 value 872.020402
#> iter 5 value 820.234904
#> iter 6 value 810.710151
#> iter 7 value 808.433572
#> iter 8 value 808.371241
#> iter 9 value 808.371027
#> iter 9 value 808.371017
#> iter 9 value 808.371017
#> final value 808.371017
#> converged
#> This is Run number 151
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.5203410 -0.10120416 -1.070341 -13.3012042 1
#> 2 1 -3.10 -5.40 0.3638040 0.93799164 -2.736196 -4.4620084 1
#> 3 1 -14.60 -12.20 0.3776672 0.05759744 -14.222333 -12.1424026 2
#> 4 1 -14.20 -0.55 0.6885427 -0.94702233 -13.511457 -1.4970223 2
#> 5 1 -5.40 -3.30 1.2594943 0.22103623 -4.140506 -3.0789638 2
#> 6 1 -4.10 -2.55 0.4048844 1.99343581 -3.695116 -0.5565642 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7460 -38700 5200
#> initial value 998.131940
#> iter 2 value 833.960019
#> iter 3 value 829.454679
#> iter 4 value 826.850058
#> iter 5 value 784.009587
#> iter 6 value 773.019765
#> iter 7 value 771.068935
#> iter 8 value 771.008428
#> iter 9 value 771.008304
#> iter 9 value 771.008295
#> iter 9 value 771.008295
#> final value 771.008295
#> converged
#> This is Run number 152
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.57090002 -0.76006385 1.020900 -13.9600639 1
#> 2 1 -3.10 -5.40 8.75508236 0.00714076 5.655082 -5.3928592 1
#> 3 1 -14.60 -12.20 -0.34228836 -0.30263007 -14.942288 -12.5026301 2
#> 4 1 -14.20 -0.55 0.69218864 0.90694680 -13.507811 0.3569468 2
#> 5 1 -5.40 -3.30 0.36017574 2.49964138 -5.039824 -0.8003586 2
#> 6 1 -4.10 -2.55 0.06690711 0.10387992 -4.033093 -2.4461201 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7620 -37650 6575
#> initial value 998.131940
#> iter 2 value 841.213815
#> iter 3 value 837.664457
#> iter 4 value 837.361545
#> iter 5 value 784.046055
#> iter 6 value 777.093115
#> iter 7 value 776.708796
#> iter 8 value 776.680343
#> iter 9 value 776.680300
#> iter 9 value 776.680288
#> iter 9 value 776.680288
#> final value 776.680288
#> converged
#> This is Run number 153
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.2413562 1.0230826 1.6913562 -12.176917 1
#> 2 1 -3.10 -5.40 2.8731596 2.1012617 -0.2268404 -3.298738 1
#> 3 1 -14.60 -12.20 1.8352728 1.3968337 -12.7647272 -10.803166 2
#> 4 1 -14.20 -0.55 0.3469918 -1.2084200 -13.8530082 -1.758420 2
#> 5 1 -5.40 -3.30 1.5515718 -0.1631828 -3.8484282 -3.463183 2
#> 6 1 -4.10 -2.55 -0.4327455 0.1453351 -4.5327455 -2.404665 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6720 -37150 5550
#> initial value 998.131940
#> iter 2 value 854.595284
#> iter 3 value 850.200495
#> iter 4 value 846.386042
#> iter 5 value 798.654691
#> iter 6 value 788.271739
#> iter 7 value 786.295138
#> iter 8 value 786.240605
#> iter 9 value 786.240486
#> iter 10 value 786.240473
#> iter 11 value 786.240453
#> iter 12 value 786.240431
#> iter 12 value 786.240431
#> iter 12 value 786.240431
#> final value 786.240431
#> converged
#> This is Run number 154
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.4799782 1.8678493 -1.029978 -11.332151 1
#> 2 1 -3.10 -5.40 -0.7207945 -0.2483910 -3.820794 -5.648391 1
#> 3 1 -14.60 -12.20 1.8022028 -0.4063768 -12.797797 -12.606377 2
#> 4 1 -14.20 -0.55 0.3653153 -0.8645092 -13.834685 -1.414509 2
#> 5 1 -5.40 -3.30 2.4374656 5.0977176 -2.962534 1.797718 2
#> 6 1 -4.10 -2.55 -0.7617558 -0.1469219 -4.861756 -2.696922 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6620 -38250 6450
#> initial value 998.131940
#> iter 2 value 834.537341
#> iter 3 value 827.648079
#> iter 4 value 823.109794
#> iter 5 value 777.670215
#> iter 6 value 766.980586
#> iter 7 value 765.357030
#> iter 8 value 765.320023
#> iter 9 value 765.319985
#> iter 10 value 765.319954
#> iter 11 value 765.319918
#> iter 11 value 765.319908
#> iter 11 value 765.319908
#> final value 765.319908
#> converged
#> This is Run number 155
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.78574162 3.39916638 1.235742 -9.8008336 1
#> 2 1 -3.10 -5.40 0.04898344 0.47205078 -3.051017 -4.9279492 1
#> 3 1 -14.60 -12.20 -1.70182206 -0.01094297 -16.301822 -12.2109430 2
#> 4 1 -14.20 -0.55 -0.82963514 1.05557476 -15.029635 0.5055748 2
#> 5 1 -5.40 -3.30 0.27934689 -0.41983761 -5.120653 -3.7198376 2
#> 6 1 -4.10 -2.55 -1.37499417 0.12345214 -5.474994 -2.4265479 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7040 -37450 5950
#> initial value 998.131940
#> iter 2 value 848.210284
#> iter 3 value 844.457574
#> iter 4 value 842.779210
#> iter 5 value 794.577063
#> iter 6 value 783.964476
#> iter 7 value 782.123613
#> iter 8 value 782.076381
#> iter 9 value 782.076308
#> iter 9 value 782.076299
#> iter 9 value 782.076299
#> final value 782.076299
#> converged
#> This is Run number 156
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.56926560 1.8837654 0.0192656 -11.3162346 1
#> 2 1 -3.10 -5.40 0.33165859 0.1455418 -2.7683414 -5.2544582 1
#> 3 1 -14.60 -12.20 -0.54086671 -0.5755894 -15.1408667 -12.7755894 2
#> 4 1 -14.20 -0.55 0.09668544 -0.1546388 -14.1033146 -0.7046388 2
#> 5 1 -5.40 -3.30 0.28026040 -0.7484327 -5.1197396 -4.0484327 2
#> 6 1 -4.10 -2.55 0.78798338 -1.1693809 -3.3120166 -3.7193809 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6820 -37050 5450
#> initial value 998.131940
#> iter 2 value 856.364102
#> iter 3 value 852.497585
#> iter 4 value 849.295669
#> iter 5 value 801.178253
#> iter 6 value 790.837985
#> iter 7 value 788.802751
#> iter 8 value 788.745492
#> iter 9 value 788.745347
#> iter 10 value 788.745334
#> iter 11 value 788.745313
#> iter 12 value 788.745289
#> iter 12 value 788.745289
#> iter 12 value 788.745289
#> final value 788.745289
#> converged
#> This is Run number 157
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.86526348 1.9245940 0.3152635 -11.2754060 1
#> 2 1 -3.10 -5.40 0.03324372 -0.3172190 -3.0667563 -5.7172190 1
#> 3 1 -14.60 -12.20 0.55125988 -0.8579482 -14.0487401 -13.0579482 2
#> 4 1 -14.20 -0.55 -0.54561015 -0.2495503 -14.7456102 -0.7995503 2
#> 5 1 -5.40 -3.30 -0.74882950 0.7383848 -6.1488295 -2.5616152 2
#> 6 1 -4.10 -2.55 -0.33919757 -0.2101050 -4.4391976 -2.7601050 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6800 -37425 6600
#> initial value 998.131940
#> iter 2 value 845.063651
#> iter 3 value 840.552628
#> iter 4 value 838.796081
#> iter 5 value 789.555862
#> iter 6 value 778.985069
#> iter 7 value 777.310498
#> iter 8 value 777.274389
#> iter 9 value 777.274351
#> iter 10 value 777.274334
#> iter 11 value 777.274277
#> iter 12 value 777.274237
#> iter 12 value 777.274237
#> iter 12 value 777.274237
#> final value 777.274237
#> converged
#> This is Run number 158
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.042608767 0.9683149 1.4926088 -12.2316851 1
#> 2 1 -3.10 -5.40 2.403175451 0.3726447 -0.6968245 -5.0273553 1
#> 3 1 -14.60 -12.20 1.146536239 -0.5983689 -13.4534638 -12.7983689 2
#> 4 1 -14.20 -0.55 1.022128516 -0.1684058 -13.1778715 -0.7184058 2
#> 5 1 -5.40 -3.30 0.002690226 1.0085020 -5.3973098 -2.2914980 2
#> 6 1 -4.10 -2.55 0.979985912 1.3673395 -3.1200141 -1.1826605 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6300 -37200 6725
#> initial value 998.131940
#> iter 2 value 847.619325
#> iter 3 value 841.771464
#> iter 4 value 837.657162
#> iter 5 value 788.294771
#> iter 6 value 777.932843
#> iter 7 value 776.279655
#> iter 8 value 776.244838
#> iter 8 value 776.244835
#> final value 776.244835
#> converged
#> This is Run number 159
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.64804550 -0.3515795 -1.198045 -13.5515795 1
#> 2 1 -3.10 -5.40 -0.33809165 0.6835371 -3.438092 -4.7164629 1
#> 3 1 -14.60 -12.20 1.98192407 0.8772060 -12.618076 -11.3227940 2
#> 4 1 -14.20 -0.55 -0.84946519 -0.2933119 -15.049465 -0.8433119 2
#> 5 1 -5.40 -3.30 -0.07987132 1.0474637 -5.479871 -2.2525363 2
#> 6 1 -4.10 -2.55 1.64529898 -0.4335788 -2.454701 -2.9835788 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7160 -37025 6500
#> initial value 998.131940
#> iter 2 value 850.703302
#> iter 3 value 847.658482
#> iter 4 value 847.337632
#> iter 5 value 796.775064
#> iter 6 value 786.247885
#> iter 7 value 784.518831
#> iter 8 value 784.480096
#> iter 9 value 784.480038
#> iter 10 value 784.480017
#> iter 11 value 784.479961
#> iter 12 value 784.479916
#> iter 12 value 784.479916
#> iter 12 value 784.479916
#> final value 784.479916
#> converged
#> This is Run number 160
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.98423829 -0.50471324 0.4342383 -13.7047132 1
#> 2 1 -3.10 -5.40 2.18799357 3.55256637 -0.9120064 -1.8474336 1
#> 3 1 -14.60 -12.20 -0.08168934 -0.23672185 -14.6816893 -12.4367219 2
#> 4 1 -14.20 -0.55 2.83752470 -0.05864938 -11.3624753 -0.6086494 2
#> 5 1 -5.40 -3.30 3.69107620 -0.30412236 -1.7089238 -3.6041224 1
#> 6 1 -4.10 -2.55 2.00181237 0.87242841 -2.0981876 -1.6775716 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7180 -37500 6625
#> initial value 998.131940
#> iter 2 value 843.543368
#> iter 3 value 839.745284
#> iter 4 value 839.288278
#> iter 5 value 790.016392
#> iter 6 value 779.328853
#> iter 7 value 777.662118
#> iter 8 value 777.626563
#> iter 9 value 777.626542
#> iter 10 value 777.626521
#> iter 11 value 777.626460
#> iter 12 value 777.626388
#> iter 12 value 777.626388
#> iter 12 value 777.626388
#> final value 777.626388
#> converged
#> This is Run number 161
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.8308997 0.1511761 0.2808997 -13.04882394 1
#> 2 1 -3.10 -5.40 -0.3026536 -0.3965300 -3.4026536 -5.79653001 1
#> 3 1 -14.60 -12.20 1.5247940 3.3724470 -13.0752060 -8.82755300 2
#> 4 1 -14.20 -0.55 1.6461505 0.6476817 -12.5538495 0.09768166 2
#> 5 1 -5.40 -3.30 0.5119753 -0.8752973 -4.8880247 -4.17529731 2
#> 6 1 -4.10 -2.55 1.2975058 -0.2799402 -2.8024942 -2.82994021 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7280 -37675 5650
#> initial value 998.131940
#> iter 2 value 846.468852
#> iter 3 value 843.029472
#> iter 4 value 841.688044
#> iter 5 value 794.528208
#> iter 6 value 783.828189
#> iter 7 value 781.894795
#> iter 8 value 781.840952
#> iter 9 value 781.840840
#> iter 10 value 781.840825
#> iter 11 value 781.840794
#> iter 12 value 781.840754
#> iter 12 value 781.840754
#> iter 12 value 781.840754
#> final value 781.840754
#> converged
#> This is Run number 162
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.6280295 -1.3169388 2.078030 -14.5169388 1
#> 2 1 -3.10 -5.40 -0.3514191 0.1244344 -3.451419 -5.2755656 1
#> 3 1 -14.60 -12.20 -0.7427355 0.5991061 -15.342735 -11.6008939 2
#> 4 1 -14.20 -0.55 1.1820872 0.9149136 -13.017913 0.3649136 2
#> 5 1 -5.40 -3.30 0.7547262 -0.2767088 -4.645274 -3.5767088 2
#> 6 1 -4.10 -2.55 0.2586815 -0.7564654 -3.841319 -3.3064654 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6000 -35925 5575
#> initial value 998.131940
#> iter 2 value 870.520626
#> iter 3 value 865.348006
#> iter 4 value 858.664730
#> iter 5 value 808.581730
#> iter 6 value 798.827040
#> iter 7 value 796.846565
#> iter 8 value 796.796021
#> iter 9 value 796.795907
#> iter 9 value 796.795903
#> iter 9 value 796.795903
#> final value 796.795903
#> converged
#> This is Run number 163
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.53135314 -0.02147069 1.981353 -13.221471 1
#> 2 1 -3.10 -5.40 2.60056005 -0.27317562 -0.499440 -5.673176 1
#> 3 1 -14.60 -12.20 -0.88184079 1.84380732 -15.481841 -10.356193 2
#> 4 1 -14.20 -0.55 -1.28708662 -0.55431239 -15.487087 -1.104312 2
#> 5 1 -5.40 -3.30 0.02699625 0.45032041 -5.373004 -2.849680 2
#> 6 1 -4.10 -2.55 0.31326205 -0.11151226 -3.786738 -2.661512 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7080 -37025 6475
#> initial value 998.131940
#> iter 2 value 850.934562
#> iter 3 value 847.785159
#> iter 4 value 847.266300
#> iter 5 value 796.739741
#> iter 6 value 786.226590
#> iter 7 value 784.490588
#> iter 8 value 784.451468
#> iter 9 value 784.451412
#> iter 10 value 784.451389
#> iter 11 value 784.451333
#> iter 12 value 784.451290
#> iter 12 value 784.451290
#> iter 12 value 784.451290
#> final value 784.451290
#> converged
#> This is Run number 164
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.8413059 -0.22802083 0.2913059 -13.428021 1
#> 2 1 -3.10 -5.40 0.9187617 4.26342391 -2.1812383 -1.136576 2
#> 3 1 -14.60 -12.20 0.9298211 -0.07119918 -13.6701789 -12.271199 2
#> 4 1 -14.20 -0.55 2.9484064 1.88454552 -11.2515936 1.334546 2
#> 5 1 -5.40 -3.30 -0.3949838 0.81858284 -5.7949838 -2.481417 2
#> 6 1 -4.10 -2.55 3.0583092 -1.25157921 -1.0416908 -3.801579 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7220 -36525 5100
#> initial value 998.131940
#> iter 2 value 864.554757
#> iter 3 value 862.573271
#> iter 4 value 861.469610
#> iter 5 value 811.586557
#> iter 6 value 801.549898
#> iter 7 value 799.256002
#> iter 8 value 799.187895
#> iter 9 value 799.187639
#> iter 9 value 799.187627
#> iter 9 value 799.187627
#> final value 799.187627
#> converged
#> This is Run number 165
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.2921278 -0.85231969 -0.8421278 -14.0523197 1
#> 2 1 -3.10 -5.40 2.3486807 0.41798887 -0.7513193 -4.9820111 1
#> 3 1 -14.60 -12.20 1.0087430 -0.08755500 -13.5912570 -12.2875550 2
#> 4 1 -14.20 -0.55 -0.7692039 -0.14180984 -14.9692039 -0.6918098 2
#> 5 1 -5.40 -3.30 2.8585370 -0.04066433 -2.5414630 -3.3406643 1
#> 6 1 -4.10 -2.55 -1.3816487 0.85842471 -5.4816487 -1.6915753 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6460 -36475 7150
#> initial value 998.131940
#> iter 2 value 854.485129
#> iter 3 value 850.739753
#> iter 4 value 849.366392
#> iter 5 value 796.221261
#> iter 6 value 786.035766
#> iter 7 value 784.404465
#> iter 8 value 784.374124
#> iter 9 value 784.374081
#> iter 10 value 784.374054
#> iter 11 value 784.374002
#> iter 12 value 784.373968
#> iter 12 value 784.373968
#> iter 12 value 784.373968
#> final value 784.373968
#> converged
#> This is Run number 166
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.5249282 4.3644315 0.9749282 -8.835568 1
#> 2 1 -3.10 -5.40 3.3753319 1.4394727 0.2753319 -3.960527 1
#> 3 1 -14.60 -12.20 -0.8044044 0.3471268 -15.4044044 -11.852873 2
#> 4 1 -14.20 -0.55 1.3727465 -1.0807581 -12.8272535 -1.630758 2
#> 5 1 -5.40 -3.30 0.5764820 -0.9081824 -4.8235180 -4.208182 2
#> 6 1 -4.10 -2.55 -0.4551412 3.5793436 -4.5551412 1.029344 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6360 -36650 7275
#> initial value 998.131940
#> iter 2 value 851.459883
#> iter 3 value 847.044851
#> iter 4 value 845.203666
#> iter 5 value 792.501025
#> iter 6 value 782.297617
#> iter 7 value 780.685579
#> iter 8 value 780.656332
#> iter 9 value 780.656284
#> iter 10 value 780.656251
#> iter 11 value 780.656201
#> iter 12 value 780.656177
#> iter 12 value 780.656177
#> iter 12 value 780.656177
#> final value 780.656177
#> converged
#> This is Run number 167
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.776845301 -1.0730688 0.2268453 -14.2730688 1
#> 2 1 -3.10 -5.40 0.271734071 0.9077378 -2.8282659 -4.4922622 1
#> 3 1 -14.60 -12.20 -0.580769882 0.7158352 -15.1807699 -11.4841648 2
#> 4 1 -14.20 -0.55 2.667496476 -0.1994776 -11.5325035 -0.7494776 2
#> 5 1 -5.40 -3.30 -0.572513556 0.0909715 -5.9725136 -3.2090285 2
#> 6 1 -4.10 -2.55 0.003957326 -0.7043514 -4.0960427 -3.2543514 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6900 -36450 4825
#> initial value 998.131940
#> iter 2 value 867.070910
#> iter 3 value 864.152618
#> iter 4 value 861.144867
#> iter 5 value 812.177723
#> iter 6 value 802.286610
#> iter 7 value 799.903094
#> iter 8 value 799.830914
#> iter 9 value 799.830633
#> iter 9 value 799.830632
#> iter 9 value 799.830632
#> final value 799.830632
#> converged
#> This is Run number 168
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.18369870 2.06192618 -0.3663013 -11.138074 1
#> 2 1 -3.10 -5.40 1.54943615 -0.43374961 -1.5505638 -5.833750 1
#> 3 1 -14.60 -12.20 -0.09053966 -0.02011893 -14.6905397 -12.220119 2
#> 4 1 -14.20 -0.55 0.73729110 1.42748404 -13.4627089 0.877484 2
#> 5 1 -5.40 -3.30 -0.55044007 1.63056506 -5.9504401 -1.669435 2
#> 6 1 -4.10 -2.55 -1.56565974 0.08723830 -5.6656597 -2.462762 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7180 -38225 5725
#> initial value 998.131940
#> iter 2 value 838.479667
#> iter 3 value 833.843400
#> iter 4 value 831.423181
#> iter 5 value 786.230389
#> iter 6 value 775.367802
#> iter 7 value 773.546873
#> iter 8 value 773.497520
#> iter 9 value 773.497460
#> iter 9 value 773.497454
#> iter 9 value 773.497454
#> final value 773.497454
#> converged
#> This is Run number 169
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.9286120 0.04595374 -1.478612 -13.1540463 1
#> 2 1 -3.10 -5.40 0.7190665 -0.72603317 -2.380934 -6.1260332 1
#> 3 1 -14.60 -12.20 -0.5503876 -1.53901400 -15.150388 -13.7390140 2
#> 4 1 -14.20 -0.55 0.1863202 0.76694562 -14.013680 0.2169456 2
#> 5 1 -5.40 -3.30 0.7399865 2.91370843 -4.660014 -0.3862916 2
#> 6 1 -4.10 -2.55 1.7889054 -1.16264300 -2.311095 -3.7126430 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5980 -36825 6600
#> initial value 998.131940
#> iter 2 value 853.405403
#> iter 3 value 846.897669
#> iter 4 value 840.745502
#> iter 5 value 791.239045
#> iter 6 value 781.067992
#> iter 7 value 779.387023
#> iter 8 value 779.350668
#> iter 9 value 779.350649
#> iter 9 value 779.350639
#> iter 10 value 779.350619
#> iter 11 value 779.350605
#> iter 11 value 779.350602
#> iter 11 value 779.350602
#> final value 779.350602
#> converged
#> This is Run number 170
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.3162649 1.3153358 -0.8662649 -11.8846642 1
#> 2 1 -3.10 -5.40 1.9045576 1.9437124 -1.1954424 -3.4562876 1
#> 3 1 -14.60 -12.20 0.5248672 -0.6558654 -14.0751328 -12.8558654 2
#> 4 1 -14.20 -0.55 5.4193907 0.3937133 -8.7806093 -0.1562867 2
#> 5 1 -5.40 -3.30 -1.0395705 5.1028961 -6.4395705 1.8028961 2
#> 6 1 -4.10 -2.55 -0.6281245 -0.3322676 -4.7281245 -2.8822676 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6600 -38100 6900
#> initial value 998.131940
#> iter 2 value 833.983521
#> iter 3 value 827.296982
#> iter 4 value 823.959623
#> iter 5 value 776.910945
#> iter 6 value 766.299992
#> iter 7 value 764.719548
#> iter 8 value 764.687200
#> iter 9 value 764.687116
#> iter 10 value 764.687065
#> iter 11 value 764.687022
#> iter 11 value 764.687018
#> iter 11 value 764.687018
#> final value 764.687018
#> converged
#> This is Run number 171
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.9349211 -0.0262689 2.384921 -13.2262689 1
#> 2 1 -3.10 -5.40 0.6742470 3.1523658 -2.425753 -2.2476342 2
#> 3 1 -14.60 -12.20 0.2348336 -0.4657631 -14.365166 -12.6657631 2
#> 4 1 -14.20 -0.55 0.3840841 0.7015523 -13.815916 0.1515523 2
#> 5 1 -5.40 -3.30 4.0806165 0.8026223 -1.319383 -2.4973777 1
#> 6 1 -4.10 -2.55 0.2595403 1.5016443 -3.840460 -1.0483557 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7200 -36575 5450
#> initial value 998.131940
#> iter 2 value 862.242410
#> iter 3 value 860.186601
#> iter 4 value 859.376187
#> iter 5 value 809.053168
#> iter 6 value 798.885187
#> iter 7 value 796.757968
#> iter 8 value 796.697834
#> iter 9 value 796.697639
#> iter 10 value 796.697622
#> iter 11 value 796.697589
#> iter 12 value 796.697545
#> iter 12 value 796.697545
#> iter 12 value 796.697545
#> final value 796.697545
#> converged
#> This is Run number 172
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.7783030 -0.7799000 0.228303 -13.9799000 1
#> 2 1 -3.10 -5.40 -1.1799415 0.6869201 -4.279941 -4.7130799 1
#> 3 1 -14.60 -12.20 4.7298040 0.1748285 -9.870196 -12.0251715 1
#> 4 1 -14.20 -0.55 -0.3544671 -0.4078103 -14.554467 -0.9578103 2
#> 5 1 -5.40 -3.30 0.2404823 -0.1848079 -5.159518 -3.4848079 2
#> 6 1 -4.10 -2.55 -0.3009539 1.6983120 -4.400954 -0.8516880 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6520 -36675 6150
#> initial value 998.131940
#> iter 2 value 857.808967
#> iter 3 value 853.820907
#> iter 4 value 850.851396
#> iter 5 value 800.406180
#> iter 6 value 790.170235
#> iter 7 value 788.357823
#> iter 8 value 788.314723
#> iter 9 value 788.314662
#> iter 10 value 788.314647
#> iter 11 value 788.314608
#> iter 12 value 788.314572
#> iter 12 value 788.314572
#> iter 12 value 788.314572
#> final value 788.314572
#> converged
#> This is Run number 173
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.5596155 -1.25697478 0.009615462 -14.45697478 1
#> 2 1 -3.10 -5.40 -1.1680902 -0.67666372 -4.268090150 -6.07666372 1
#> 3 1 -14.60 -12.20 -0.2779217 1.60558969 -14.877921663 -10.59441031 2
#> 4 1 -14.20 -0.55 0.7713265 0.49717469 -13.428673528 -0.05282531 2
#> 5 1 -5.40 -3.30 0.9059446 -0.83921190 -4.494055411 -4.13921190 2
#> 6 1 -4.10 -2.55 0.4769119 -0.03321431 -3.623088117 -2.58321431 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6820 -36050 5225
#> initial value 998.131940
#> iter 2 value 870.355810
#> iter 3 value 868.057773
#> iter 4 value 865.966977
#> iter 5 value 814.883464
#> iter 6 value 805.069986
#> iter 7 value 802.870828
#> iter 8 value 802.809868
#> iter 9 value 802.809668
#> iter 10 value 802.809654
#> iter 11 value 802.809629
#> iter 12 value 802.809597
#> iter 12 value 802.809597
#> iter 12 value 802.809597
#> final value 802.809597
#> converged
#> This is Run number 174
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.3433904 1.26967683 1.793390 -11.930323 1
#> 2 1 -3.10 -5.40 1.6880410 0.25969912 -1.411959 -5.140301 1
#> 3 1 -14.60 -12.20 1.6301231 -0.07850569 -12.969877 -12.278506 2
#> 4 1 -14.20 -0.55 -0.3573498 -0.15091497 -14.557350 -0.700915 2
#> 5 1 -5.40 -3.30 2.1244139 -1.45276183 -3.275586 -4.752762 1
#> 6 1 -4.10 -2.55 0.2331520 -0.11520470 -3.866848 -2.665205 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6440 -36725 6900
#> initial value 998.131940
#> iter 2 value 852.812320
#> iter 3 value 848.542874
#> iter 4 value 846.412397
#> iter 5 value 794.628494
#> iter 6 value 784.367067
#> iter 7 value 782.710485
#> iter 8 value 782.677492
#> iter 9 value 782.677463
#> iter 10 value 782.677444
#> iter 11 value 782.677388
#> iter 12 value 782.677344
#> iter 12 value 782.677344
#> iter 12 value 782.677344
#> final value 782.677344
#> converged
#> This is Run number 175
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 4.3552137 0.4954863 3.805214 -12.7045137 1
#> 2 1 -3.10 -5.40 0.9137171 0.8076059 -2.186283 -4.5923941 1
#> 3 1 -14.60 -12.20 -0.1490423 1.5188402 -14.749042 -10.6811598 2
#> 4 1 -14.20 -0.55 0.3678268 0.8999636 -13.832173 0.3499636 2
#> 5 1 -5.40 -3.30 0.2204986 -0.9888253 -5.179501 -4.2888253 2
#> 6 1 -4.10 -2.55 -0.9124282 1.5884201 -5.012428 -0.9615799 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6980 -35900 5550
#> initial value 998.131940
#> iter 2 value 870.493632
#> iter 3 value 868.912187
#> iter 4 value 868.082057
#> iter 5 value 815.690725
#> iter 6 value 805.851488
#> iter 7 value 803.756343
#> iter 8 value 803.700596
#> iter 9 value 803.700419
#> iter 10 value 803.700397
#> iter 11 value 803.700358
#> iter 12 value 803.700315
#> iter 12 value 803.700315
#> iter 12 value 803.700315
#> final value 803.700315
#> converged
#> This is Run number 176
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.0048433 0.71432970 0.4548433 -12.4856703 1
#> 2 1 -3.10 -5.40 -1.1875471 1.08722789 -4.2875471 -4.3127721 1
#> 3 1 -14.60 -12.20 -0.5087251 1.21547825 -15.1087251 -10.9845217 2
#> 4 1 -14.20 -0.55 -0.4367762 0.19615659 -14.6367762 -0.3538434 2
#> 5 1 -5.40 -3.30 2.9519539 0.07814871 -2.4480461 -3.2218513 1
#> 6 1 -4.10 -2.55 0.8461172 1.67182393 -3.2538828 -0.8781761 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7480 -37050 4875
#> initial value 998.131940
#> iter 2 value 858.426845
#> iter 3 value 856.313756
#> iter 4 value 855.353080
#> iter 5 value 807.280456
#> iter 6 value 797.052011
#> iter 7 value 794.648417
#> iter 8 value 794.571630
#> iter 9 value 794.571305
#> iter 9 value 794.571301
#> iter 9 value 794.571301
#> final value 794.571301
#> converged
#> This is Run number 177
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.3027170 0.31967656 -0.852717 -12.8803234 1
#> 2 1 -3.10 -5.40 -0.2040689 2.24270595 -3.304069 -3.1572940 2
#> 3 1 -14.60 -12.20 0.6230689 2.39778169 -13.976931 -9.8022183 2
#> 4 1 -14.20 -0.55 3.9486658 0.19780652 -10.251334 -0.3521935 2
#> 5 1 -5.40 -3.30 3.6831444 -0.01272369 -1.716856 -3.3127237 1
#> 6 1 -4.10 -2.55 -0.7395783 1.45583884 -4.839578 -1.0941612 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6580 -36925 6725
#> initial value 998.131940
#> iter 2 value 851.173952
#> iter 3 value 846.951058
#> iter 4 value 844.972849
#> iter 5 value 794.042059
#> iter 6 value 783.678122
#> iter 7 value 781.999772
#> iter 8 value 781.964767
#> iter 9 value 781.964712
#> iter 10 value 781.964672
#> iter 11 value 781.964644
#> iter 12 value 781.964617
#> iter 12 value 781.964617
#> iter 12 value 781.964617
#> final value 781.964617
#> converged
#> This is Run number 178
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.69585871 1.4702467 0.1458587 -11.729753 1
#> 2 1 -3.10 -5.40 -0.64591393 2.9974533 -3.7459139 -2.402547 2
#> 3 1 -14.60 -12.20 -0.15346826 -0.9135248 -14.7534683 -13.113525 2
#> 4 1 -14.20 -0.55 1.80467176 1.1006180 -12.3953282 0.550618 2
#> 5 1 -5.40 -3.30 -0.12765690 7.4710265 -5.5276569 4.171026 2
#> 6 1 -4.10 -2.55 -0.05030021 0.8397626 -4.1503002 -1.710237 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7200 -39000 6400
#> initial value 998.131940
#> iter 2 value 823.444799
#> iter 3 value 817.256240
#> iter 4 value 815.056525
#> iter 5 value 771.322952
#> iter 6 value 760.363245
#> iter 7 value 758.790704
#> iter 8 value 758.755608
#> iter 9 value 758.755505
#> iter 10 value 758.755447
#> iter 11 value 758.755397
#> iter 11 value 758.755391
#> iter 11 value 758.755391
#> final value 758.755391
#> converged
#> This is Run number 179
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.7609547 -0.34051807 0.2109547 -13.540518 1
#> 2 1 -3.10 -5.40 -0.2358056 -0.90012847 -3.3358056 -6.300128 1
#> 3 1 -14.60 -12.20 -0.3123379 -0.17230518 -14.9123379 -12.372305 2
#> 4 1 -14.20 -0.55 1.0348437 1.80075730 -13.1651563 1.250757 2
#> 5 1 -5.40 -3.30 2.6193158 -0.08105251 -2.7806842 -3.381053 1
#> 6 1 -4.10 -2.55 1.4329158 0.38303446 -2.6670842 -2.166966 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6440 -35950 6850
#> initial value 998.131940
#> iter 2 value 863.022572
#> iter 3 value 860.282364
#> iter 4 value 858.999055
#> iter 5 value 804.755317
#> iter 6 value 794.770359
#> iter 7 value 793.081429
#> iter 8 value 793.047726
#> iter 9 value 793.047710
#> iter 10 value 793.047690
#> iter 11 value 793.047632
#> iter 12 value 793.047562
#> iter 12 value 793.047562
#> iter 12 value 793.047562
#> final value 793.047562
#> converged
#> This is Run number 180
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.59325170 2.6136817 0.0432517 -10.586318 1
#> 2 1 -3.10 -5.40 0.06205956 -1.1647375 -3.0379404 -6.564737 1
#> 3 1 -14.60 -12.20 -0.28637859 -1.4855725 -14.8863786 -13.685572 2
#> 4 1 -14.20 -0.55 0.56999834 -0.4526095 -13.6300017 -1.002610 2
#> 5 1 -5.40 -3.30 1.54556195 -0.1931132 -3.8544380 -3.493113 2
#> 6 1 -4.10 -2.55 1.12013120 -1.0150913 -2.9798688 -3.565091 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7100 -37525 6450
#> initial value 998.131940
#> iter 2 value 844.319701
#> iter 3 value 840.440901
#> iter 4 value 839.576371
#> iter 5 value 790.676328
#> iter 6 value 779.998220
#> iter 7 value 778.294162
#> iter 8 value 778.255819
#> iter 9 value 778.255762
#> iter 10 value 778.255715
#> iter 11 value 778.255691
#> iter 12 value 778.255653
#> iter 12 value 778.255653
#> iter 12 value 778.255653
#> final value 778.255653
#> converged
#> This is Run number 181
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.20925082 -0.3772826 -0.7592508 -13.5772826 1
#> 2 1 -3.10 -5.40 -0.66938934 0.3988336 -3.7693893 -5.0011664 1
#> 3 1 -14.60 -12.20 1.05359101 -0.9123324 -13.5464090 -13.1123324 2
#> 4 1 -14.20 -0.55 0.03034771 -0.1221365 -14.1696523 -0.6721365 2
#> 5 1 -5.40 -3.30 2.32708710 0.8290166 -3.0729129 -2.4709834 2
#> 6 1 -4.10 -2.55 1.37400425 -0.2376031 -2.7259957 -2.7876031 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6840 -36425 6250
#> initial value 998.131940
#> iter 2 value 860.272691
#> iter 3 value 857.664009
#> iter 4 value 856.679230
#> iter 5 value 804.745097
#> iter 6 value 794.533878
#> iter 7 value 792.710412
#> iter 8 value 792.667380
#> iter 9 value 792.667300
#> iter 10 value 792.667270
#> iter 11 value 792.667221
#> iter 12 value 792.667184
#> iter 12 value 792.667184
#> iter 12 value 792.667184
#> final value 792.667184
#> converged
#> This is Run number 182
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.1796479 -0.28839411 -0.7296479 -13.4883941 1
#> 2 1 -3.10 -5.40 -0.3588552 2.11732162 -3.4588552 -3.2826784 2
#> 3 1 -14.60 -12.20 -1.7779983 -0.19889881 -16.3779983 -12.3988988 2
#> 4 1 -14.20 -0.55 0.6528162 1.54972330 -13.5471838 0.9997233 2
#> 5 1 -5.40 -3.30 0.7016938 0.04535965 -4.6983062 -3.2546403 2
#> 6 1 -4.10 -2.55 0.1617755 -0.55842689 -3.9382245 -3.1084269 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6640 -34700 5250
#> initial value 998.131940
#> iter 2 value 886.530088
#> iter 3 value 885.738060
#> iter 4 value 884.496810
#> iter 5 value 829.520106
#> iter 6 value 820.432580
#> iter 7 value 818.287348
#> iter 8 value 818.234532
#> iter 9 value 818.234360
#> iter 10 value 818.234335
#> iter 11 value 818.234296
#> iter 12 value 818.234265
#> iter 12 value 818.234265
#> iter 12 value 818.234265
#> final value 818.234265
#> converged
#> This is Run number 183
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.8852002 1.355328 -1.435200 -11.8446722 1
#> 2 1 -3.10 -5.40 0.7693151 3.489260 -2.330685 -1.9107395 2
#> 3 1 -14.60 -12.20 -0.8575837 1.051173 -15.457584 -11.1488269 2
#> 4 1 -14.20 -0.55 -0.5654713 -1.242760 -14.765471 -1.7927601 2
#> 5 1 -5.40 -3.30 2.0545579 2.339840 -3.345442 -0.9601604 2
#> 6 1 -4.10 -2.55 1.0757534 1.557491 -3.024247 -0.9925088 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6720 -35875 3875
#> initial value 998.131940
#> iter 2 value 878.244693
#> iter 3 value 874.526560
#> iter 4 value 869.189019
#> iter 5 value 821.226007
#> iter 6 value 812.039988
#> iter 7 value 809.085426
#> iter 8 value 808.988469
#> iter 9 value 808.987877
#> iter 10 value 808.987853
#> iter 10 value 808.987853
#> iter 11 value 808.987841
#> iter 11 value 808.987839
#> iter 11 value 808.987839
#> final value 808.987839
#> converged
#> This is Run number 184
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.7994820 0.65631846 0.249482 -12.5436815 1
#> 2 1 -3.10 -5.40 0.7171542 0.61481509 -2.382846 -4.7851849 1
#> 3 1 -14.60 -12.20 -0.5311463 1.38650221 -15.131146 -10.8134978 2
#> 4 1 -14.20 -0.55 1.7195718 -0.05897955 -12.480428 -0.6089796 2
#> 5 1 -5.40 -3.30 -0.5507568 2.35104944 -5.950757 -0.9489506 2
#> 6 1 -4.10 -2.55 0.4832677 -0.77308813 -3.616732 -3.3230881 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6400 -35875 5875
#> initial value 998.131940
#> iter 2 value 869.518725
#> iter 3 value 866.514820
#> iter 4 value 863.587279
#> iter 5 value 811.262623
#> iter 6 value 801.430014
#> iter 7 value 799.515441
#> iter 8 value 799.469048
#> iter 9 value 799.468951
#> iter 10 value 799.468927
#> iter 11 value 799.468891
#> iter 12 value 799.468866
#> iter 12 value 799.468866
#> iter 12 value 799.468866
#> final value 799.468866
#> converged
#> This is Run number 185
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.2098898 1.57259500 -0.3401102 -11.627405 1
#> 2 1 -3.10 -5.40 1.2949007 -0.40213365 -1.8050993 -5.802134 1
#> 3 1 -14.60 -12.20 1.4838098 1.86475111 -13.1161902 -10.335249 2
#> 4 1 -14.20 -0.55 0.4464334 -0.97925331 -13.7535666 -1.529253 2
#> 5 1 -5.40 -3.30 0.9827652 0.09450328 -4.4172348 -3.205497 2
#> 6 1 -4.10 -2.55 0.8247078 0.40898184 -3.2752922 -2.141018 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6380 -35875 4950
#> initial value 998.131940
#> iter 2 value 874.044398
#> iter 3 value 870.129266
#> iter 4 value 864.972121
#> iter 5 value 815.158864
#> iter 6 value 805.540093
#> iter 7 value 803.267534
#> iter 8 value 803.203287
#> iter 9 value 803.203064
#> iter 10 value 803.203052
#> iter 10 value 803.203048
#> iter 10 value 803.203043
#> final value 803.203043
#> converged
#> This is Run number 186
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.1596379 3.6532638 0.6096379 -9.5467362 1
#> 2 1 -3.10 -5.40 -0.9142328 2.4479012 -4.0142328 -2.9520988 2
#> 3 1 -14.60 -12.20 -0.6820099 -0.3365390 -15.2820099 -12.5365390 2
#> 4 1 -14.20 -0.55 1.3754941 2.6630646 -12.8245059 2.1130646 2
#> 5 1 -5.40 -3.30 0.8108964 -0.2539947 -4.5891036 -3.5539947 2
#> 6 1 -4.10 -2.55 1.4885714 2.2835724 -2.6114286 -0.2664276 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7000 -37475 6200
#> initial value 998.131940
#> iter 2 value 846.528807
#> iter 3 value 842.584994
#> iter 4 value 841.072793
#> iter 5 value 792.527834
#> iter 6 value 781.896612
#> iter 7 value 780.130701
#> iter 8 value 780.088214
#> iter 9 value 780.088162
#> iter 10 value 780.088138
#> iter 11 value 780.088091
#> iter 12 value 780.088055
#> iter 12 value 780.088055
#> iter 12 value 780.088055
#> final value 780.088055
#> converged
#> This is Run number 187
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.5096554 2.173751e-06 -1.059655 -13.1999978 1
#> 2 1 -3.10 -5.40 0.8492934 1.223339e+00 -2.250707 -4.1766613 1
#> 3 1 -14.60 -12.20 -0.7928258 2.577355e-02 -15.392826 -12.1742265 2
#> 4 1 -14.20 -0.55 0.8130195 2.997825e-01 -13.386981 -0.2502175 2
#> 5 1 -5.40 -3.30 0.2692675 1.039468e+00 -5.130732 -2.2605320 2
#> 6 1 -4.10 -2.55 -0.6322402 1.442302e+00 -4.732240 -1.1076981 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5740 -35975 6850
#> initial value 998.131940
#> iter 2 value 862.828213
#> iter 3 value 857.449927
#> iter 4 value 851.923687
#> iter 5 value 799.179233
#> iter 6 value 789.356685
#> iter 7 value 787.694419
#> iter 8 value 787.661589
#> iter 9 value 787.661571
#> iter 10 value 787.661558
#> iter 11 value 787.661521
#> iter 12 value 787.661492
#> iter 12 value 787.661492
#> iter 12 value 787.661492
#> final value 787.661492
#> converged
#> This is Run number 188
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.0598586 0.005772754 0.5098586 -13.1942272 1
#> 2 1 -3.10 -5.40 -0.2856184 -0.458176471 -3.3856184 -5.8581765 1
#> 3 1 -14.60 -12.20 0.1730072 -0.672164000 -14.4269928 -12.8721640 2
#> 4 1 -14.20 -0.55 3.4400857 1.478677426 -10.7599143 0.9286774 2
#> 5 1 -5.40 -3.30 0.9852594 -0.507106403 -4.4147406 -3.8071064 2
#> 6 1 -4.10 -2.55 1.2221485 0.696088790 -2.8778515 -1.8539112 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6640 -37425 5900
#> initial value 998.131940
#> iter 2 value 849.111345
#> iter 3 value 843.992364
#> iter 4 value 839.915195
#> iter 5 value 792.566317
#> iter 6 value 782.057448
#> iter 7 value 780.229799
#> iter 8 value 780.182910
#> iter 9 value 780.182852
#> iter 10 value 780.182839
#> iter 11 value 780.182812
#> iter 12 value 780.182787
#> iter 12 value 780.182787
#> iter 12 value 780.182787
#> final value 780.182787
#> converged
#> This is Run number 189
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.66213940 -0.4828375 0.1121394 -13.682838 1
#> 2 1 -3.10 -5.40 -1.20610021 -0.2589377 -4.3061002 -5.658938 1
#> 3 1 -14.60 -12.20 -0.06551797 0.1220047 -14.6655180 -12.077995 2
#> 4 1 -14.20 -0.55 0.21174171 -0.5780381 -13.9882583 -1.128038 2
#> 5 1 -5.40 -3.30 3.08284613 1.9011606 -2.3171539 -1.398839 2
#> 6 1 -4.10 -2.55 0.78175292 0.1035007 -3.3182471 -2.446499 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6200 -36425 7650
#> initial value 998.131940
#> iter 2 value 851.950427
#> iter 3 value 847.465638
#> iter 4 value 845.696127
#> iter 5 value 791.654307
#> iter 6 value 781.585760
#> iter 7 value 779.998397
#> iter 8 value 779.971935
#> iter 9 value 779.971872
#> iter 10 value 779.971828
#> iter 11 value 779.971785
#> iter 11 value 779.971780
#> iter 11 value 779.971780
#> final value 779.971780
#> converged
#> This is Run number 190
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.1199434 -0.47437419 1.569943 -13.6743742 1
#> 2 1 -3.10 -5.40 0.9936583 -0.09649975 -2.106342 -5.4964998 1
#> 3 1 -14.60 -12.20 1.0793994 -0.11757852 -13.520601 -12.3175785 2
#> 4 1 -14.20 -0.55 1.1038404 -0.23825704 -13.096160 -0.7882570 2
#> 5 1 -5.40 -3.30 0.4742471 2.70673240 -4.925753 -0.5932676 2
#> 6 1 -4.10 -2.55 0.7067174 0.13826026 -3.393283 -2.4117397 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7080 -36950 5700
#> initial value 998.131940
#> iter 2 value 856.202257
#> iter 3 value 853.359770
#> iter 4 value 852.066162
#> iter 5 value 802.603287
#> iter 6 value 792.216229
#> iter 7 value 790.236298
#> iter 8 value 790.182677
#> iter 9 value 790.182545
#> iter 10 value 790.182527
#> iter 11 value 790.182491
#> iter 12 value 790.182452
#> iter 12 value 790.182452
#> iter 12 value 790.182452
#> final value 790.182452
#> converged
#> This is Run number 191
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 3.4361780 -0.04810365 2.886178 -13.248104 1
#> 2 1 -3.10 -5.40 -0.2961198 3.10912066 -3.396120 -2.290879 2
#> 3 1 -14.60 -12.20 0.5002722 2.32373293 -14.099728 -9.876267 2
#> 4 1 -14.20 -0.55 3.9631503 -0.52677310 -10.236850 -1.076773 2
#> 5 1 -5.40 -3.30 2.6245975 -0.02509667 -2.775403 -3.325097 1
#> 6 1 -4.10 -2.55 -0.1688964 0.43596467 -4.268896 -2.114035 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7620 -37625 5150
#> initial value 998.131940
#> iter 2 value 849.208728
#> iter 3 value 846.658510
#> iter 4 value 845.957745
#> iter 5 value 799.179801
#> iter 6 value 788.575636
#> iter 7 value 786.378454
#> iter 8 value 786.309251
#> iter 9 value 786.309005
#> iter 9 value 786.308997
#> iter 9 value 786.308997
#> final value 786.308997
#> converged
#> This is Run number 192
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -1.1360482 -0.4900426 -1.686048 -13.690043 1
#> 2 1 -3.10 -5.40 -0.1272260 0.2995847 -3.227226 -5.100415 1
#> 3 1 -14.60 -12.20 1.0912501 2.7032901 -13.508750 -9.496710 2
#> 4 1 -14.20 -0.55 0.3287857 4.0371465 -13.871214 3.487147 2
#> 5 1 -5.40 -3.30 2.7278770 0.2373208 -2.672123 -3.062679 1
#> 6 1 -4.10 -2.55 -0.9850541 -1.0202291 -5.085054 -3.570229 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6060 -36050 5825
#> initial value 998.131940
#> iter 2 value 867.678384
#> iter 3 value 862.812978
#> iter 4 value 857.031815
#> iter 5 value 806.453465
#> iter 6 value 796.597548
#> iter 7 value 794.699384
#> iter 8 value 794.652934
#> iter 9 value 794.652849
#> iter 9 value 794.652838
#> iter 9 value 794.652838
#> final value 794.652838
#> converged
#> This is Run number 193
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.5940577 -1.0931780 2.044058 -14.2931780 1
#> 2 1 -3.10 -5.40 0.5756999 0.3919982 -2.524300 -5.0080018 1
#> 3 1 -14.60 -12.20 0.9025922 2.0984566 -13.697408 -10.1015434 2
#> 4 1 -14.20 -0.55 1.6624666 0.8011051 -12.537533 0.2511051 2
#> 5 1 -5.40 -3.30 -0.9733220 1.9572986 -6.373322 -1.3427014 2
#> 6 1 -4.10 -2.55 3.0217117 -0.3021996 -1.078288 -2.8521996 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5520 -35300 7250
#> initial value 998.131940
#> iter 2 value 868.584857
#> iter 3 value 864.216371
#> iter 4 value 859.384748
#> iter 5 value 803.653375
#> iter 6 value 794.143263
#> iter 7 value 792.529598
#> iter 8 value 792.501159
#> iter 9 value 792.501118
#> iter 10 value 792.501086
#> iter 11 value 792.501067
#> iter 12 value 792.501055
#> iter 12 value 792.501055
#> iter 12 value 792.501055
#> final value 792.501055
#> converged
#> This is Run number 194
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.79086420 1.8989593 0.2408642 -11.3010407 1
#> 2 1 -3.10 -5.40 1.75740614 1.1611140 -1.3425939 -4.2388860 1
#> 3 1 -14.60 -12.20 -0.09697232 2.5337831 -14.6969723 -9.6662169 2
#> 4 1 -14.20 -0.55 2.14213792 0.3470002 -12.0578621 -0.2029998 2
#> 5 1 -5.40 -3.30 -0.20917531 -0.1521680 -5.6091753 -3.4521680 2
#> 6 1 -4.10 -2.55 0.68734302 -0.5462565 -3.4126570 -3.0962565 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6700 -37375 6950
#> initial value 998.131940
#> iter 2 value 843.685275
#> iter 3 value 838.864187
#> iter 4 value 837.232820
#> iter 5 value 787.267622
#> iter 6 value 776.754674
#> iter 7 value 775.133951
#> iter 8 value 775.102104
#> iter 9 value 775.102053
#> iter 10 value 775.102014
#> iter 11 value 775.101959
#> iter 12 value 775.101936
#> iter 12 value 775.101936
#> iter 12 value 775.101936
#> final value 775.101936
#> converged
#> This is Run number 195
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.3553564 -1.118812273 0.8053564 -14.318812273 1
#> 2 1 -3.10 -5.40 -0.4695371 -0.901305784 -3.5695371 -6.301305784 1
#> 3 1 -14.60 -12.20 1.0286403 0.007499048 -13.5713597 -12.192500952 2
#> 4 1 -14.20 -0.55 1.0242284 0.552297749 -13.1757716 0.002297749 2
#> 5 1 -5.40 -3.30 0.1868646 0.025484406 -5.2131354 -3.274515594 2
#> 6 1 -4.10 -2.55 0.2420068 1.453917127 -3.8579932 -1.096082873 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6440 -35625 6175
#> initial value 998.131940
#> iter 2 value 870.955886
#> iter 3 value 868.684563
#> iter 4 value 866.841717
#> iter 5 value 812.941727
#> iter 6 value 803.172936
#> iter 7 value 801.333811
#> iter 8 value 801.291863
#> iter 9 value 801.291778
#> iter 10 value 801.291757
#> iter 11 value 801.291709
#> iter 12 value 801.291669
#> iter 12 value 801.291669
#> iter 12 value 801.291669
#> final value 801.291669
#> converged
#> This is Run number 196
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.05680836 -0.4021661 -0.4931916 -13.6021661 1
#> 2 1 -3.10 -5.40 3.92106971 4.1632178 0.8210697 -1.2367822 1
#> 3 1 -14.60 -12.20 0.34769978 -1.1078596 -14.2523002 -13.3078596 2
#> 4 1 -14.20 -0.55 0.70579900 0.7774788 -13.4942010 0.2274788 2
#> 5 1 -5.40 -3.30 -1.19645286 -0.3341694 -6.5964529 -3.6341694 2
#> 6 1 -4.10 -2.55 -0.92970397 0.9035829 -5.0297040 -1.6464171 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7120 -37350 6475
#> initial value 998.131940
#> iter 2 value 846.535155
#> iter 3 value 842.959247
#> iter 4 value 842.320660
#> iter 5 value 792.807565
#> iter 6 value 782.177254
#> iter 7 value 780.464578
#> iter 8 value 780.426169
#> iter 9 value 780.426123
#> iter 10 value 780.426110
#> iter 11 value 780.426056
#> iter 12 value 780.425998
#> iter 12 value 780.425998
#> iter 12 value 780.425998
#> final value 780.425998
#> converged
#> This is Run number 197
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.3565641 -0.3814313 -0.9065641 -13.581431 1
#> 2 1 -3.10 -5.40 -1.3982304 0.9258198 -4.4982304 -4.474180 2
#> 3 1 -14.60 -12.20 -0.7949762 -1.0543012 -15.3949762 -13.254301 2
#> 4 1 -14.20 -0.55 2.8948784 2.5623493 -11.3051216 2.012349 2
#> 5 1 -5.40 -3.30 0.4196487 -0.1334840 -4.9803513 -3.433484 2
#> 6 1 -4.10 -2.55 2.3784499 -1.3179442 -1.7215501 -3.867944 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7100 -36700 6350
#> initial value 998.131940
#> iter 2 value 855.910372
#> iter 3 value 853.321345
#> iter 4 value 852.950268
#> iter 5 value 801.621256
#> iter 6 value 791.239347
#> iter 7 value 789.448794
#> iter 8 value 789.406887
#> iter 9 value 789.406812
#> iter 10 value 789.406780
#> iter 11 value 789.406731
#> iter 12 value 789.406691
#> iter 12 value 789.406691
#> iter 12 value 789.406691
#> final value 789.406691
#> converged
#> This is Run number 198
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.08824033 -0.6094064 -0.4617597 -13.8094064 1
#> 2 1 -3.10 -5.40 -0.03725672 -0.9907419 -3.1372567 -6.3907419 1
#> 3 1 -14.60 -12.20 3.55394712 1.8953880 -11.0460529 -10.3046120 2
#> 4 1 -14.20 -0.55 -0.26865078 1.3179818 -14.4686508 0.7679818 2
#> 5 1 -5.40 -3.30 0.67731874 -0.1664248 -4.7226813 -3.4664248 2
#> 6 1 -4.10 -2.55 1.19904057 -0.1313012 -2.9009594 -2.6813012 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5840 -34675 6625
#> initial value 998.131940
#> iter 2 value 879.807450
#> iter 3 value 877.744135
#> iter 4 value 874.859282
#> iter 5 value 817.889848
#> iter 6 value 808.624187
#> iter 7 value 806.936616
#> iter 8 value 806.904067
#> iter 9 value 806.904017
#> iter 9 value 806.904011
#> iter 9 value 806.904011
#> final value 806.904011
#> converged
#> This is Run number 199
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.4181505 -0.09904670 -0.1318495 -13.2990467 1
#> 2 1 -3.10 -5.40 -0.3739264 0.68697362 -3.4739264 -4.7130264 1
#> 3 1 -14.60 -12.20 0.3307118 -0.36971061 -14.2692882 -12.5697106 2
#> 4 1 -14.20 -0.55 1.1531712 0.03933174 -13.0468288 -0.5106683 2
#> 5 1 -5.40 -3.30 -0.7378131 -0.01826230 -6.1378131 -3.3182623 2
#> 6 1 -4.10 -2.55 0.6505477 0.46066348 -3.4494523 -2.0893365 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6580 -35650 6350
#> initial value 998.131940
#> iter 2 value 869.592174
#> iter 3 value 867.673163
#> iter 4 value 866.608359
#> iter 5 value 812.291789
#> iter 6 value 802.459285
#> iter 7 value 800.652963
#> iter 8 value 800.612596
#> iter 9 value 800.612515
#> iter 9 value 800.612511
#> iter 9 value 800.612511
#> final value 800.612511
#> converged
#> This is Run number 200
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -1.3286324 1.9889056 -1.878632 -11.211094 1
#> 2 1 -3.10 -5.40 1.5169832 0.7642022 -1.583017 -4.635798 1
#> 3 1 -14.60 -12.20 1.2739884 -0.1053637 -13.326012 -12.305364 2
#> 4 1 -14.20 -0.55 -1.3879096 -0.7042969 -15.587910 -1.254297 2
#> 5 1 -5.40 -3.30 0.3681653 -0.4306773 -5.031835 -3.730677 2
#> 6 1 -4.10 -2.55 2.6574841 1.6127390 -1.442516 -0.937261 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7000 -37775 5775
#> initial value 998.131940
#> iter 2 value 844.710179
#> iter 3 value 840.267926
#> iter 4 value 837.619606
#> iter 5 value 791.011790
#> iter 6 value 780.318036
#> iter 7 value 778.464803
#> iter 8 value 778.415305
#> iter 9 value 778.415233
#> iter 10 value 778.415220
#> iter 11 value 778.415190
#> iter 12 value 778.415157
#> iter 12 value 778.415157
#> iter 12 value 778.415157
#> final value 778.415157
#> converged
#> This is Run number 201
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.60448751 -0.26936859 -1.154488 -13.4693686 1
#> 2 1 -3.10 -5.40 1.04008394 -0.92246289 -2.059916 -6.3224629 1
#> 3 1 -14.60 -12.20 1.52639950 -0.01853393 -13.073601 -12.2185339 2
#> 4 1 -14.20 -0.55 -0.05578399 0.94096352 -14.255784 0.3909635 2
#> 5 1 -5.40 -3.30 -0.84633573 -0.17176101 -6.246336 -3.4717610 2
#> 6 1 -4.10 -2.55 0.47675628 -0.72149710 -3.623244 -3.2714971 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7180 -37375 5800
#> initial value 998.131940
#> iter 2 value 849.892326
#> iter 3 value 846.639908
#> iter 4 value 845.424872
#> iter 5 value 797.084670
#> iter 6 value 786.491216
#> iter 7 value 784.582468
#> iter 8 value 784.531356
#> iter 9 value 784.531253
#> iter 10 value 784.531239
#> iter 11 value 784.531202
#> iter 12 value 784.531158
#> iter 12 value 784.531158
#> iter 12 value 784.531158
#> final value 784.531158
#> converged
#> This is Run number 202
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.1682514 2.2069740 0.6182514 -10.9930260 1
#> 2 1 -3.10 -5.40 2.7578556 0.5435083 -0.3421444 -4.8564917 1
#> 3 1 -14.60 -12.20 1.0423797 1.8822904 -13.5576203 -10.3177096 2
#> 4 1 -14.20 -0.55 -0.7068249 1.0454586 -14.9068249 0.4954586 2
#> 5 1 -5.40 -3.30 -0.2871837 0.5805517 -5.6871837 -2.7194483 2
#> 6 1 -4.10 -2.55 1.9104225 1.5506022 -2.1895775 -0.9993978 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5700 -35400 7075
#> initial value 998.131940
#> iter 2 value 868.521543
#> iter 3 value 864.571877
#> iter 4 value 860.453971
#> iter 5 value 805.076838
#> iter 6 value 795.486141
#> iter 7 value 793.850474
#> iter 8 value 793.820536
#> iter 9 value 793.820498
#> iter 9 value 793.820495
#> iter 9 value 793.820495
#> final value 793.820495
#> converged
#> This is Run number 203
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.4411590 1.6178889 -0.108841 -11.5821111 1
#> 2 1 -3.10 -5.40 -0.3427403 -0.2824832 -3.442740 -5.6824832 1
#> 3 1 -14.60 -12.20 2.1044807 1.3285094 -12.495519 -10.8714906 2
#> 4 1 -14.20 -0.55 1.2234276 1.3163622 -12.976572 0.7663622 2
#> 5 1 -5.40 -3.30 2.1449481 1.4113263 -3.255052 -1.8886737 2
#> 6 1 -4.10 -2.55 0.5522771 0.6752234 -3.547723 -1.8747766 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5800 -34975 6275
#> initial value 998.131940
#> iter 2 value 878.313908
#> iter 3 value 875.117145
#> iter 4 value 870.747762
#> iter 5 value 815.798699
#> iter 6 value 806.429055
#> iter 7 value 804.669151
#> iter 8 value 804.632553
#> iter 9 value 804.632497
#> iter 10 value 804.632476
#> iter 11 value 804.632439
#> iter 12 value 804.632418
#> iter 12 value 804.632418
#> iter 12 value 804.632418
#> final value 804.632418
#> converged
#> This is Run number 204
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.2800345 0.3264201 -0.8300345 -12.8735799 1
#> 2 1 -3.10 -5.40 1.2718849 -1.4462789 -1.8281151 -6.8462789 1
#> 3 1 -14.60 -12.20 1.1941175 2.3627337 -13.4058825 -9.8372663 2
#> 4 1 -14.20 -0.55 0.0587319 0.6601346 -14.1412681 0.1101346 2
#> 5 1 -5.40 -3.30 2.4374082 0.8218695 -2.9625918 -2.4781305 2
#> 6 1 -4.10 -2.55 -0.1653879 0.8804388 -4.2653879 -1.6695612 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7580 -36650 5575
#> initial value 998.131940
#> iter 2 value 860.155734
#> iter 3 value 858.442594
#> iter 4 value 858.402595
#> iter 5 value 807.935756
#> iter 6 value 797.818652
#> iter 7 value 795.764247
#> iter 8 value 795.706906
#> iter 9 value 795.706713
#> iter 9 value 795.706709
#> iter 9 value 795.706709
#> final value 795.706709
#> converged
#> This is Run number 205
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.575719479 1.2217463 0.02571948 -11.9782537 1
#> 2 1 -3.10 -5.40 -0.553836659 -0.5593638 -3.65383666 -5.9593638 1
#> 3 1 -14.60 -12.20 -0.122987840 0.6950422 -14.72298784 -11.5049578 2
#> 4 1 -14.20 -0.55 0.310678202 -0.1175640 -13.88932180 -0.6675640 2
#> 5 1 -5.40 -3.30 -0.171063273 1.7745317 -5.57106327 -1.5254683 2
#> 6 1 -4.10 -2.55 -0.007487008 2.1352614 -4.10748701 -0.4147386 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6800 -36600 5850
#> initial value 998.131940
#> iter 2 value 860.233828
#> iter 3 value 857.218916
#> iter 4 value 855.331275
#> iter 5 value 804.774730
#> iter 6 value 794.555440
#> iter 7 value 792.626943
#> iter 8 value 792.577512
#> iter 9 value 792.577405
#> iter 10 value 792.577384
#> iter 11 value 792.577346
#> iter 12 value 792.577311
#> iter 12 value 792.577311
#> iter 12 value 792.577311
#> final value 792.577311
#> converged
#> This is Run number 206
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.4313884 -0.08109476 -0.9813884 -13.281095 1
#> 2 1 -3.10 -5.40 3.4072708 1.35034931 0.3072708 -4.049651 1
#> 3 1 -14.60 -12.20 -0.6456188 0.63633644 -15.2456188 -11.563664 2
#> 4 1 -14.20 -0.55 0.9997532 -0.94661641 -13.2002468 -1.496616 2
#> 5 1 -5.40 -3.30 -1.0570524 1.08653198 -6.4570524 -2.213468 2
#> 6 1 -4.10 -2.55 -0.6094024 -0.25126652 -4.7094024 -2.801267 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7300 -37150 5625
#> initial value 998.131940
#> iter 2 value 853.697382
#> iter 3 value 851.056075
#> iter 4 value 850.264757
#> iter 5 value 801.393430
#> iter 6 value 790.906029
#> iter 7 value 788.895558
#> iter 8 value 788.839295
#> iter 9 value 788.839144
#> iter 10 value 788.839129
#> iter 11 value 788.839095
#> iter 12 value 788.839050
#> iter 12 value 788.839050
#> iter 12 value 788.839050
#> final value 788.839050
#> converged
#> This is Run number 207
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -1.12809312 2.9369925 -1.678093 -10.2630075 1
#> 2 1 -3.10 -5.40 -1.34291221 1.8230701 -4.442912 -3.5769299 2
#> 3 1 -14.60 -12.20 -0.55397690 1.6880484 -15.153977 -10.5119516 2
#> 4 1 -14.20 -0.55 -1.18141886 0.2911606 -15.381419 -0.2588394 2
#> 5 1 -5.40 -3.30 -0.21150041 0.7179864 -5.611500 -2.5820136 2
#> 6 1 -4.10 -2.55 -0.04887962 -0.9659513 -4.148880 -3.5159513 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6300 -37350 6625
#> initial value 998.131940
#> iter 2 value 846.185755
#> iter 3 value 839.963267
#> iter 4 value 835.305979
#> iter 5 value 786.779671
#> iter 6 value 776.375423
#> iter 7 value 774.717001
#> iter 8 value 774.681076
#> iter 9 value 774.681062
#> iter 10 value 774.681047
#> iter 11 value 774.681008
#> iter 12 value 774.680971
#> iter 12 value 774.680971
#> iter 12 value 774.680971
#> final value 774.680971
#> converged
#> This is Run number 208
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.0478131 0.48905641 1.497813 -12.710944 1
#> 2 1 -3.10 -5.40 0.7632667 0.45242732 -2.336733 -4.947573 1
#> 3 1 -14.60 -12.20 0.1261895 1.17184474 -14.473811 -11.028155 2
#> 4 1 -14.20 -0.55 -0.5349202 -0.27999900 -14.734920 -0.829999 2
#> 5 1 -5.40 -3.30 2.1738729 -0.20329561 -3.226127 -3.503296 1
#> 6 1 -4.10 -2.55 0.1631515 -0.04054984 -3.936849 -2.590550 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6900 -38025 6875
#> initial value 998.131940
#> iter 2 value 834.999598
#> iter 3 value 829.506238
#> iter 4 value 827.892017
#> iter 5 value 780.118335
#> iter 6 value 769.412767
#> iter 7 value 767.822607
#> iter 8 value 767.790941
#> iter 9 value 767.790861
#> iter 10 value 767.790801
#> iter 11 value 767.790745
#> iter 11 value 767.790740
#> iter 11 value 767.790740
#> final value 767.790740
#> converged
#> This is Run number 209
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.4065586 0.2050601 0.8565586 -12.994940 1
#> 2 1 -3.10 -5.40 -1.3527379 0.4271253 -4.4527379 -4.972875 1
#> 3 1 -14.60 -12.20 -0.2441851 1.8445068 -14.8441851 -10.355493 2
#> 4 1 -14.20 -0.55 0.9176072 3.8683484 -13.2823928 3.318348 2
#> 5 1 -5.40 -3.30 0.9567661 -0.6538852 -4.4432339 -3.953885 2
#> 6 1 -4.10 -2.55 -1.0394508 -0.3465534 -5.1394508 -2.896553 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6840 -36450 5425
#> initial value 998.131940
#> iter 2 value 864.308542
#> iter 3 value 861.530405
#> iter 4 value 859.331888
#> iter 5 value 809.109208
#> iter 6 value 799.041611
#> iter 7 value 796.943808
#> iter 8 value 796.885988
#> iter 9 value 796.885821
#> iter 10 value 796.885803
#> iter 11 value 796.885776
#> iter 12 value 796.885746
#> iter 12 value 796.885746
#> iter 12 value 796.885746
#> final value 796.885746
#> converged
#> This is Run number 210
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.49390439 -0.6901272 -1.043904 -13.890127 1
#> 2 1 -3.10 -5.40 -0.26773248 0.6768361 -3.367732 -4.723164 1
#> 3 1 -14.60 -12.20 1.38087453 0.2318921 -13.219125 -11.968108 2
#> 4 1 -14.20 -0.55 1.16924385 2.6509907 -13.030756 2.100991 2
#> 5 1 -5.40 -3.30 0.04622983 -0.9927535 -5.353770 -4.292754 2
#> 6 1 -4.10 -2.55 0.78463913 -0.3319828 -3.315361 -2.881983 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6920 -36600 5475
#> initial value 998.131940
#> iter 2 value 862.065559
#> iter 3 value 859.304012
#> iter 4 value 857.385344
#> iter 5 value 807.421782
#> iter 6 value 797.262299
#> iter 7 value 795.184750
#> iter 8 value 795.127317
#> iter 9 value 795.127154
#> iter 10 value 795.127136
#> iter 11 value 795.127107
#> iter 12 value 795.127075
#> iter 12 value 795.127075
#> iter 12 value 795.127075
#> final value 795.127075
#> converged
#> This is Run number 211
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.00741987 1.53694391 -0.5425801 -11.6630561 1
#> 2 1 -3.10 -5.40 -0.18889939 -0.99424576 -3.2888994 -6.3942458 1
#> 3 1 -14.60 -12.20 0.61138069 0.04030681 -13.9886193 -12.1596932 2
#> 4 1 -14.20 -0.55 -1.88873540 0.27687408 -16.0887354 -0.2731259 2
#> 5 1 -5.40 -3.30 0.71161981 1.45057356 -4.6883802 -1.8494264 2
#> 6 1 -4.10 -2.55 0.33658836 1.51489222 -3.7634116 -1.0351078 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6760 -37300 5600
#> initial value 998.131940
#> iter 2 value 852.299715
#> iter 3 value 847.801382
#> iter 4 value 844.092125
#> iter 5 value 796.692582
#> iter 6 value 786.236488
#> iter 7 value 784.289810
#> iter 8 value 784.236383
#> iter 9 value 784.236276
#> iter 10 value 784.236262
#> iter 11 value 784.236241
#> iter 12 value 784.236219
#> iter 12 value 784.236219
#> iter 12 value 784.236219
#> final value 784.236219
#> converged
#> This is Run number 212
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.1955838 2.27795694 -0.3544162 -10.9220431 1
#> 2 1 -3.10 -5.40 0.2012945 -1.24797792 -2.8987055 -6.6479779 1
#> 3 1 -14.60 -12.20 0.3993494 1.39216691 -14.2006506 -10.8078331 2
#> 4 1 -14.20 -0.55 -0.8712329 0.08776695 -15.0712329 -0.4622331 2
#> 5 1 -5.40 -3.30 -1.1210041 1.24611889 -6.5210041 -2.0538811 2
#> 6 1 -4.10 -2.55 0.9362255 2.04149585 -3.1637745 -0.5085041 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7020 -36900 5375
#> initial value 998.131940
#> iter 2 value 858.558466
#> iter 3 value 855.587135
#> iter 4 value 853.591896
#> iter 5 value 804.690332
#> iter 6 value 794.405566
#> iter 7 value 792.300359
#> iter 8 value 792.240111
#> iter 9 value 792.239934
#> iter 10 value 792.239919
#> iter 11 value 792.239893
#> iter 12 value 792.239862
#> iter 12 value 792.239862
#> iter 12 value 792.239862
#> final value 792.239862
#> converged
#> This is Run number 213
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.51011783 -0.48362869 -1.060118 -13.683629 1
#> 2 1 -3.10 -5.40 0.24003228 3.85408873 -2.859968 -1.545911 2
#> 3 1 -14.60 -12.20 2.48699839 0.73567544 -12.113002 -11.464325 2
#> 4 1 -14.20 -0.55 -1.02153914 -0.39945095 -15.221539 -0.949451 2
#> 5 1 -5.40 -3.30 2.00536228 -0.01950285 -3.394638 -3.319503 2
#> 6 1 -4.10 -2.55 -0.03960423 -1.03587859 -4.139604 -3.585879 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6520 -36350 5875
#> initial value 998.131940
#> iter 2 value 863.488276
#> iter 3 value 860.017260
#> iter 4 value 857.031762
#> iter 5 value 806.085865
#> iter 6 value 796.018149
#> iter 7 value 794.109628
#> iter 8 value 794.062091
#> iter 9 value 794.061997
#> iter 10 value 794.061976
#> iter 11 value 794.061942
#> iter 12 value 794.061915
#> iter 12 value 794.061915
#> iter 12 value 794.061915
#> final value 794.061915
#> converged
#> This is Run number 214
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.03916815 6.8388484 0.4891681 -6.3611516 1
#> 2 1 -3.10 -5.40 0.83131022 -0.2757464 -2.2686898 -5.6757464 1
#> 3 1 -14.60 -12.20 -0.29990500 -0.3328947 -14.8999050 -12.5328947 2
#> 4 1 -14.20 -0.55 -0.27930131 1.0362854 -14.4793013 0.4862854 2
#> 5 1 -5.40 -3.30 -0.29015387 -1.1406679 -5.6901539 -4.4406679 2
#> 6 1 -4.10 -2.55 -0.02436472 1.6066615 -4.1243647 -0.9433385 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6140 -37350 7525
#> initial value 998.131940
#> iter 2 value 840.548833
#> iter 3 value 833.637227
#> iter 4 value 829.912164
#> iter 5 value 779.595708
#> iter 6 value 769.339172
#> iter 7 value 767.766455
#> iter 8 value 767.737480
#> iter 9 value 767.737383
#> iter 10 value 767.737340
#> iter 11 value 767.737310
#> iter 11 value 767.737302
#> iter 11 value 767.737302
#> final value 767.737302
#> converged
#> This is Run number 215
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.561763154 -0.2982590 2.011763 -13.498259 1
#> 2 1 -3.10 -5.40 -0.602901189 0.6043676 -3.702901 -4.795632 1
#> 3 1 -14.60 -12.20 -0.000316579 -0.3095222 -14.600317 -12.509522 2
#> 4 1 -14.20 -0.55 0.263301396 1.9537550 -13.936699 1.403755 2
#> 5 1 -5.40 -3.30 1.029932347 -0.1625724 -4.370068 -3.462572 2
#> 6 1 -4.10 -2.55 0.026480142 0.5392624 -4.073520 -2.010738 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7200 -38075 5725
#> initial value 998.131940
#> iter 2 value 840.585767
#> iter 3 value 836.272769
#> iter 4 value 834.178537
#> iter 5 value 788.398711
#> iter 6 value 777.573117
#> iter 7 value 775.728696
#> iter 8 value 775.678593
#> iter 9 value 775.678523
#> iter 9 value 775.678513
#> iter 9 value 775.678513
#> final value 775.678513
#> converged
#> This is Run number 216
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.66828632 -0.1985588 2.118286 -13.39855875 1
#> 2 1 -3.10 -5.40 0.01873175 -0.6432037 -3.081268 -6.04320373 1
#> 3 1 -14.60 -12.20 0.55946671 0.4381047 -14.040533 -11.76189531 2
#> 4 1 -14.20 -0.55 0.76788607 0.4798441 -13.432114 -0.07015591 2
#> 5 1 -5.40 -3.30 -1.50231732 -1.3267402 -6.902317 -4.62674024 2
#> 6 1 -4.10 -2.55 0.05635659 -0.1417200 -4.043643 -2.69171995 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7580 -37875 5600
#> initial value 998.131940
#> iter 2 value 843.579669
#> iter 3 value 840.505990
#> iter 4 value 839.942510
#> iter 5 value 793.302097
#> iter 6 value 782.491959
#> iter 7 value 780.542804
#> iter 8 value 780.487011
#> iter 9 value 780.486882
#> iter 9 value 780.486873
#> iter 9 value 780.486873
#> final value 780.486873
#> converged
#> This is Run number 217
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.2370272 -0.9188913 -0.7870272 -14.118891 1
#> 2 1 -3.10 -5.40 0.4683085 1.2361033 -2.6316915 -4.163897 1
#> 3 1 -14.60 -12.20 -0.4888360 1.1392376 -15.0888360 -11.060762 2
#> 4 1 -14.20 -0.55 -0.2111245 1.9011068 -14.4111245 1.351107 2
#> 5 1 -5.40 -3.30 1.5836584 -0.1441007 -3.8163416 -3.444101 2
#> 6 1 -4.10 -2.55 1.2531416 0.5282860 -2.8468584 -2.021714 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6160 -35450 7150
#> initial value 998.131940
#> iter 2 value 867.413344
#> iter 3 value 864.961642
#> iter 4 value 863.456078
#> iter 5 value 807.281287
#> iter 6 value 797.551311
#> iter 7 value 795.910580
#> iter 8 value 795.880719
#> iter 9 value 795.880666
#> iter 10 value 795.880618
#> iter 11 value 795.880605
#> iter 12 value 795.880568
#> iter 12 value 795.880568
#> iter 12 value 795.880568
#> final value 795.880568
#> converged
#> This is Run number 218
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.4054621 0.5454071 -0.9554621 -12.65459292 1
#> 2 1 -3.10 -5.40 1.0738699 -0.3003661 -2.0261301 -5.70036612 1
#> 3 1 -14.60 -12.20 -0.4242810 0.8962216 -15.0242810 -11.30377844 2
#> 4 1 -14.20 -0.55 0.5787500 0.5772306 -13.6212500 0.02723057 2
#> 5 1 -5.40 -3.30 -0.2908292 -0.3798646 -5.6908292 -3.67986463 2
#> 6 1 -4.10 -2.55 0.6420155 -0.7346397 -3.4579845 -3.28463967 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6260 -35500 5950
#> initial value 998.131940
#> iter 2 value 873.767219
#> iter 3 value 871.024921
#> iter 4 value 868.021416
#> iter 5 value 814.554851
#> iter 6 value 804.909257
#> iter 7 value 803.025518
#> iter 8 value 802.981703
#> iter 9 value 802.981613
#> iter 10 value 802.981588
#> iter 11 value 802.981550
#> iter 12 value 802.981526
#> iter 12 value 802.981526
#> iter 12 value 802.981526
#> final value 802.981526
#> converged
#> This is Run number 219
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.03909853 -0.8379911 -0.5890985 -14.0379911 1
#> 2 1 -3.10 -5.40 1.20951256 0.3957147 -1.8904874 -5.0042853 1
#> 3 1 -14.60 -12.20 -0.32738877 2.0703041 -14.9273888 -10.1296959 2
#> 4 1 -14.20 -0.55 0.71712521 0.7401823 -13.4828748 0.1901823 2
#> 5 1 -5.40 -3.30 -0.53060762 0.8000549 -5.9306076 -2.4999451 2
#> 6 1 -4.10 -2.55 -0.47882894 3.0745738 -4.5788289 0.5245738 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7940 -38175 4000
#> initial value 998.131940
#> iter 2 value 846.004158
#> iter 3 value 843.484327
#> iter 4 value 841.890733
#> iter 5 value 798.642387
#> iter 6 value 788.278772
#> iter 7 value 785.404581
#> iter 8 value 785.292579
#> iter 9 value 785.291881
#> iter 10 value 785.291859
#> iter 10 value 785.291857
#> iter 10 value 785.291851
#> final value 785.291851
#> converged
#> This is Run number 220
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 4.5325359 2.3052061 3.982536 -10.894794 1
#> 2 1 -3.10 -5.40 3.7376050 -0.9864284 0.637605 -6.386428 1
#> 3 1 -14.60 -12.20 0.0622845 -0.6639699 -14.537716 -12.863970 2
#> 4 1 -14.20 -0.55 -0.1838607 2.9756654 -14.383861 2.425665 2
#> 5 1 -5.40 -3.30 1.2762321 0.2811649 -4.123768 -3.018835 2
#> 6 1 -4.10 -2.55 0.2523981 0.2106335 -3.847602 -2.339367 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6500 -36625 5925
#> initial value 998.131940
#> iter 2 value 859.690921
#> iter 3 value 855.635235
#> iter 4 value 852.159499
#> iter 5 value 802.122349
#> iter 6 value 791.934581
#> iter 7 value 790.058578
#> iter 8 value 790.011886
#> iter 9 value 790.011806
#> iter 10 value 790.011787
#> iter 11 value 790.011755
#> iter 12 value 790.011730
#> iter 12 value 790.011730
#> iter 12 value 790.011730
#> final value 790.011730
#> converged
#> This is Run number 221
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.4865964 1.2432057 0.9365964 -11.9567943 1
#> 2 1 -3.10 -5.40 1.4557191 0.6375309 -1.6442809 -4.7624691 1
#> 3 1 -14.60 -12.20 0.1866966 -0.9161204 -14.4133034 -13.1161204 2
#> 4 1 -14.20 -0.55 1.1944419 0.3715710 -13.0055581 -0.1784290 2
#> 5 1 -5.40 -3.30 1.8871776 -0.6147566 -3.5128224 -3.9147566 1
#> 6 1 -4.10 -2.55 -0.5849015 1.7463018 -4.6849015 -0.8036982 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6340 -36750 4475
#> initial value 998.131940
#> iter 2 value 864.957486
#> iter 3 value 858.287946
#> iter 4 value 849.168797
#> iter 5 value 804.422876
#> iter 6 value 794.560210
#> iter 7 value 792.050998
#> iter 8 value 791.965487
#> iter 9 value 791.965014
#> iter 10 value 791.965001
#> iter 10 value 791.965000
#> iter 10 value 791.964995
#> final value 791.964995
#> converged
#> This is Run number 222
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.5548302 0.9392740 -1.104830 -12.2607260 1
#> 2 1 -3.10 -5.40 0.0268062 -1.8538888 -3.073194 -7.2538888 1
#> 3 1 -14.60 -12.20 -0.4016416 -1.1491968 -15.001642 -13.3491968 2
#> 4 1 -14.20 -0.55 2.4187518 0.9808984 -11.781248 0.4308984 2
#> 5 1 -5.40 -3.30 0.4726978 2.4688643 -4.927302 -0.8311357 2
#> 6 1 -4.10 -2.55 -0.3756296 1.6932975 -4.475630 -0.8567025 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6620 -37700 5750
#> initial value 998.131940
#> iter 2 value 846.136203
#> iter 3 value 840.275349
#> iter 4 value 835.085738
#> iter 5 value 789.275805
#> iter 6 value 778.700130
#> iter 7 value 776.860491
#> iter 8 value 776.811240
#> iter 9 value 776.811178
#> iter 9 value 776.811168
#> iter 9 value 776.811168
#> final value 776.811168
#> converged
#> This is Run number 223
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.8543258 0.9974783 0.3043258 -12.2025217 1
#> 2 1 -3.10 -5.40 2.0752079 0.0114285 -1.0247921 -5.3885715 1
#> 3 1 -14.60 -12.20 0.2003957 0.6770154 -14.3996043 -11.5229846 2
#> 4 1 -14.20 -0.55 -1.5434896 -1.4050096 -15.7434896 -1.9550096 2
#> 5 1 -5.40 -3.30 2.0757314 2.7977009 -3.3242686 -0.5022991 2
#> 6 1 -4.10 -2.55 -0.5458166 0.2061074 -4.6458166 -2.3438926 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6520 -34650 6275
#> initial value 998.131940
#> iter 2 value 881.879441
#> iter 3 value 881.376113
#> iter 4 value 880.842587
#> iter 5 value 823.882465
#> iter 6 value 814.569351
#> iter 7 value 812.757385
#> iter 8 value 812.718110
#> iter 9 value 812.718011
#> iter 9 value 812.718002
#> iter 9 value 812.718002
#> final value 812.718002
#> converged
#> This is Run number 224
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.607683262 0.4693575 0.05768326 -12.730643 1
#> 2 1 -3.10 -5.40 0.535760733 -0.5115665 -2.56423927 -5.911566 1
#> 3 1 -14.60 -12.20 -1.422254869 -0.4982201 -16.02225487 -12.698220 2
#> 4 1 -14.20 -0.55 0.174944705 -1.2003605 -14.02505529 -1.750360 2
#> 5 1 -5.40 -3.30 -0.009232878 -1.0129717 -5.40923288 -4.312972 2
#> 6 1 -4.10 -2.55 -0.188300580 -0.3591890 -4.28830058 -2.909189 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6220 -33400 5375
#> initial value 998.131940
#> iter 2 value 900.416554
#> iter 3 value 890.481100
#> iter 4 value 889.396136
#> iter 5 value 840.195636
#> iter 6 value 832.681784
#> iter 7 value 830.758060
#> iter 8 value 830.712096
#> iter 9 value 830.711776
#> iter 10 value 830.711762
#> iter 11 value 830.711622
#> iter 12 value 830.711445
#> iter 12 value 830.711445
#> iter 12 value 830.711445
#> final value 830.711445
#> converged
#> This is Run number 225
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -1.8273781 2.38616209 -2.377378 -10.8138379 1
#> 2 1 -3.10 -5.40 -0.7995197 1.46343160 -3.899520 -3.9365684 1
#> 3 1 -14.60 -12.20 0.1586917 0.04203672 -14.441308 -12.1579633 2
#> 4 1 -14.20 -0.55 0.7442883 1.06152924 -13.455712 0.5115292 2
#> 5 1 -5.40 -3.30 -0.3621932 -0.51199653 -5.762193 -3.8119965 2
#> 6 1 -4.10 -2.55 1.1395757 0.08459677 -2.960424 -2.4654032 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6740 -35750 6850
#> initial value 998.131940
#> iter 2 value 865.302573
#> iter 3 value 863.439211
#> iter 4 value 863.157435
#> iter 5 value 808.260117
#> iter 6 value 798.292168
#> iter 7 value 796.597646
#> iter 8 value 796.563594
#> iter 9 value 796.563535
#> iter 10 value 796.563512
#> iter 11 value 796.563459
#> iter 12 value 796.563416
#> iter 12 value 796.563416
#> iter 12 value 796.563416
#> final value 796.563416
#> converged
#> This is Run number 226
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 3.1467926 0.46413638 2.596793 -12.7358636 1
#> 2 1 -3.10 -5.40 0.9841071 0.09444402 -2.115893 -5.3055560 1
#> 3 1 -14.60 -12.20 0.2080483 0.41035160 -14.391952 -11.7896484 2
#> 4 1 -14.20 -0.55 -1.3914311 -0.25283946 -15.591431 -0.8028395 2
#> 5 1 -5.40 -3.30 0.1900429 1.28538298 -5.209957 -2.0146170 2
#> 6 1 -4.10 -2.55 -1.3982069 0.73350063 -5.498207 -1.8164994 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6800 -36325 5650
#> initial value 998.131940
#> iter 2 value 864.804474
#> iter 3 value 862.192023
#> iter 4 value 860.338611
#> iter 5 value 809.283416
#> iter 6 value 799.227513
#> iter 7 value 797.212863
#> iter 8 value 797.159794
#> iter 9 value 797.159655
#> iter 10 value 797.159634
#> iter 11 value 797.159599
#> iter 12 value 797.159566
#> iter 12 value 797.159566
#> iter 12 value 797.159566
#> final value 797.159566
#> converged
#> This is Run number 227
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.3158946 -0.4753950 0.7658946 -13.67539505 1
#> 2 1 -3.10 -5.40 -0.3133233 -0.3698650 -3.4133233 -5.76986504 1
#> 3 1 -14.60 -12.20 -0.2148081 0.4728592 -14.8148081 -11.72714084 2
#> 4 1 -14.20 -0.55 3.1352365 -1.0656513 -11.0647635 -1.61565135 2
#> 5 1 -5.40 -3.30 2.0599385 3.2222442 -3.3400615 -0.07775581 2
#> 6 1 -4.10 -2.55 -0.1245836 -0.4593172 -4.2245836 -3.00931717 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6600 -34675 5125
#> initial value 998.131940
#> iter 2 value 887.429057
#> iter 3 value 886.491038
#> iter 4 value 884.952283
#> iter 5 value 830.214633
#> iter 6 value 821.179739
#> iter 7 value 818.995201
#> iter 8 value 818.941149
#> iter 9 value 818.940972
#> iter 10 value 818.940951
#> iter 11 value 818.940918
#> iter 12 value 818.940888
#> iter 12 value 818.940888
#> iter 12 value 818.940888
#> final value 818.940888
#> converged
#> This is Run number 228
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.92568734 1.7316891 1.375687 -11.468311 1
#> 2 1 -3.10 -5.40 0.80676970 2.5671633 -2.293230 -2.832837 1
#> 3 1 -14.60 -12.20 0.51784558 1.6925236 -14.082154 -10.507476 2
#> 4 1 -14.20 -0.55 -0.05444423 3.0350703 -14.254444 2.485070 2
#> 5 1 -5.40 -3.30 1.59981196 0.9035731 -3.800188 -2.396427 2
#> 6 1 -4.10 -2.55 0.81605091 -0.4801990 -3.283949 -3.030199 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7240 -36825 5200
#> initial value 998.131940
#> iter 2 value 860.169261
#> iter 3 value 857.851646
#> iter 4 value 856.648247
#> iter 5 value 807.523794
#> iter 6 value 797.303421
#> iter 7 value 795.081142
#> iter 8 value 795.015040
#> iter 9 value 795.014807
#> iter 10 value 795.014795
#> iter 11 value 795.014769
#> iter 12 value 795.014731
#> iter 12 value 795.014731
#> iter 12 value 795.014731
#> final value 795.014731
#> converged
#> This is Run number 229
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 3.4572241 -1.0334591 2.907224 -14.2334591 1
#> 2 1 -3.10 -5.40 1.3384681 1.6278816 -1.761532 -3.7721184 1
#> 3 1 -14.60 -12.20 0.7952035 0.9156107 -13.804797 -11.2843893 2
#> 4 1 -14.20 -0.55 -0.2602938 0.2415113 -14.460294 -0.3084887 2
#> 5 1 -5.40 -3.30 -1.1734813 -0.1704749 -6.573481 -3.4704749 2
#> 6 1 -4.10 -2.55 1.0187373 0.9836984 -3.081263 -1.5663016 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6680 -36275 7175
#> initial value 998.131940
#> iter 2 value 856.750264
#> iter 3 value 853.820603
#> iter 4 value 853.345465
#> iter 5 value 799.454074
#> iter 6 value 789.273982
#> iter 7 value 787.644881
#> iter 8 value 787.615030
#> iter 9 value 787.614982
#> iter 10 value 787.614956
#> iter 11 value 787.614904
#> iter 12 value 787.614868
#> iter 12 value 787.614868
#> iter 12 value 787.614868
#> final value 787.614868
#> converged
#> This is Run number 230
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.3670123 -0.5454151 0.8170123 -13.745415088 1
#> 2 1 -3.10 -5.40 2.8100269 1.0072883 -0.2899731 -4.392711655 1
#> 3 1 -14.60 -12.20 0.1843117 1.4703301 -14.4156883 -10.729669866 2
#> 4 1 -14.20 -0.55 0.9582980 0.5516586 -13.2417020 0.001658554 2
#> 5 1 -5.40 -3.30 2.7507964 4.1435901 -2.6492036 0.843590112 2
#> 6 1 -4.10 -2.55 3.8220638 2.8693731 -0.2779362 0.319373116 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7140 -37475 7075
#> initial value 998.131940
#> iter 2 value 841.150276
#> iter 3 value 836.956487
#> iter 4 value 836.726130
#> iter 5 value 786.735242
#> iter 6 value 776.098083
#> iter 7 value 774.514931
#> iter 8 value 774.486038
#> iter 9 value 774.485958
#> iter 10 value 774.485906
#> iter 11 value 774.485848
#> iter 12 value 774.485833
#> iter 12 value 774.485833
#> iter 12 value 774.485833
#> final value 774.485833
#> converged
#> This is Run number 231
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 3.4911843 0.3890723 2.941184 -12.8109277 1
#> 2 1 -3.10 -5.40 0.3865471 1.1087142 -2.713453 -4.2912858 1
#> 3 1 -14.60 -12.20 3.3603668 0.9241733 -11.239633 -11.2758267 1
#> 4 1 -14.20 -0.55 -0.5978765 0.3022616 -14.797876 -0.2477384 2
#> 5 1 -5.40 -3.30 2.2806319 -1.0169474 -3.119368 -4.3169474 1
#> 6 1 -4.10 -2.55 1.1239265 0.1650019 -2.976074 -2.3849981 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6220 -36800 6650
#> initial value 998.131940
#> iter 2 value 853.413955
#> iter 3 value 848.131918
#> iter 4 value 844.049696
#> iter 5 value 793.564673
#> iter 6 value 783.337663
#> iter 7 value 781.653798
#> iter 8 value 781.618090
#> iter 9 value 781.618050
#> iter 10 value 781.618030
#> iter 11 value 781.618007
#> iter 12 value 781.617974
#> iter 12 value 781.617974
#> iter 12 value 781.617974
#> final value 781.617974
#> converged
#> This is Run number 232
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.94649780 2.00461372 -1.496498 -11.1953863 1
#> 2 1 -3.10 -5.40 -0.43611418 -0.24815533 -3.536114 -5.6481553 1
#> 3 1 -14.60 -12.20 0.07384209 0.79969251 -14.526158 -11.4003075 2
#> 4 1 -14.20 -0.55 0.55948675 0.00551342 -13.640513 -0.5444866 2
#> 5 1 -5.40 -3.30 0.62010052 0.31803846 -4.779899 -2.9819615 2
#> 6 1 -4.10 -2.55 1.90289555 -0.26349189 -2.197104 -2.8134919 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6540 -36675 5100
#> initial value 998.131940
#> iter 2 value 863.138716
#> iter 3 value 858.548820
#> iter 4 value 853.263450
#> iter 5 value 805.492624
#> iter 6 value 795.436894
#> iter 7 value 793.250066
#> iter 8 value 793.185735
#> iter 9 value 793.185526
#> iter 9 value 793.185525
#> iter 9 value 793.185525
#> final value 793.185525
#> converged
#> This is Run number 233
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.43378643 0.2184106 0.8837864 -12.981589 1
#> 2 1 -3.10 -5.40 -0.33258185 0.7908424 -3.4325818 -4.609158 1
#> 3 1 -14.60 -12.20 0.08208239 1.0393206 -14.5179176 -11.160679 2
#> 4 1 -14.20 -0.55 0.66388985 5.5404941 -13.5361101 4.990494 2
#> 5 1 -5.40 -3.30 0.23348994 -0.1587373 -5.1665101 -3.458737 2
#> 6 1 -4.10 -2.55 -0.14909086 -1.3159556 -4.2490909 -3.865956 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6680 -35825 5400
#> initial value 998.131940
#> iter 2 value 872.403412
#> iter 3 value 870.134249
#> iter 4 value 867.946335
#> iter 5 value 815.996030
#> iter 6 value 806.258745
#> iter 7 value 804.145486
#> iter 8 value 804.089576
#> iter 9 value 804.089410
#> iter 10 value 804.089391
#> iter 11 value 804.089361
#> iter 12 value 804.089332
#> iter 12 value 804.089332
#> iter 12 value 804.089332
#> final value 804.089332
#> converged
#> This is Run number 234
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.140862 0.3307145 0.5908620 -12.8692855 1
#> 2 1 -3.10 -5.40 1.332385 0.5823580 -1.7676154 -4.8176420 1
#> 3 1 -14.60 -12.20 5.866352 0.8412036 -8.7336478 -11.3587964 1
#> 4 1 -14.20 -0.55 -1.111482 0.1209739 -15.3114822 -0.4290261 2
#> 5 1 -5.40 -3.30 1.422022 -0.4445774 -3.9779785 -3.7445774 2
#> 6 1 -4.10 -2.55 4.304112 -1.2490640 0.2041117 -3.7990640 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6800 -36775 6125
#> initial value 998.131940
#> iter 2 value 856.468196
#> iter 3 value 853.187384
#> iter 4 value 851.507706
#> iter 5 value 800.979514
#> iter 6 value 790.648586
#> iter 7 value 788.815446
#> iter 8 value 788.770934
#> iter 9 value 788.770859
#> iter 9 value 788.770849
#> iter 9 value 788.770849
#> final value 788.770849
#> converged
#> This is Run number 235
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.87873128 1.1216344 -1.428731 -12.078366 1
#> 2 1 -3.10 -5.40 1.53231102 4.0723236 -1.567689 -1.327676 2
#> 3 1 -14.60 -12.20 1.37769426 -0.3999933 -13.222306 -12.599993 2
#> 4 1 -14.20 -0.55 0.54977709 -0.8086238 -13.650223 -1.358624 2
#> 5 1 -5.40 -3.30 -0.04532407 -0.1027343 -5.445324 -3.402734 2
#> 6 1 -4.10 -2.55 1.44179615 -1.2614602 -2.658204 -3.811460 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7100 -37500 6350
#> initial value 998.131940
#> iter 2 value 845.240436
#> iter 3 value 841.448759
#> iter 4 value 840.495027
#> iter 5 value 791.678394
#> iter 6 value 781.009575
#> iter 7 value 779.279660
#> iter 8 value 779.239581
#> iter 9 value 779.239564
#> iter 10 value 779.239545
#> iter 11 value 779.239488
#> iter 12 value 779.239416
#> iter 12 value 779.239416
#> iter 12 value 779.239416
#> final value 779.239416
#> converged
#> This is Run number 236
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.47446318 -0.2112967 0.9244632 -13.4112967 1
#> 2 1 -3.10 -5.40 -0.01569883 0.3804752 -3.1156988 -5.0195248 1
#> 3 1 -14.60 -12.20 -0.06812916 5.2840882 -14.6681292 -6.9159118 2
#> 4 1 -14.20 -0.55 0.35794495 0.1517922 -13.8420551 -0.3982078 2
#> 5 1 -5.40 -3.30 1.88556459 -0.7545776 -3.5144354 -4.0545776 1
#> 6 1 -4.10 -2.55 0.13358996 1.6352299 -3.9664100 -0.9147701 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6220 -36350 7375
#> initial value 998.131940
#> iter 2 value 854.737333
#> iter 3 value 850.538326
#> iter 4 value 848.553329
#> iter 5 value 794.793208
#> iter 6 value 784.724461
#> iter 7 value 783.114981
#> iter 8 value 783.086527
#> iter 9 value 783.086482
#> iter 10 value 783.086456
#> iter 11 value 783.086408
#> iter 12 value 783.086380
#> iter 12 value 783.086380
#> iter 12 value 783.086380
#> final value 783.086380
#> converged
#> This is Run number 237
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -1.7521916 0.8584949 -2.302192 -12.3415051 1
#> 2 1 -3.10 -5.40 -0.1740855 0.8209470 -3.274085 -4.5790530 1
#> 3 1 -14.60 -12.20 -1.5389306 -0.4909919 -16.138931 -12.6909919 2
#> 4 1 -14.20 -0.55 0.8276107 0.3662336 -13.372389 -0.1837664 2
#> 5 1 -5.40 -3.30 0.3238574 1.1963219 -5.076143 -2.1036781 2
#> 6 1 -4.10 -2.55 0.2645018 0.1713893 -3.835498 -2.3786107 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6960 -37625 6150
#> initial value 998.131940
#> iter 2 value 844.787441
#> iter 3 value 840.476155
#> iter 4 value 838.512543
#> iter 5 value 790.641305
#> iter 6 value 779.976332
#> iter 7 value 778.214720
#> iter 8 value 778.171900
#> iter 9 value 778.171853
#> iter 10 value 778.171831
#> iter 11 value 778.171787
#> iter 12 value 778.171753
#> iter 12 value 778.171753
#> iter 12 value 778.171753
#> final value 778.171753
#> converged
#> This is Run number 238
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.8031308 0.05971412 2.253131 -13.14028588 1
#> 2 1 -3.10 -5.40 -0.5115848 3.24663405 -3.611585 -2.15336595 2
#> 3 1 -14.60 -12.20 -0.1866335 -0.17668199 -14.786633 -12.37668199 2
#> 4 1 -14.20 -0.55 -0.5587304 0.60807608 -14.758730 0.05807608 2
#> 5 1 -5.40 -3.30 -0.1080907 0.20391297 -5.508091 -3.09608703 2
#> 6 1 -4.10 -2.55 0.4942018 -1.16087832 -3.605798 -3.71087832 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7420 -37550 5875
#> initial value 998.131940
#> iter 2 value 846.831959
#> iter 3 value 843.788527
#> iter 4 value 843.276354
#> iter 5 value 795.234119
#> iter 6 value 784.525805
#> iter 7 value 782.647092
#> iter 8 value 782.597032
#> iter 9 value 782.596933
#> iter 9 value 782.596932
#> iter 9 value 782.596932
#> final value 782.596932
#> converged
#> This is Run number 239
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.2890983 3.5597133 -0.8390983 -9.640287 1
#> 2 1 -3.10 -5.40 1.1299882 -0.9602333 -1.9700118 -6.360233 1
#> 3 1 -14.60 -12.20 0.8697001 0.4620590 -13.7302999 -11.737941 2
#> 4 1 -14.20 -0.55 0.5805506 1.9815165 -13.6194494 1.431517 2
#> 5 1 -5.40 -3.30 2.6877411 0.2876782 -2.7122589 -3.012322 1
#> 6 1 -4.10 -2.55 0.8949654 0.4084996 -3.2050346 -2.141500 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6380 -34775 5875
#> initial value 998.131940
#> iter 2 value 882.691341
#> iter 3 value 881.549074
#> iter 4 value 880.014825
#> iter 5 value 824.256500
#> iter 6 value 814.981499
#> iter 7 value 813.075504
#> iter 8 value 813.032190
#> iter 9 value 813.032080
#> iter 10 value 813.032049
#> iter 11 value 813.032001
#> iter 12 value 813.031971
#> iter 12 value 813.031971
#> iter 12 value 813.031971
#> final value 813.031971
#> converged
#> This is Run number 240
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.3841560 0.11059225 -0.165844 -13.0894077 1
#> 2 1 -3.10 -5.40 0.9281999 -0.89800441 -2.171800 -6.2980044 1
#> 3 1 -14.60 -12.20 1.3618357 -0.73407015 -13.238164 -12.9340701 2
#> 4 1 -14.20 -0.55 0.8958278 -0.43083585 -13.304172 -0.9808359 2
#> 5 1 -5.40 -3.30 -1.0988134 -0.04411912 -6.498813 -3.3441191 2
#> 6 1 -4.10 -2.55 0.5433744 -0.43859029 -3.556626 -2.9885903 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7820 -38000 5800
#> initial value 998.131940
#> iter 2 value 840.423027
#> iter 3 value 837.367774
#> iter 4 value 837.299185
#> iter 5 value 790.727760
#> iter 6 value 779.882840
#> iter 7 value 778.041992
#> iter 8 value 777.992136
#> iter 9 value 777.992039
#> iter 10 value 777.992010
#> iter 11 value 777.991973
#> iter 12 value 777.991934
#> iter 12 value 777.991934
#> iter 12 value 777.991934
#> final value 777.991934
#> converged
#> This is Run number 241
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.1826669 -0.2374472 -0.3673331 -13.4374472 1
#> 2 1 -3.10 -5.40 2.3782212 0.4718798 -0.7217788 -4.9281202 1
#> 3 1 -14.60 -12.20 1.7402193 1.1670404 -12.8597807 -11.0329596 2
#> 4 1 -14.20 -0.55 0.6788021 0.6815796 -13.5211979 0.1315796 2
#> 5 1 -5.40 -3.30 -0.3342822 0.3235480 -5.7342822 -2.9764520 2
#> 6 1 -4.10 -2.55 -0.7749447 1.3721732 -4.8749447 -1.1778268 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6620 -37950 6850
#> initial value 998.131940
#> iter 2 value 836.400381
#> iter 3 value 830.141909
#> iter 4 value 827.085290
#> iter 5 value 779.533379
#> iter 6 value 768.927739
#> iter 7 value 767.331539
#> iter 8 value 767.298789
#> iter 9 value 767.298723
#> iter 10 value 767.298672
#> iter 11 value 767.298625
#> iter 11 value 767.298621
#> iter 11 value 767.298621
#> final value 767.298621
#> converged
#> This is Run number 242
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.7769561 0.9946985 1.226956 -12.205301521 1
#> 2 1 -3.10 -5.40 0.7605927 -0.8563481 -2.339407 -6.256348070 1
#> 3 1 -14.60 -12.20 4.2047975 -0.8571613 -10.395203 -13.057161261 1
#> 4 1 -14.20 -0.55 0.5795358 0.5558129 -13.620464 0.005812856 2
#> 5 1 -5.40 -3.30 -0.4671461 0.6801192 -5.867146 -2.619880844 2
#> 6 1 -4.10 -2.55 -0.4459831 4.0886642 -4.545983 1.538664248 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7200 -37000 5975
#> initial value 998.131940
#> iter 2 value 853.956379
#> iter 3 value 851.248564
#> iter 4 value 850.627350
#> iter 5 value 800.768580
#> iter 6 value 790.294734
#> iter 7 value 788.405629
#> iter 8 value 788.356930
#> iter 9 value 788.356826
#> iter 9 value 788.356821
#> iter 9 value 788.356821
#> final value 788.356821
#> converged
#> This is Run number 243
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.24303574 1.134409368 0.6930357 -12.065591 1
#> 2 1 -3.10 -5.40 -0.06529325 0.004509223 -3.1652933 -5.395491 1
#> 3 1 -14.60 -12.20 2.41760723 4.109072262 -12.1823928 -8.090928 2
#> 4 1 -14.20 -0.55 -1.78068588 -0.456899638 -15.9806859 -1.006900 2
#> 5 1 -5.40 -3.30 -0.20977069 2.214450761 -5.6097707 -1.085549 2
#> 6 1 -4.10 -2.55 -0.31611234 0.227629671 -4.4161123 -2.322370 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7000 -37400 6750
#> initial value 998.131940
#> iter 2 value 844.335272
#> iter 3 value 840.292868
#> iter 4 value 839.527332
#> iter 5 value 789.778349
#> iter 6 value 779.163748
#> iter 7 value 777.512992
#> iter 8 value 777.478962
#> iter 9 value 777.478914
#> iter 10 value 777.478887
#> iter 11 value 777.478829
#> iter 12 value 777.478790
#> iter 12 value 777.478790
#> iter 12 value 777.478790
#> final value 777.478790
#> converged
#> This is Run number 244
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.1185496 2.3751419 -0.4314504 -10.824858 1
#> 2 1 -3.10 -5.40 -1.2794156 0.4968937 -4.3794156 -4.903106 1
#> 3 1 -14.60 -12.20 2.0370469 0.9784832 -12.5629531 -11.221517 2
#> 4 1 -14.20 -0.55 1.9878568 -0.4510366 -12.2121432 -1.001037 2
#> 5 1 -5.40 -3.30 -0.7728222 0.9917704 -6.1728222 -2.308230 2
#> 6 1 -4.10 -2.55 -0.6667971 -0.3786773 -4.7667971 -2.928677 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6740 -36650 5175
#> initial value 998.131940
#> iter 2 value 863.004922
#> iter 3 value 859.393760
#> iter 4 value 855.787717
#> iter 5 value 807.093841
#> iter 6 value 797.007143
#> iter 7 value 794.830121
#> iter 8 value 794.767063
#> iter 9 value 794.766865
#> iter 9 value 794.766858
#> iter 9 value 794.766858
#> final value 794.766858
#> converged
#> This is Run number 245
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.02164333 1.6880942 -0.5283567 -11.5119058 1
#> 2 1 -3.10 -5.40 -1.15377969 1.4392913 -4.2537797 -3.9607087 2
#> 3 1 -14.60 -12.20 3.10785763 1.0836570 -11.4921424 -11.1163430 2
#> 4 1 -14.20 -0.55 0.29265046 -0.3172216 -13.9073495 -0.8672216 2
#> 5 1 -5.40 -3.30 -0.68534003 -0.5186914 -6.0853400 -3.8186914 2
#> 6 1 -4.10 -2.55 1.40026965 -0.2121482 -2.6997303 -2.7621482 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6160 -35775 6875
#> initial value 998.131940
#> iter 2 value 865.147834
#> iter 3 value 861.967442
#> iter 4 value 859.654100
#> iter 5 value 805.117656
#> iter 6 value 795.271504
#> iter 7 value 793.594075
#> iter 8 value 793.561261
#> iter 9 value 793.561247
#> iter 10 value 793.561227
#> iter 11 value 793.561172
#> iter 12 value 793.561111
#> iter 12 value 793.561111
#> iter 12 value 793.561111
#> final value 793.561111
#> converged
#> This is Run number 246
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.3497388 0.6664119 -0.8997388 -12.5335881 1
#> 2 1 -3.10 -5.40 -0.4545210 3.3972272 -3.5545210 -2.0027728 2
#> 3 1 -14.60 -12.20 1.1674545 -0.9554242 -13.4325455 -13.1554242 2
#> 4 1 -14.20 -0.55 -0.5382219 1.0157685 -14.7382219 0.4657685 2
#> 5 1 -5.40 -3.30 -0.5589700 1.3021706 -5.9589700 -1.9978294 2
#> 6 1 -4.10 -2.55 3.2412103 2.0020780 -0.8587897 -0.5479220 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7220 -36875 6650
#> initial value 998.131940
#> iter 2 value 851.727089
#> iter 3 value 848.848616
#> iter 4 value 848.752040
#> iter 5 value 797.526080
#> iter 6 value 787.073831
#> iter 7 value 785.388240
#> iter 8 value 785.352463
#> iter 9 value 785.352416
#> iter 10 value 785.352387
#> iter 11 value 785.352362
#> iter 12 value 785.352284
#> iter 12 value 785.352284
#> iter 12 value 785.352284
#> final value 785.352284
#> converged
#> This is Run number 247
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.2888187 -0.4739682 -0.8388187 -13.673968 1
#> 2 1 -3.10 -5.40 2.7150291 -1.2848869 -0.3849709 -6.684887 1
#> 3 1 -14.60 -12.20 3.3549110 -0.5789699 -11.2450890 -12.778970 1
#> 4 1 -14.20 -0.55 0.6062672 -1.9996166 -13.5937328 -2.549617 2
#> 5 1 -5.40 -3.30 2.7352664 2.6868800 -2.6647336 -0.613120 2
#> 6 1 -4.10 -2.55 1.3120492 0.2055462 -2.7879508 -2.344454 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6600 -35650 6400
#> initial value 998.131940
#> iter 2 value 869.294196
#> iter 3 value 867.422357
#> iter 4 value 866.481343
#> iter 5 value 812.060388
#> iter 6 value 802.216567
#> iter 7 value 800.421084
#> iter 8 value 800.381293
#> iter 9 value 800.381213
#> iter 10 value 800.381181
#> iter 11 value 800.381129
#> iter 12 value 800.381092
#> iter 12 value 800.381092
#> iter 12 value 800.381092
#> final value 800.381092
#> converged
#> This is Run number 248
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.6030931 -0.1915626 0.05309309 -13.391563 1
#> 2 1 -3.10 -5.40 -0.4012817 3.1793942 -3.50128172 -2.220606 2
#> 3 1 -14.60 -12.20 -0.7204064 2.2044877 -15.32040640 -9.995512 2
#> 4 1 -14.20 -0.55 -0.1328821 5.1362567 -14.33288212 4.586257 2
#> 5 1 -5.40 -3.30 1.0544184 0.3946301 -4.34558155 -2.905370 2
#> 6 1 -4.10 -2.55 1.2116599 1.3483194 -2.88834006 -1.201681 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6460 -35575 5850
#> initial value 998.131940
#> iter 2 value 873.306767
#> iter 3 value 871.032499
#> iter 4 value 868.834425
#> iter 5 value 815.457420
#> iter 6 value 805.766527
#> iter 7 value 803.833440
#> iter 8 value 803.786946
#> iter 9 value 803.786837
#> iter 10 value 803.786811
#> iter 11 value 803.786770
#> iter 12 value 803.786741
#> iter 12 value 803.786741
#> iter 12 value 803.786741
#> final value 803.786741
#> converged
#> This is Run number 249
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.18443740 -1.71730110 0.6344374 -14.917301 1
#> 2 1 -3.10 -5.40 2.75696939 0.64660461 -0.3430306 -4.753395 1
#> 3 1 -14.60 -12.20 0.73324662 1.76537419 -13.8667534 -10.434626 2
#> 4 1 -14.20 -0.55 0.11555588 2.60154605 -14.0844441 2.051546 2
#> 5 1 -5.40 -3.30 1.19138713 -0.12325538 -4.2086129 -3.423255 2
#> 6 1 -4.10 -2.55 0.09576463 -0.09385245 -4.0042354 -2.643852 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6400 -37100 7200
#> initial value 998.131940
#> iter 2 value 845.978118
#> iter 3 value 840.724114
#> iter 4 value 838.364771
#> iter 5 value 787.334541
#> iter 6 value 776.998445
#> iter 7 value 775.394394
#> iter 8 value 775.364420
#> iter 9 value 775.364365
#> iter 10 value 775.364317
#> iter 11 value 775.364268
#> iter 11 value 775.364260
#> iter 11 value 775.364260
#> final value 775.364260
#> converged
#> This is Run number 250
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.70677441 2.80382302 0.1567744 -10.3961770 1
#> 2 1 -3.10 -5.40 -0.49241047 0.19138983 -3.5924105 -5.2086102 1
#> 3 1 -14.60 -12.20 0.02260755 3.05779528 -14.5773925 -9.1422047 2
#> 4 1 -14.20 -0.55 -0.13215107 0.31537873 -14.3321511 -0.2346213 2
#> 5 1 -5.40 -3.30 0.05273082 0.02646003 -5.3472692 -3.2735400 2
#> 6 1 -4.10 -2.55 -0.36584155 -1.00917930 -4.4658416 -3.5591793 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6380 -36250 7050
#> initial value 998.131940
#> iter 2 value 858.035684
#> iter 3 value 854.547087
#> iter 4 value 852.952103
#> iter 5 value 799.335417
#> iter 6 value 789.247390
#> iter 7 value 787.597530
#> iter 8 value 787.566112
#> iter 9 value 787.566074
#> iter 10 value 787.566056
#> iter 11 value 787.565999
#> iter 12 value 787.565959
#> iter 12 value 787.565959
#> iter 12 value 787.565959
#> final value 787.565959
#> converged
#> This is Run number 251
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.8633979 1.93995357 -1.413398 -11.2600464 1
#> 2 1 -3.10 -5.40 -0.3379980 1.54822353 -3.437998 -3.8517765 1
#> 3 1 -14.60 -12.20 -0.5677089 0.91043482 -15.167709 -11.2895652 2
#> 4 1 -14.20 -0.55 -0.7663440 -0.37453206 -14.966344 -0.9245321 2
#> 5 1 -5.40 -3.30 0.6832707 -0.80419609 -4.716729 -4.1041961 2
#> 6 1 -4.10 -2.55 -1.0207924 0.08287602 -5.120792 -2.4671240 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7340 -38400 5675
#> initial value 998.131940
#> iter 2 value 836.067172
#> iter 3 value 831.643204
#> iter 4 value 829.724410
#> iter 5 value 784.995935
#> iter 6 value 774.053144
#> iter 7 value 772.231215
#> iter 8 value 772.181132
#> iter 9 value 772.181070
#> iter 9 value 772.181065
#> iter 9 value 772.181065
#> final value 772.181065
#> converged
#> This is Run number 252
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.6285924 0.1429883 0.07859238 -13.057012 1
#> 2 1 -3.10 -5.40 0.7910657 -0.1141896 -2.30893434 -5.514190 1
#> 3 1 -14.60 -12.20 -0.7595728 1.3493265 -15.35957277 -10.850673 2
#> 4 1 -14.20 -0.55 1.3219221 -0.6248254 -12.87807789 -1.174825 2
#> 5 1 -5.40 -3.30 0.5216787 -0.3538833 -4.87832132 -3.653883 2
#> 6 1 -4.10 -2.55 3.2654131 -0.9166259 -0.83458690 -3.466626 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6180 -35200 5775
#> initial value 998.131940
#> iter 2 value 878.306116
#> iter 3 value 875.706095
#> iter 4 value 872.369395
#> iter 5 value 818.528768
#> iter 6 value 809.072973
#> iter 7 value 807.148564
#> iter 8 value 807.103638
#> iter 9 value 807.103538
#> iter 10 value 807.103515
#> iter 11 value 807.103481
#> iter 12 value 807.103460
#> iter 12 value 807.103460
#> iter 12 value 807.103460
#> final value 807.103460
#> converged
#> This is Run number 253
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.14601965 0.33108657 -0.4039803 -12.868913 1
#> 2 1 -3.10 -5.40 -0.44024854 1.11089733 -3.5402485 -4.289103 1
#> 3 1 -14.60 -12.20 1.02711495 1.19491520 -13.5728851 -11.005085 2
#> 4 1 -14.20 -0.55 1.39465622 2.27926982 -12.8053438 1.729270 2
#> 5 1 -5.40 -3.30 2.35617242 -0.03065405 -3.0438276 -3.330654 1
#> 6 1 -4.10 -2.55 0.02542222 1.30079612 -4.0745778 -1.249204 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6900 -37025 5500
#> initial value 998.131940
#> iter 2 value 856.387392
#> iter 3 value 852.868999
#> iter 4 value 850.284654
#> iter 5 value 801.777571
#> iter 6 value 791.425307
#> iter 7 value 789.397846
#> iter 8 value 789.341240
#> iter 9 value 789.341098
#> iter 10 value 789.341082
#> iter 11 value 789.341057
#> iter 12 value 789.341030
#> iter 12 value 789.341030
#> iter 12 value 789.341030
#> final value 789.341030
#> converged
#> This is Run number 254
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 4.2770840 -0.9876265 3.727084 -14.187627 1
#> 2 1 -3.10 -5.40 -0.8703434 1.6622501 -3.970343 -3.737750 2
#> 3 1 -14.60 -12.20 -0.0873493 1.2586506 -14.687349 -10.941349 2
#> 4 1 -14.20 -0.55 1.3611363 -1.5405143 -12.838864 -2.090514 2
#> 5 1 -5.40 -3.30 0.9970956 0.5490796 -4.402904 -2.750920 2
#> 6 1 -4.10 -2.55 -0.7565813 -1.6618103 -4.856581 -4.211810 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6600 -35125 6300
#> initial value 998.131940
#> iter 2 value 876.166774
#> iter 3 value 875.098827
#> iter 4 value 874.473562
#> iter 5 value 818.731289
#> iter 6 value 809.157745
#> iter 7 value 807.335542
#> iter 8 value 807.295080
#> iter 9 value 807.294983
#> iter 9 value 807.294978
#> iter 9 value 807.294978
#> final value 807.294978
#> converged
#> This is Run number 255
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.43166874 1.3723960 1.881669 -11.827604 1
#> 2 1 -3.10 -5.40 1.50163739 1.7077688 -1.598363 -3.692231 1
#> 3 1 -14.60 -12.20 1.04716632 0.7171094 -13.552834 -11.482891 2
#> 4 1 -14.20 -0.55 -0.32038884 -1.1431478 -14.520389 -1.693148 2
#> 5 1 -5.40 -3.30 -0.09400871 1.1477176 -5.494009 -2.152282 2
#> 6 1 -4.10 -2.55 -0.74432698 -1.0317317 -4.844327 -3.581732 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6580 -36450 5975
#> initial value 998.131940
#> iter 2 value 861.643071
#> iter 3 value 858.237064
#> iter 4 value 855.633984
#> iter 5 value 804.677488
#> iter 6 value 794.541572
#> iter 7 value 792.662897
#> iter 8 value 792.616707
#> iter 9 value 792.616621
#> iter 10 value 792.616600
#> iter 11 value 792.616562
#> iter 12 value 792.616531
#> iter 12 value 792.616531
#> iter 12 value 792.616531
#> final value 792.616531
#> converged
#> This is Run number 256
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.95647328 1.35205640 0.4064733 -11.84794360 1
#> 2 1 -3.10 -5.40 -0.07171851 0.08484824 -3.1717185 -5.31515176 1
#> 3 1 -14.60 -12.20 -1.19033905 1.20279084 -15.7903390 -10.99720916 2
#> 4 1 -14.20 -0.55 0.64354316 0.50577392 -13.5564568 -0.04422608 2
#> 5 1 -5.40 -3.30 2.35251732 -0.81967381 -3.0474827 -4.11967381 1
#> 6 1 -4.10 -2.55 -0.94091864 1.59920509 -5.0409186 -0.95079491 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6760 -37950 7050
#> initial value 998.131940
#> iter 2 value 835.066336
#> iter 3 value 829.208238
#> iter 4 value 827.296085
#> iter 5 value 779.096154
#> iter 6 value 768.470451
#> iter 7 value 766.894262
#> iter 8 value 766.863892
#> iter 9 value 766.863794
#> iter 10 value 766.863734
#> iter 11 value 766.863684
#> iter 11 value 766.863679
#> iter 11 value 766.863679
#> final value 766.863679
#> converged
#> This is Run number 257
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.5784256 0.6043153 0.02842565 -12.5956847 1
#> 2 1 -3.10 -5.40 0.7430814 0.2521758 -2.35691858 -5.1478242 1
#> 3 1 -14.60 -12.20 1.6917571 1.0056062 -12.90824292 -11.1943938 2
#> 4 1 -14.20 -0.55 -0.2611114 -0.3670253 -14.46111142 -0.9170253 2
#> 5 1 -5.40 -3.30 1.2799635 0.7942253 -4.12003646 -2.5057747 2
#> 6 1 -4.10 -2.55 0.6893978 0.1151406 -3.41060218 -2.4348594 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6720 -36225 6125
#> initial value 998.131940
#> iter 2 value 863.607205
#> iter 3 value 861.043622
#> iter 4 value 859.652159
#> iter 5 value 807.419976
#> iter 6 value 797.335150
#> iter 7 value 795.475803
#> iter 8 value 795.431284
#> iter 9 value 795.431194
#> iter 10 value 795.431178
#> iter 11 value 795.431132
#> iter 12 value 795.431083
#> iter 12 value 795.431083
#> iter 12 value 795.431083
#> final value 795.431083
#> converged
#> This is Run number 258
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -1.2365839 0.2515878 -1.786584 -12.9484122 1
#> 2 1 -3.10 -5.40 -1.3449420 -0.8062325 -4.444942 -6.2062325 1
#> 3 1 -14.60 -12.20 -0.6797954 0.5693697 -15.279795 -11.6306303 2
#> 4 1 -14.20 -0.55 2.1875367 0.7079137 -12.012463 0.1579137 2
#> 5 1 -5.40 -3.30 1.2026982 1.4892599 -4.197302 -1.8107401 2
#> 6 1 -4.10 -2.55 0.9044302 -0.7629164 -3.195570 -3.3129164 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6840 -36650 6825
#> initial value 998.131940
#> iter 2 value 853.992102
#> iter 3 value 850.859697
#> iter 4 value 850.265091
#> iter 5 value 798.065315
#> iter 6 value 787.721949
#> iter 7 value 786.044440
#> iter 8 value 786.010309
#> iter 9 value 786.010252
#> iter 10 value 786.010204
#> iter 11 value 786.010182
#> iter 12 value 786.010139
#> iter 12 value 786.010139
#> iter 12 value 786.010139
#> final value 786.010139
#> converged
#> This is Run number 259
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.16290373 -0.2026967 -0.7129037 -13.402697 1
#> 2 1 -3.10 -5.40 -1.44251632 4.2939501 -4.5425163 -1.106050 2
#> 3 1 -14.60 -12.20 0.33431021 5.9800954 -14.2656898 -6.219905 2
#> 4 1 -14.20 -0.55 -0.02794031 -1.4745660 -14.2279403 -2.024566 2
#> 5 1 -5.40 -3.30 2.11030767 -0.7653352 -3.2896923 -4.065335 1
#> 6 1 -4.10 -2.55 0.23907045 1.2301284 -3.8609296 -1.319872 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5980 -36125 5425
#> initial value 998.131940
#> iter 2 value 868.752798
#> iter 3 value 862.801289
#> iter 4 value 854.973001
#> iter 5 value 806.233080
#> iter 6 value 796.417189
#> iter 7 value 794.384222
#> iter 8 value 794.329680
#> iter 9 value 794.329537
#> iter 9 value 794.329528
#> iter 9 value 794.329524
#> final value 794.329524
#> converged
#> This is Run number 260
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.98032891 1.0055967 0.4303289 -12.1944033 1
#> 2 1 -3.10 -5.40 0.25058551 1.6017483 -2.8494145 -3.7982517 1
#> 3 1 -14.60 -12.20 -0.09909323 -0.4442047 -14.6990932 -12.6442047 2
#> 4 1 -14.20 -0.55 0.03527099 -0.2946315 -14.1647290 -0.8446315 2
#> 5 1 -5.40 -3.30 -0.18911473 -0.6037894 -5.5891147 -3.9037894 2
#> 6 1 -4.10 -2.55 1.27735360 0.1129826 -2.8226464 -2.4370174 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7620 -38275 5325
#> initial value 998.131940
#> iter 2 value 839.274892
#> iter 3 value 835.851622
#> iter 4 value 834.769445
#> iter 5 value 789.884099
#> iter 6 value 778.973792
#> iter 7 value 776.973870
#> iter 8 value 776.913000
#> iter 9 value 776.912849
#> iter 9 value 776.912839
#> iter 9 value 776.912839
#> final value 776.912839
#> converged
#> This is Run number 261
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.96646354 0.7920779 -1.516464 -12.407922 1
#> 2 1 -3.10 -5.40 0.99179247 -0.6281186 -2.108208 -6.028119 1
#> 3 1 -14.60 -12.20 -1.37708999 -0.6053112 -15.977090 -12.805311 2
#> 4 1 -14.20 -0.55 2.19602582 2.8138008 -12.003974 2.263801 2
#> 5 1 -5.40 -3.30 -0.08741177 -0.6125451 -5.487412 -3.912545 2
#> 6 1 -4.10 -2.55 1.44819307 0.3107284 -2.651807 -2.239272 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7440 -38350 5350
#> initial value 998.131940
#> iter 2 value 838.314537
#> iter 3 value 834.307852
#> iter 4 value 832.393552
#> iter 5 value 787.970384
#> iter 6 value 777.060832
#> iter 7 value 775.104252
#> iter 8 value 775.045601
#> iter 9 value 775.045478
#> iter 9 value 775.045466
#> iter 9 value 775.045466
#> final value 775.045466
#> converged
#> This is Run number 262
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.0037079 0.6362866 0.4537079 -12.563713 1
#> 2 1 -3.10 -5.40 0.8184227 0.4532423 -2.2815773 -4.946758 1
#> 3 1 -14.60 -12.20 2.1385046 -1.5134610 -12.4614954 -13.713461 1
#> 4 1 -14.20 -0.55 0.4350746 -0.4986116 -13.7649254 -1.048612 2
#> 5 1 -5.40 -3.30 -0.1639317 0.6188933 -5.5639317 -2.681107 2
#> 6 1 -4.10 -2.55 -0.2460598 0.6648865 -4.3460598 -1.885114 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6920 -36400 6025
#> initial value 998.131940
#> iter 2 value 861.770230
#> iter 3 value 859.385579
#> iter 4 value 858.443155
#> iter 5 value 806.775465
#> iter 6 value 796.594897
#> iter 7 value 794.698099
#> iter 8 value 794.650917
#> iter 9 value 794.650811
#> iter 10 value 794.650797
#> iter 11 value 794.650752
#> iter 12 value 794.650699
#> iter 12 value 794.650699
#> iter 12 value 794.650699
#> final value 794.650699
#> converged
#> This is Run number 263
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.1064328 0.1344452 -0.6564328 -13.065555 1
#> 2 1 -3.10 -5.40 -1.0135633 0.7102979 -4.1135633 -4.689702 1
#> 3 1 -14.60 -12.20 0.7072073 1.2524430 -13.8927927 -10.947557 2
#> 4 1 -14.20 -0.55 0.8532800 -0.9984387 -13.3467200 -1.548439 2
#> 5 1 -5.40 -3.30 -1.4060273 0.9814363 -6.8060273 -2.318564 2
#> 6 1 -4.10 -2.55 0.2676817 0.8387533 -3.8323183 -1.711247 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7420 -38975 6350
#> initial value 998.131940
#> iter 2 value 823.861506
#> iter 3 value 818.388829
#> iter 4 value 817.170255
#> iter 5 value 773.159240
#> iter 6 value 762.122314
#> iter 7 value 760.538311
#> iter 8 value 760.503123
#> iter 9 value 760.503034
#> iter 10 value 760.502971
#> iter 11 value 760.502913
#> iter 11 value 760.502907
#> iter 11 value 760.502907
#> final value 760.502907
#> converged
#> This is Run number 264
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.00642556 0.43056388 -0.5564256 -12.769436 1
#> 2 1 -3.10 -5.40 -1.68232730 0.09011343 -4.7823273 -5.309887 1
#> 3 1 -14.60 -12.20 1.39055833 -0.45223808 -13.2094417 -12.652238 2
#> 4 1 -14.20 -0.55 -1.51942860 3.14147112 -15.7194286 2.591471 2
#> 5 1 -5.40 -3.30 0.23310296 1.59000972 -5.1668970 -1.709990 2
#> 6 1 -4.10 -2.55 1.05400807 3.70403494 -3.0459919 1.154035 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6600 -36575 5600
#> initial value 998.131940
#> iter 2 value 861.979709
#> iter 3 value 858.234922
#> iter 4 value 854.790901
#> iter 5 value 805.126613
#> iter 6 value 794.994076
#> iter 7 value 792.999276
#> iter 8 value 792.946232
#> iter 9 value 792.946108
#> iter 10 value 792.946092
#> iter 11 value 792.946068
#> iter 12 value 792.946044
#> iter 12 value 792.946044
#> iter 12 value 792.946044
#> final value 792.946044
#> converged
#> This is Run number 265
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.59201938 0.7112506 -1.1420194 -12.4887494 1
#> 2 1 -3.10 -5.40 2.60433419 -0.3118044 -0.4956658 -5.7118044 1
#> 3 1 -14.60 -12.20 1.84390993 0.3141657 -12.7560901 -11.8858343 2
#> 4 1 -14.20 -0.55 -0.62284285 -0.4233888 -14.8228428 -0.9733888 2
#> 5 1 -5.40 -3.30 0.79472426 0.1330984 -4.6052757 -3.1669016 2
#> 6 1 -4.10 -2.55 0.07444471 0.3076175 -4.0255553 -2.2423825 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7120 -36950 6250
#> initial value 998.131940
#> iter 2 value 853.180173
#> iter 3 value 850.308846
#> iter 4 value 849.753350
#> iter 5 value 799.333082
#> iter 6 value 788.857594
#> iter 7 value 787.054374
#> iter 8 value 787.011077
#> iter 9 value 787.011002
#> iter 10 value 787.010972
#> iter 11 value 787.010924
#> iter 12 value 787.010885
#> iter 12 value 787.010885
#> iter 12 value 787.010885
#> final value 787.010885
#> converged
#> This is Run number 266
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.7561789 -1.1533740 0.2061789 -14.3533740 1
#> 2 1 -3.10 -5.40 -1.1591655 -0.5355807 -4.2591655 -5.9355807 1
#> 3 1 -14.60 -12.20 1.9871193 5.3075799 -12.6128807 -6.8924201 2
#> 4 1 -14.20 -0.55 0.2874433 -0.4168284 -13.9125567 -0.9668284 2
#> 5 1 -5.40 -3.30 0.2421598 -0.2910911 -5.1578402 -3.5910911 2
#> 6 1 -4.10 -2.55 0.7900595 -0.2504211 -3.3099405 -2.8004211 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6020 -35525 7375
#> initial value 998.131940
#> iter 2 value 865.091186
#> iter 3 value 862.123928
#> iter 4 value 860.216908
#> iter 5 value 803.949480
#> iter 6 value 794.220555
#> iter 7 value 792.606134
#> iter 8 value 792.578234
#> iter 8 value 792.578232
#> final value 792.578232
#> converged
#> This is Run number 267
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.53690419 0.05527475 -0.01309581 -13.1447253 1
#> 2 1 -3.10 -5.40 0.31703201 -0.87506669 -2.78296799 -6.2750667 1
#> 3 1 -14.60 -12.20 2.98981757 -0.39009447 -11.61018243 -12.5900945 1
#> 4 1 -14.20 -0.55 -0.58465443 1.21626142 -14.78465443 0.6662614 2
#> 5 1 -5.40 -3.30 -0.02292520 -0.72854987 -5.42292520 -4.0285499 2
#> 6 1 -4.10 -2.55 -0.01283511 -0.14918258 -4.11283511 -2.6991826 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6820 -36425 5900
#> initial value 998.131940
#> iter 2 value 862.206547
#> iter 3 value 859.543596
#> iter 4 value 858.035191
#> iter 5 value 806.772309
#> iter 6 value 796.618344
#> iter 7 value 794.692630
#> iter 8 value 794.643890
#> iter 9 value 794.643780
#> iter 10 value 794.643760
#> iter 11 value 794.643718
#> iter 12 value 794.643679
#> iter 12 value 794.643679
#> iter 12 value 794.643679
#> final value 794.643679
#> converged
#> This is Run number 268
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.27317575 -0.34889111 1.723176 -13.548891 1
#> 2 1 -3.10 -5.40 -0.31221079 0.17335812 -3.412211 -5.226642 1
#> 3 1 -14.60 -12.20 -0.17206578 -0.97039119 -14.772066 -13.170391 2
#> 4 1 -14.20 -0.55 0.76739730 -2.10131840 -13.432603 -2.651318 2
#> 5 1 -5.40 -3.30 -0.06283837 0.07068821 -5.462838 -3.229312 2
#> 6 1 -4.10 -2.55 0.17184848 -0.71489382 -3.928152 -3.264894 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6260 -36850 6300
#> initial value 998.131940
#> iter 2 value 854.771285
#> iter 3 value 849.406151
#> iter 4 value 844.679087
#> iter 5 value 795.180991
#> iter 6 value 784.931444
#> iter 7 value 783.182052
#> iter 8 value 783.141822
#> iter 9 value 783.141785
#> iter 9 value 783.141783
#> iter 9 value 783.141783
#> final value 783.141783
#> converged
#> This is Run number 269
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.20909039 1.0794813 -0.7590904 -12.1205187 1
#> 2 1 -3.10 -5.40 2.14998801 0.5620876 -0.9500120 -4.8379124 1
#> 3 1 -14.60 -12.20 0.02360503 0.8667716 -14.5763950 -11.3332284 2
#> 4 1 -14.20 -0.55 2.56688514 1.7737568 -11.6331149 1.2237568 2
#> 5 1 -5.40 -3.30 0.51267039 0.4018231 -4.8873296 -2.8981769 2
#> 6 1 -4.10 -2.55 0.50520356 2.3349762 -3.5947964 -0.2150238 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7100 -36800 6375
#> initial value 998.131940
#> iter 2 value 854.461166
#> iter 3 value 851.719800
#> iter 4 value 851.309938
#> iter 5 value 800.244447
#> iter 6 value 789.819621
#> iter 7 value 788.042192
#> iter 8 value 788.000887
#> iter 9 value 788.000817
#> iter 10 value 788.000786
#> iter 11 value 788.000736
#> iter 12 value 788.000696
#> iter 12 value 788.000696
#> iter 12 value 788.000696
#> final value 788.000696
#> converged
#> This is Run number 270
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.7343160 3.1962425 -1.284316 -10.0037575 1
#> 2 1 -3.10 -5.40 0.2285052 -0.6150899 -2.871495 -6.0150899 1
#> 3 1 -14.60 -12.20 -1.5072927 -0.8704191 -16.107293 -13.0704191 2
#> 4 1 -14.20 -0.55 0.5537104 0.2252658 -13.646290 -0.3247342 2
#> 5 1 -5.40 -3.30 -1.4327472 -0.8576995 -6.832747 -4.1576995 2
#> 6 1 -4.10 -2.55 -1.0304435 -1.1442524 -5.130444 -3.6942524 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5920 -36375 7225
#> initial value 998.131940
#> iter 2 value 855.431530
#> iter 3 value 850.055847
#> iter 4 value 845.964031
#> iter 5 value 793.206017
#> iter 6 value 783.212669
#> iter 7 value 781.593837
#> iter 8 value 781.563753
#> iter 9 value 781.563722
#> iter 10 value 781.563710
#> iter 11 value 781.563669
#> iter 12 value 781.563635
#> iter 12 value 781.563635
#> iter 12 value 781.563635
#> final value 781.563635
#> converged
#> This is Run number 271
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.4763114 1.65706721 -1.026311 -11.542933 1
#> 2 1 -3.10 -5.40 -0.4159060 -0.42304076 -3.515906 -5.823041 1
#> 3 1 -14.60 -12.20 1.8163061 0.16173269 -12.783694 -12.038267 2
#> 4 1 -14.20 -0.55 0.6978858 -0.55650109 -13.502114 -1.106501 2
#> 5 1 -5.40 -3.30 0.5032579 0.01309725 -4.896742 -3.286903 2
#> 6 1 -4.10 -2.55 -0.9441935 4.31226415 -5.044193 1.762264 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6660 -35825 5825
#> initial value 998.131940
#> iter 2 value 870.261639
#> iter 3 value 868.129252
#> iter 4 value 866.517638
#> iter 5 value 813.687592
#> iter 6 value 803.852860
#> iter 7 value 801.893794
#> iter 8 value 801.845186
#> iter 9 value 801.845064
#> iter 10 value 801.845040
#> iter 11 value 801.844997
#> iter 12 value 801.844963
#> iter 12 value 801.844963
#> iter 12 value 801.844963
#> final value 801.844963
#> converged
#> This is Run number 272
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.5985061 2.4942921 0.04850609 -10.7057079 1
#> 2 1 -3.10 -5.40 -0.8884202 -0.8972397 -3.98842018 -6.2972397 1
#> 3 1 -14.60 -12.20 2.9693288 1.4954536 -11.63067116 -10.7045464 2
#> 4 1 -14.20 -0.55 4.7431101 0.4225451 -9.45688993 -0.1274549 2
#> 5 1 -5.40 -3.30 5.6622344 0.2985312 0.26223436 -3.0014688 1
#> 6 1 -4.10 -2.55 -0.8091993 -0.9025903 -4.90919931 -3.4525903 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6160 -34375 6100
#> initial value 998.131940
#> iter 2 value 886.131938
#> iter 3 value 885.232851
#> iter 4 value 883.526796
#> iter 5 value 826.398310
#> iter 6 value 817.315433
#> iter 7 value 815.509657
#> iter 8 value 815.471574
#> iter 9 value 815.471487
#> iter 10 value 815.471456
#> iter 11 value 815.471404
#> iter 12 value 815.471375
#> iter 12 value 815.471375
#> iter 12 value 815.471375
#> final value 815.471375
#> converged
#> This is Run number 273
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.5685755 0.8166088 0.01857548 -12.38339115 1
#> 2 1 -3.10 -5.40 0.9216710 -1.1917557 -2.17832901 -6.59175565 1
#> 3 1 -14.60 -12.20 -0.8156665 0.2772132 -15.41566654 -11.92278678 2
#> 4 1 -14.20 -0.55 0.8676163 2.9686297 -13.33238372 2.41862971 2
#> 5 1 -5.40 -3.30 -0.1454097 2.1711444 -5.54540975 -1.12885558 2
#> 6 1 -4.10 -2.55 0.7589935 2.4858372 -3.34100648 -0.06416284 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6480 -36425 6650
#> initial value 998.131940
#> iter 2 value 858.195110
#> iter 3 value 854.655270
#> iter 4 value 852.719858
#> iter 5 value 800.376324
#> iter 6 value 790.210616
#> iter 7 value 788.498341
#> iter 8 value 788.462197
#> iter 9 value 788.462153
#> iter 10 value 788.462131
#> iter 11 value 788.462076
#> iter 12 value 788.462041
#> iter 12 value 788.462041
#> iter 12 value 788.462041
#> final value 788.462041
#> converged
#> This is Run number 274
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.98975976 2.0784573 0.4397598 -11.121543 1
#> 2 1 -3.10 -5.40 -0.29753219 -1.1411595 -3.3975322 -6.541159 1
#> 3 1 -14.60 -12.20 -0.33837436 5.1199302 -14.9383744 -7.080070 2
#> 4 1 -14.20 -0.55 -0.14278636 -1.0123141 -14.3427864 -1.562314 2
#> 5 1 -5.40 -3.30 0.33762856 -0.3581719 -5.0623714 -3.658172 2
#> 6 1 -4.10 -2.55 -0.08337477 0.7173648 -4.1833748 -1.832635 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5740 -33900 6675
#> initial value 998.131940
#> iter 2 value 888.209235
#> iter 3 value 887.476564
#> iter 4 value 885.248439
#> iter 5 value 825.971140
#> iter 6 value 817.107195
#> iter 7 value 815.472239
#> iter 8 value 815.442602
#> iter 9 value 815.442551
#> iter 9 value 815.442546
#> iter 9 value 815.442546
#> final value 815.442546
#> converged
#> This is Run number 275
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.58014789 -0.4008664 -1.130148 -13.600866 1
#> 2 1 -3.10 -5.40 0.33889473 -0.6833605 -2.761105 -6.083361 1
#> 3 1 -14.60 -12.20 0.02856126 1.4303827 -14.571439 -10.769617 2
#> 4 1 -14.20 -0.55 0.18990932 2.3034591 -14.010091 1.753459 2
#> 5 1 -5.40 -3.30 -0.52288498 -0.4995226 -5.922885 -3.799523 2
#> 6 1 -4.10 -2.55 0.23707718 0.8916151 -3.862923 -1.658385 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6780 -37050 5375
#> initial value 998.131940
#> iter 2 value 856.761065
#> iter 3 value 852.702316
#> iter 4 value 849.077457
#> iter 5 value 801.248094
#> iter 6 value 790.929877
#> iter 7 value 788.869275
#> iter 8 value 788.810495
#> iter 9 value 788.810340
#> iter 9 value 788.810329
#> iter 9 value 788.810329
#> final value 788.810329
#> converged
#> This is Run number 276
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.2009770 -0.6116204 0.650977 -13.8116204 1
#> 2 1 -3.10 -5.40 -0.2588705 0.5581381 -3.358871 -4.8418619 1
#> 3 1 -14.60 -12.20 0.8497262 -0.5215903 -13.750274 -12.7215903 2
#> 4 1 -14.20 -0.55 -0.5378658 0.4306919 -14.737866 -0.1193081 2
#> 5 1 -5.40 -3.30 3.2858700 0.6380959 -2.114130 -2.6619041 1
#> 6 1 -4.10 -2.55 1.1761258 -1.2247903 -2.923874 -3.7747903 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6040 -36675 6500
#> initial value 998.131940
#> iter 2 value 855.957161
#> iter 3 value 850.069926
#> iter 4 value 844.501649
#> iter 5 value 794.474960
#> iter 6 value 784.334478
#> iter 7 value 782.626486
#> iter 8 value 782.589080
#> iter 9 value 782.589053
#> iter 10 value 782.589038
#> iter 11 value 782.589006
#> iter 12 value 782.588986
#> iter 12 value 782.588986
#> iter 12 value 782.588986
#> final value 782.588986
#> converged
#> This is Run number 277
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.6601730 0.8804747 0.110173 -12.3195253 1
#> 2 1 -3.10 -5.40 -0.6621730 -0.7309346 -3.762173 -6.1309346 1
#> 3 1 -14.60 -12.20 -0.7303535 -0.1493881 -15.330353 -12.3493881 2
#> 4 1 -14.20 -0.55 1.9870570 4.3215054 -12.212943 3.7715054 2
#> 5 1 -5.40 -3.30 -0.9422506 -0.9382466 -6.342251 -4.2382466 2
#> 6 1 -4.10 -2.55 0.8283728 3.0379468 -3.271627 0.4879468 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6820 -38000 6325
#> initial value 998.131940
#> iter 2 value 838.686033
#> iter 3 value 833.166746
#> iter 4 value 830.188032
#> iter 5 value 783.571058
#> iter 6 value 772.849747
#> iter 7 value 771.172354
#> iter 8 value 771.133490
#> iter 9 value 771.133463
#> iter 10 value 771.133447
#> iter 11 value 771.133401
#> iter 12 value 771.133366
#> iter 12 value 771.133366
#> iter 12 value 771.133366
#> final value 771.133366
#> converged
#> This is Run number 278
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.3626523 -0.4714176 -0.1873477 -13.671418 1
#> 2 1 -3.10 -5.40 0.6222400 -0.3110334 -2.4777600 -5.711033 1
#> 3 1 -14.60 -12.20 0.1243548 -0.3058766 -14.4756452 -12.505877 2
#> 4 1 -14.20 -0.55 -0.3640955 -0.2364540 -14.5640955 -0.786454 2
#> 5 1 -5.40 -3.30 -0.1905371 0.3915192 -5.5905371 -2.908481 2
#> 6 1 -4.10 -2.55 0.5282355 -0.9273751 -3.5717645 -3.477375 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6100 -36200 6950
#> initial value 998.131940
#> iter 2 value 859.377984
#> iter 3 value 855.075684
#> iter 4 value 851.909547
#> iter 5 value 798.772798
#> iter 6 value 788.779736
#> iter 7 value 787.122407
#> iter 8 value 787.090146
#> iter 9 value 787.090095
#> iter 10 value 787.090049
#> iter 10 value 787.090038
#> iter 10 value 787.090031
#> final value 787.090031
#> converged
#> This is Run number 279
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 5.705380899 -0.4749229 5.155381 -13.6749229 1
#> 2 1 -3.10 -5.40 1.344130438 0.3189679 -1.755870 -5.0810321 1
#> 3 1 -14.60 -12.20 0.003440916 0.6267837 -14.596559 -11.5732163 2
#> 4 1 -14.20 -0.55 1.183241005 0.2979961 -13.016759 -0.2520039 2
#> 5 1 -5.40 -3.30 1.024614215 -0.4629716 -4.375386 -3.7629716 2
#> 6 1 -4.10 -2.55 1.309187596 1.5576441 -2.790812 -0.9923559 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6960 -36550 5625
#> initial value 998.131940
#> iter 2 value 861.920001
#> iter 3 value 859.379385
#> iter 4 value 857.930932
#> iter 5 value 807.440779
#> iter 6 value 797.264992
#> iter 7 value 795.236632
#> iter 8 value 795.181937
#> iter 9 value 795.181789
#> iter 10 value 795.181769
#> iter 11 value 795.181734
#> iter 12 value 795.181698
#> iter 12 value 795.181698
#> iter 12 value 795.181698
#> final value 795.181698
#> converged
#> This is Run number 280
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.7396128 -0.6276345 0.1896128 -13.827635 1
#> 2 1 -3.10 -5.40 -1.1570645 -1.0006201 -4.2570645 -6.400620 1
#> 3 1 -14.60 -12.20 0.2924908 1.7222168 -14.3075092 -10.477783 2
#> 4 1 -14.20 -0.55 -0.2199271 -0.7915231 -14.4199271 -1.341523 2
#> 5 1 -5.40 -3.30 0.2924287 -0.3762290 -5.1075713 -3.676229 2
#> 6 1 -4.10 -2.55 2.1317494 0.7008127 -1.9682506 -1.849187 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6380 -37250 5950
#> initial value 998.131940
#> iter 2 value 851.326289
#> iter 3 value 845.419993
#> iter 4 value 839.845722
#> iter 5 value 792.489121
#> iter 6 value 782.096060
#> iter 7 value 780.283824
#> iter 8 value 780.238041
#> iter 9 value 780.237989
#> iter 9 value 780.237978
#> iter 9 value 780.237978
#> final value 780.237978
#> converged
#> This is Run number 281
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.54774372 -0.41284347 0.9977437 -13.6128435 1
#> 2 1 -3.10 -5.40 0.24465517 -0.81480526 -2.8553448 -6.2148053 1
#> 3 1 -14.60 -12.20 -1.29473683 1.35616570 -15.8947368 -10.8438343 2
#> 4 1 -14.20 -0.55 -0.66893096 -0.09577448 -14.8689310 -0.6457745 2
#> 5 1 -5.40 -3.30 -0.03242911 0.39229891 -5.4324291 -2.9077011 2
#> 6 1 -4.10 -2.55 0.21777999 0.99765047 -3.8822200 -1.5523495 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6640 -36300 6450
#> initial value 998.131940
#> iter 2 value 860.874155
#> iter 3 value 857.999683
#> iter 4 value 856.634228
#> iter 5 value 804.095220
#> iter 6 value 793.954481
#> iter 7 value 792.187302
#> iter 8 value 792.147981
#> iter 9 value 792.147920
#> iter 10 value 792.147890
#> iter 11 value 792.147839
#> iter 12 value 792.147803
#> iter 12 value 792.147803
#> iter 12 value 792.147803
#> final value 792.147803
#> converged
#> This is Run number 282
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 3.2864113 -0.69662253 2.736411 -13.896623 1
#> 2 1 -3.10 -5.40 0.6902212 1.07798628 -2.409779 -4.322014 1
#> 3 1 -14.60 -12.20 1.1032195 0.96777001 -13.496780 -11.232230 2
#> 4 1 -14.20 -0.55 -0.7378084 1.82053544 -14.937808 1.270535 2
#> 5 1 -5.40 -3.30 -0.2568745 -0.02050383 -5.656874 -3.320504 2
#> 6 1 -4.10 -2.55 2.6384859 -0.58658253 -1.461514 -3.136583 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6840 -35575 4575
#> initial value 998.131940
#> iter 2 value 879.097570
#> iter 3 value 877.130116
#> iter 4 value 874.669522
#> iter 5 value 823.462651
#> iter 6 value 814.125480
#> iter 7 value 811.604819
#> iter 8 value 811.532306
#> iter 9 value 811.532007
#> iter 10 value 811.531989
#> iter 10 value 811.531985
#> iter 10 value 811.531977
#> final value 811.531977
#> converged
#> This is Run number 283
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.81960655 0.95757812 0.2696065 -12.2424219 1
#> 2 1 -3.10 -5.40 2.66732798 0.22656113 -0.4326720 -5.1734389 1
#> 3 1 -14.60 -12.20 -0.08323466 -0.37960087 -14.6832347 -12.5796009 2
#> 4 1 -14.20 -0.55 0.30176560 -0.43487428 -13.8982344 -0.9848743 2
#> 5 1 -5.40 -3.30 -0.94225668 1.01938144 -6.3422567 -2.2806186 2
#> 6 1 -4.10 -2.55 0.24371366 0.08413319 -3.8562863 -2.4658668 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7000 -37500 5900
#> initial value 998.131940
#> iter 2 value 847.833450
#> iter 3 value 843.882092
#> iter 4 value 841.865954
#> iter 5 value 793.998023
#> iter 6 value 783.381898
#> iter 7 value 781.534370
#> iter 8 value 781.486488
#> iter 9 value 781.486415
#> iter 10 value 781.486403
#> iter 11 value 781.486367
#> iter 12 value 781.486325
#> iter 12 value 781.486325
#> iter 12 value 781.486325
#> final value 781.486325
#> converged
#> This is Run number 284
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.4451904 -1.1154118 -0.9951904 -14.315412 1
#> 2 1 -3.10 -5.40 1.0799088 0.2948551 -2.0200912 -5.105145 1
#> 3 1 -14.60 -12.20 0.1658788 -0.2497995 -14.4341212 -12.449800 2
#> 4 1 -14.20 -0.55 -0.3982124 -1.4288659 -14.5982124 -1.978866 2
#> 5 1 -5.40 -3.30 -0.1466284 1.3390572 -5.5466284 -1.960943 2
#> 6 1 -4.10 -2.55 -0.6170453 -0.8307955 -4.7170453 -3.380796 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6080 -34550 6500
#> initial value 998.131940
#> iter 2 value 881.935559
#> iter 3 value 880.777943
#> iter 4 value 879.074483
#> iter 5 value 821.652313
#> iter 6 value 812.421824
#> iter 7 value 810.699724
#> iter 8 value 810.665357
#> iter 9 value 810.665291
#> iter 9 value 810.665280
#> iter 9 value 810.665280
#> final value 810.665280
#> converged
#> This is Run number 285
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.5479099 -1.6488209 -0.002090119 -14.848821 1
#> 2 1 -3.10 -5.40 0.1779844 0.3166805 -2.922015634 -5.083320 1
#> 3 1 -14.60 -12.20 4.4452700 2.1438407 -10.154729969 -10.056159 2
#> 4 1 -14.20 -0.55 1.7623506 1.2672410 -12.437649449 0.717241 2
#> 5 1 -5.40 -3.30 0.6155751 4.3057739 -4.784424883 1.005774 2
#> 6 1 -4.10 -2.55 1.2577544 -1.0777092 -2.842245599 -3.627709 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7200 -37050 5450
#> initial value 998.131940
#> iter 2 value 856.026864
#> iter 3 value 853.322463
#> iter 4 value 852.060935
#> iter 5 value 803.258261
#> iter 6 value 792.866554
#> iter 7 value 790.785039
#> iter 8 value 790.725343
#> iter 9 value 790.725168
#> iter 10 value 790.725152
#> iter 11 value 790.725122
#> iter 12 value 790.725085
#> iter 12 value 790.725085
#> iter 12 value 790.725085
#> final value 790.725085
#> converged
#> This is Run number 286
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.8790167 -1.0868957 0.3290167 -14.2868957 1
#> 2 1 -3.10 -5.40 -1.4579879 0.5811272 -4.5579879 -4.8188728 1
#> 3 1 -14.60 -12.20 -0.2103101 1.0708103 -14.8103101 -11.1291897 2
#> 4 1 -14.20 -0.55 2.3904336 0.7113696 -11.8095664 0.1613696 2
#> 5 1 -5.40 -3.30 0.2681184 3.9808359 -5.1318816 0.6808359 2
#> 6 1 -4.10 -2.55 1.6323693 3.6951274 -2.4676307 1.1451274 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7020 -36600 5425
#> initial value 998.131940
#> iter 2 value 862.225923
#> iter 3 value 859.726332
#> iter 4 value 858.187297
#> iter 5 value 808.174574
#> iter 6 value 798.016861
#> iter 7 value 795.905768
#> iter 8 value 795.846556
#> iter 9 value 795.846376
#> iter 10 value 795.846359
#> iter 11 value 795.846329
#> iter 12 value 795.846294
#> iter 12 value 795.846294
#> iter 12 value 795.846294
#> final value 795.846294
#> converged
#> This is Run number 287
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.1283939 0.05608599 -0.6783939 -13.1439140 1
#> 2 1 -3.10 -5.40 -1.0463562 -0.55877832 -4.1463562 -5.9587783 1
#> 3 1 -14.60 -12.20 0.4990947 1.01365855 -14.1009053 -11.1863415 2
#> 4 1 -14.20 -0.55 0.3815413 0.07392807 -13.8184587 -0.4760719 2
#> 5 1 -5.40 -3.30 -0.1403078 -0.47731552 -5.5403078 -3.7773155 2
#> 6 1 -4.10 -2.55 -0.5688859 0.74831414 -4.6688859 -1.8016859 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7020 -38450 6550
#> initial value 998.131940
#> iter 2 value 830.799214
#> iter 3 value 825.013440
#> iter 4 value 822.909591
#> iter 5 value 777.126786
#> iter 6 value 766.287440
#> iter 7 value 764.686151
#> iter 8 value 764.651501
#> iter 9 value 764.651432
#> iter 10 value 764.651377
#> iter 11 value 764.651324
#> iter 11 value 764.651318
#> iter 11 value 764.651318
#> final value 764.651318
#> converged
#> This is Run number 288
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.5040161 -0.4917471 -0.04598385 -13.6917471 1
#> 2 1 -3.10 -5.40 2.0306256 -1.0778264 -1.06937443 -6.4778264 1
#> 3 1 -14.60 -12.20 2.2393610 3.6392983 -12.36063905 -8.5607017 2
#> 4 1 -14.20 -0.55 -0.7345304 -0.2172503 -14.93453045 -0.7672503 2
#> 5 1 -5.40 -3.30 -0.1117259 -0.2407006 -5.51172587 -3.5407006 2
#> 6 1 -4.10 -2.55 0.6174830 -0.4393223 -3.48251700 -2.9893223 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6660 -37525 6725
#> initial value 998.131940
#> iter 2 value 843.042059
#> iter 3 value 837.864482
#> iter 4 value 835.469744
#> iter 5 value 786.538578
#> iter 6 value 775.988682
#> iter 7 value 774.345689
#> iter 8 value 774.311319
#> iter 9 value 774.311280
#> iter 10 value 774.311268
#> iter 11 value 774.311216
#> iter 12 value 774.311171
#> iter 12 value 774.311171
#> iter 12 value 774.311171
#> final value 774.311171
#> converged
#> This is Run number 289
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.8739509 -1.1946807 -1.423951 -14.394681 1
#> 2 1 -3.10 -5.40 0.5287856 0.6651384 -2.571214 -4.734862 1
#> 3 1 -14.60 -12.20 -0.2822350 2.3927257 -14.882235 -9.807274 2
#> 4 1 -14.20 -0.55 -0.9330111 2.2305223 -15.133011 1.680522 2
#> 5 1 -5.40 -3.30 -0.7603608 0.1199075 -6.160361 -3.180093 2
#> 6 1 -4.10 -2.55 -0.1190093 0.5645306 -4.219009 -1.985469 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7580 -37875 4775
#> initial value 998.131940
#> iter 2 value 847.538594
#> iter 3 value 844.597589
#> iter 4 value 843.004090
#> iter 5 value 797.785924
#> iter 6 value 787.196408
#> iter 7 value 784.850627
#> iter 8 value 784.771392
#> iter 9 value 784.771064
#> iter 9 value 784.771062
#> iter 9 value 784.771062
#> final value 784.771062
#> converged
#> This is Run number 290
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.9652044 0.2337695 0.4152044 -12.9662305 1
#> 2 1 -3.10 -5.40 0.7744345 -0.3321166 -2.3255655 -5.7321166 1
#> 3 1 -14.60 -12.20 1.3427277 -0.1226288 -13.2572723 -12.3226288 2
#> 4 1 -14.20 -0.55 1.1517677 0.8603531 -13.0482323 0.3103531 2
#> 5 1 -5.40 -3.30 0.7675438 0.4855555 -4.6324562 -2.8144445 2
#> 6 1 -4.10 -2.55 -0.1937696 2.3270554 -4.2937696 -0.2229446 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5900 -36900 7025
#> initial value 998.131940
#> iter 2 value 849.837654
#> iter 3 value 842.936168
#> iter 4 value 837.090567
#> iter 5 value 786.962029
#> iter 6 value 776.815727
#> iter 7 value 775.195743
#> iter 8 value 775.163366
#> iter 9 value 775.163340
#> iter 10 value 775.163319
#> iter 11 value 775.163287
#> iter 12 value 775.163271
#> iter 12 value 775.163271
#> iter 12 value 775.163271
#> final value 775.163271
#> converged
#> This is Run number 291
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.5615938 1.2791781 0.01159383 -11.9208219 1
#> 2 1 -3.10 -5.40 0.8620329 -0.5307779 -2.23796711 -5.9307779 1
#> 3 1 -14.60 -12.20 1.2301915 -0.9896422 -13.36980851 -13.1896422 2
#> 4 1 -14.20 -0.55 -0.6981630 0.9616887 -14.89816295 0.4116887 2
#> 5 1 -5.40 -3.30 0.1980059 -0.7750127 -5.20199411 -4.0750127 2
#> 6 1 -4.10 -2.55 0.8630388 2.8238901 -3.23696121 0.2738901 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7060 -35725 4850
#> initial value 998.131940
#> iter 2 value 875.889915
#> iter 3 value 874.494827
#> iter 4 value 873.281287
#> iter 5 value 821.569075
#> iter 6 value 812.049822
#> iter 7 value 809.627763
#> iter 8 value 809.558502
#> iter 9 value 809.558224
#> iter 9 value 809.558215
#> iter 9 value 809.558215
#> final value 809.558215
#> converged
#> This is Run number 292
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.8774011 0.28170459 -1.427401 -12.9182954 1
#> 2 1 -3.10 -5.40 1.2910675 -0.81491079 -1.808933 -6.2149108 1
#> 3 1 -14.60 -12.20 0.9201870 1.63155488 -13.679813 -10.5684451 2
#> 4 1 -14.20 -0.55 3.9744685 -0.01270237 -10.225532 -0.5627024 2
#> 5 1 -5.40 -3.30 1.0217914 0.12320168 -4.378209 -3.1767983 2
#> 6 1 -4.10 -2.55 1.7246697 1.27155220 -2.375330 -1.2784478 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5980 -35275 6150
#> initial value 998.131940
#> iter 2 value 875.448477
#> iter 3 value 872.238823
#> iter 4 value 868.264424
#> iter 5 value 814.199513
#> iter 6 value 804.673385
#> iter 7 value 802.866531
#> iter 8 value 802.827051
#> iter 9 value 802.826985
#> iter 10 value 802.826962
#> iter 11 value 802.826926
#> iter 12 value 802.826904
#> iter 12 value 802.826904
#> iter 12 value 802.826904
#> final value 802.826904
#> converged
#> This is Run number 293
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.3350087 -0.06292133 -0.8850087 -13.2629213 1
#> 2 1 -3.10 -5.40 2.4603722 0.08167944 -0.6396278 -5.3183206 1
#> 3 1 -14.60 -12.20 -0.2229428 -1.14614909 -14.8229428 -13.3461491 2
#> 4 1 -14.20 -0.55 -0.7043632 -0.24806806 -14.9043632 -0.7980681 2
#> 5 1 -5.40 -3.30 -0.9625043 -0.74973011 -6.3625043 -4.0497301 2
#> 6 1 -4.10 -2.55 -0.5885254 1.52467875 -4.6885254 -1.0253213 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6120 -35125 5025
#> initial value 998.131940
#> iter 2 value 882.842195
#> iter 3 value 879.283615
#> iter 4 value 873.965935
#> iter 5 value 822.123189
#> iter 6 value 812.877539
#> iter 7 value 810.682664
#> iter 8 value 810.625735
#> iter 9 value 810.625558
#> iter 9 value 810.625546
#> iter 9 value 810.625539
#> final value 810.625539
#> converged
#> This is Run number 294
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.18553148 7.3602639 -0.3644685 -5.8397361 1
#> 2 1 -3.10 -5.40 2.07330623 1.8135600 -1.0266938 -3.5864400 1
#> 3 1 -14.60 -12.20 -0.75014907 -0.8052104 -15.3501491 -13.0052104 2
#> 4 1 -14.20 -0.55 0.38504438 1.1487254 -13.8149556 0.5987254 2
#> 5 1 -5.40 -3.30 0.08941143 -0.5174878 -5.3105886 -3.8174878 2
#> 6 1 -4.10 -2.55 1.58384179 0.8235340 -2.5161582 -1.7264660 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6680 -35425 6425
#> initial value 998.131940
#> iter 2 value 871.823151
#> iter 3 value 870.443328
#> iter 4 value 869.925508
#> iter 5 value 814.791377
#> iter 6 value 805.035459
#> iter 7 value 803.239136
#> iter 8 value 803.199519
#> iter 9 value 803.199432
#> iter 10 value 803.199398
#> iter 11 value 803.199347
#> iter 12 value 803.199309
#> iter 12 value 803.199309
#> iter 12 value 803.199309
#> final value 803.199309
#> converged
#> This is Run number 295
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.1874187 0.1776931 0.6374187 -13.0223069 1
#> 2 1 -3.10 -5.40 0.2742298 0.7484585 -2.8257702 -4.6515415 1
#> 3 1 -14.60 -12.20 1.0278275 -0.2869529 -13.5721725 -12.4869529 2
#> 4 1 -14.20 -0.55 0.6135815 -0.2010984 -13.5864185 -0.7510984 2
#> 5 1 -5.40 -3.30 0.7120024 0.5957752 -4.6879976 -2.7042248 2
#> 6 1 -4.10 -2.55 -0.3149532 2.8580118 -4.4149532 0.3080118 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 8120 -38550 5025
#> initial value 998.131940
#> iter 2 value 835.969875
#> iter 3 value 833.202651
#> iter 4 value 832.987854
#> iter 5 value 789.200108
#> iter 6 value 778.229358
#> iter 7 value 776.090097
#> iter 8 value 776.018707
#> iter 9 value 776.018458
#> iter 9 value 776.018456
#> iter 9 value 776.018456
#> final value 776.018456
#> converged
#> This is Run number 296
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 6.3152586 0.004437711 5.765259 -13.1955623 1
#> 2 1 -3.10 -5.40 -0.2334836 2.398785798 -3.333484 -3.0012142 2
#> 3 1 -14.60 -12.20 4.1561868 0.047962865 -10.443813 -12.1520371 1
#> 4 1 -14.20 -0.55 1.9729937 -0.439765810 -12.227006 -0.9897658 2
#> 5 1 -5.40 -3.30 1.3953400 1.844243334 -4.004660 -1.4557567 2
#> 6 1 -4.10 -2.55 -0.4233438 -0.121351089 -4.523344 -2.6713511 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6780 -36075 5250
#> initial value 998.131940
#> iter 2 value 869.953430
#> iter 3 value 867.507369
#> iter 4 value 865.221324
#> iter 5 value 814.241212
#> iter 6 value 804.410365
#> iter 7 value 802.228757
#> iter 8 value 802.168514
#> iter 9 value 802.168321
#> iter 10 value 802.168307
#> iter 11 value 802.168282
#> iter 12 value 802.168252
#> iter 12 value 802.168252
#> iter 12 value 802.168252
#> final value 802.168252
#> converged
#> This is Run number 297
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.681792957 -0.4330232 -1.231793 -13.633023 1
#> 2 1 -3.10 -5.40 -0.001170216 1.8160730 -3.101170 -3.583927 1
#> 3 1 -14.60 -12.20 1.485477836 2.0359894 -13.114522 -10.164011 2
#> 4 1 -14.20 -0.55 0.834837748 -1.2172864 -13.365162 -1.767286 2
#> 5 1 -5.40 -3.30 -0.522906307 2.4181940 -5.922906 -0.881806 2
#> 6 1 -4.10 -2.55 1.071660164 0.2734758 -3.028340 -2.276524 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6740 -37125 5500
#> initial value 998.131940
#> iter 2 value 855.168365
#> iter 3 value 850.876520
#> iter 4 value 847.129608
#> iter 5 value 799.375524
#> iter 6 value 789.007876
#> iter 7 value 787.008143
#> iter 8 value 786.952415
#> iter 9 value 786.952287
#> iter 10 value 786.952274
#> iter 11 value 786.952255
#> iter 12 value 786.952233
#> iter 12 value 786.952233
#> iter 12 value 786.952233
#> final value 786.952233
#> converged
#> This is Run number 298
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.2046094 0.5772936 -0.3453906 -12.622706 1
#> 2 1 -3.10 -5.40 2.9524292 -0.2380436 -0.1475708 -5.638044 1
#> 3 1 -14.60 -12.20 1.0008024 0.2718060 -13.5991976 -11.928194 2
#> 4 1 -14.20 -0.55 0.1053789 -1.0992151 -14.0946211 -1.649215 2
#> 5 1 -5.40 -3.30 -0.4739480 1.0260748 -5.8739480 -2.273925 2
#> 6 1 -4.10 -2.55 1.2580610 1.1571542 -2.8419390 -1.392846 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7080 -37475 5825
#> initial value 998.131940
#> iter 2 value 848.501220
#> iter 3 value 844.828423
#> iter 4 value 843.108553
#> iter 5 value 795.182746
#> iter 6 value 784.567455
#> iter 7 value 782.687003
#> iter 8 value 782.637215
#> iter 9 value 782.637128
#> iter 10 value 782.637113
#> iter 11 value 782.637078
#> iter 12 value 782.637038
#> iter 12 value 782.637038
#> iter 12 value 782.637038
#> final value 782.637038
#> converged
#> This is Run number 299
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.2931532 -0.4835734 -0.2568468 -13.6835734 1
#> 2 1 -3.10 -5.40 1.6535919 -0.5787782 -1.4464081 -5.9787782 1
#> 3 1 -14.60 -12.20 0.8189650 -0.4268982 -13.7810350 -12.6268982 2
#> 4 1 -14.20 -0.55 -0.4997347 1.3083015 -14.6997347 0.7583015 2
#> 5 1 -5.40 -3.30 3.6693004 2.1513287 -1.7306996 -1.1486713 2
#> 6 1 -4.10 -2.55 -0.9193140 0.4369433 -5.0193140 -2.1130567 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6520 -35975 6600
#> initial value 998.131940
#> iter 2 value 864.167382
#> iter 3 value 861.573909
#> iter 4 value 860.265720
#> iter 5 value 806.516230
#> iter 6 value 796.521801
#> iter 7 value 794.782787
#> iter 8 value 794.745819
#> iter 9 value 794.745762
#> iter 10 value 794.745732
#> iter 11 value 794.745680
#> iter 12 value 794.745643
#> iter 12 value 794.745643
#> iter 12 value 794.745643
#> final value 794.745643
#> converged
#> This is Run number 300
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.640990 1.4106382 1.090990 -11.789362 1
#> 2 1 -3.10 -5.40 1.349527 -1.0480359 -1.750473 -6.448036 1
#> 3 1 -14.60 -12.20 -1.665966 0.2037640 -16.265966 -11.996236 2
#> 4 1 -14.20 -0.55 -0.181821 1.9091753 -14.381821 1.359175 2
#> 5 1 -5.40 -3.30 -0.274822 0.2935738 -5.674822 -3.006426 2
#> 6 1 -4.10 -2.55 -0.621793 0.7561703 -4.721793 -1.793830 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6820 -37375 7300
#> initial value 998.131940
#> iter 2 value 841.364580
#> iter 3 value 836.626606
#> iter 4 value 835.870394
#> iter 5 value 785.217896
#> iter 6 value 774.701732
#> iter 7 value 773.125527
#> iter 8 value 773.097780
#> iter 9 value 773.097687
#> iter 10 value 773.097629
#> iter 11 value 773.097575
#> iter 11 value 773.097571
#> iter 11 value 773.097571
#> final value 773.097571
#> converged
#> This is Run number 301
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.9983330 -0.55790114 1.448333 -13.757901 1
#> 2 1 -3.10 -5.40 -0.2001349 0.43700508 -3.300135 -4.962995 1
#> 3 1 -14.60 -12.20 3.9022307 2.48789290 -10.697769 -9.712107 2
#> 4 1 -14.20 -0.55 1.2114187 -1.38902985 -12.988581 -1.939030 2
#> 5 1 -5.40 -3.30 1.1986427 1.13071951 -4.201357 -2.169280 2
#> 6 1 -4.10 -2.55 -0.6882928 0.02351671 -4.788293 -2.526483 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7240 -37650 5700
#> initial value 998.131940
#> iter 2 value 846.597844
#> iter 3 value 843.088219
#> iter 4 value 841.679470
#> iter 5 value 794.388454
#> iter 6 value 783.696939
#> iter 7 value 781.781856
#> iter 8 value 781.729244
#> iter 9 value 781.729141
#> iter 10 value 781.729126
#> iter 11 value 781.729093
#> iter 12 value 781.729053
#> iter 12 value 781.729053
#> iter 12 value 781.729053
#> final value 781.729053
#> converged
#> This is Run number 302
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.607298744 -0.04778411 1.057299 -13.24778411 1
#> 2 1 -3.10 -5.40 -1.350849314 1.97102852 -4.450849 -3.42897148 2
#> 3 1 -14.60 -12.20 1.169553538 -0.83950430 -13.430446 -13.03950430 2
#> 4 1 -14.20 -0.55 -0.004745238 0.61030242 -14.204745 0.06030242 2
#> 5 1 -5.40 -3.30 -1.055921029 -0.51184826 -6.455921 -3.81184826 2
#> 6 1 -4.10 -2.55 0.520930474 0.03887691 -3.579070 -2.51112309 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7400 -37200 6275
#> initial value 998.131940
#> iter 2 value 849.382369
#> iter 3 value 846.521313
#> iter 4 value 846.394901
#> iter 5 value 796.706919
#> iter 6 value 786.115944
#> iter 7 value 784.344249
#> iter 8 value 784.301899
#> iter 9 value 784.301826
#> iter 10 value 784.301797
#> iter 11 value 784.301749
#> iter 12 value 784.301707
#> iter 12 value 784.301707
#> iter 12 value 784.301707
#> final value 784.301707
#> converged
#> This is Run number 303
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.2568711 -1.1376212 0.7068711 -14.337621 1
#> 2 1 -3.10 -5.40 0.6406116 1.8112933 -2.4593884 -3.588707 1
#> 3 1 -14.60 -12.20 0.5347469 -1.1372826 -14.0652531 -13.337283 2
#> 4 1 -14.20 -0.55 -0.2497649 2.5672865 -14.4497649 2.017287 2
#> 5 1 -5.40 -3.30 1.8637108 0.9753276 -3.5362892 -2.324672 2
#> 6 1 -4.10 -2.55 -0.8861916 0.8936942 -4.9861916 -1.656306 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7420 -37475 5675
#> initial value 998.131940
#> iter 2 value 848.911259
#> iter 3 value 846.047056
#> iter 4 value 845.406355
#> iter 5 value 797.429787
#> iter 6 value 786.781771
#> iter 7 value 784.819137
#> iter 8 value 784.764276
#> iter 9 value 784.764143
#> iter 9 value 784.764132
#> iter 9 value 784.764132
#> final value 784.764132
#> converged
#> This is Run number 304
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.3779813 0.6979649 0.8279813 -12.502035 1
#> 2 1 -3.10 -5.40 1.5644033 0.3679933 -1.5355967 -5.032007 1
#> 3 1 -14.60 -12.20 0.4928035 0.7641751 -14.1071965 -11.435825 2
#> 4 1 -14.20 -0.55 0.6663526 2.2768107 -13.5336474 1.726811 2
#> 5 1 -5.40 -3.30 0.2578789 -0.7108637 -5.1421211 -4.010864 2
#> 6 1 -4.10 -2.55 0.3329123 0.4527759 -3.7670877 -2.097224 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6300 -35100 6325
#> initial value 998.131940
#> iter 2 value 876.482322
#> iter 3 value 874.820127
#> iter 4 value 873.195650
#> iter 5 value 817.531664
#> iter 6 value 808.016255
#> iter 7 value 806.225835
#> iter 8 value 806.187335
#> iter 9 value 806.187257
#> iter 10 value 806.187239
#> iter 11 value 806.187188
#> iter 12 value 806.187142
#> iter 12 value 806.187142
#> iter 12 value 806.187142
#> final value 806.187142
#> converged
#> This is Run number 305
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.3220009 -1.0320882 0.7720009 -14.2320882 1
#> 2 1 -3.10 -5.40 -0.5900092 -0.1108428 -3.6900092 -5.5108428 1
#> 3 1 -14.60 -12.20 -0.4963308 1.5284879 -15.0963308 -10.6715121 2
#> 4 1 -14.20 -0.55 3.1915241 1.0544148 -11.0084759 0.5044148 2
#> 5 1 -5.40 -3.30 1.5976645 0.7814713 -3.8023355 -2.5185287 2
#> 6 1 -4.10 -2.55 -1.6722277 2.0297262 -5.7722277 -0.5202738 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6700 -37075 7025
#> initial value 998.131940
#> iter 2 value 847.258460
#> iter 3 value 842.987827
#> iter 4 value 841.785710
#> iter 5 value 790.666013
#> iter 6 value 780.231921
#> iter 7 value 778.606271
#> iter 8 value 778.575045
#> iter 9 value 778.574995
#> iter 10 value 778.574974
#> iter 11 value 778.574920
#> iter 12 value 778.574877
#> iter 12 value 778.574877
#> iter 12 value 778.574877
#> final value 778.574877
#> converged
#> This is Run number 306
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.2497052 -0.7076610 -0.3002948 -13.907661 1
#> 2 1 -3.10 -5.40 -0.7127727 1.3394050 -3.8127727 -4.060595 1
#> 3 1 -14.60 -12.20 -1.2307498 0.7494505 -15.8307498 -11.450550 2
#> 4 1 -14.20 -0.55 1.4064010 -1.0612300 -12.7935990 -1.611230 2
#> 5 1 -5.40 -3.30 -0.2549018 2.0682954 -5.6549018 -1.231705 2
#> 6 1 -4.10 -2.55 -0.5155848 0.1538194 -4.6155848 -2.396181 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7100 -38075 6400
#> initial value 998.131940
#> iter 2 value 836.962247
#> iter 3 value 832.177859
#> iter 4 value 830.694916
#> iter 5 value 783.746427
#> iter 6 value 772.930596
#> iter 7 value 771.266310
#> iter 8 value 771.228749
#> iter 9 value 771.228708
#> iter 10 value 771.228685
#> iter 11 value 771.228630
#> iter 12 value 771.228593
#> iter 12 value 771.228593
#> iter 12 value 771.228593
#> final value 771.228593
#> converged
#> This is Run number 307
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.3469958 0.8283039 -0.8969958 -12.371696 1
#> 2 1 -3.10 -5.40 -0.7510964 1.5486846 -3.8510964 -3.851315 1
#> 3 1 -14.60 -12.20 0.2971199 -0.5014110 -14.3028801 -12.701411 2
#> 4 1 -14.20 -0.55 2.2645527 2.3381285 -11.9354473 1.788128 2
#> 5 1 -5.40 -3.30 0.2848013 0.5045376 -5.1151987 -2.795462 2
#> 6 1 -4.10 -2.55 1.2535635 -0.6850597 -2.8464365 -3.235060 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6360 -35500 5075
#> initial value 998.131940
#> iter 2 value 878.072960
#> iter 3 value 874.930404
#> iter 4 value 870.703931
#> iter 5 value 819.254228
#> iter 6 value 809.791599
#> iter 7 value 807.582982
#> iter 8 value 807.523996
#> iter 9 value 807.523810
#> iter 9 value 807.523807
#> iter 9 value 807.523807
#> final value 807.523807
#> converged
#> This is Run number 308
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.6102850 -0.72906721 -1.160285 -13.9290672 1
#> 2 1 -3.10 -5.40 0.6859777 1.21955609 -2.414022 -4.1804439 1
#> 3 1 -14.60 -12.20 -0.1831808 -0.08548456 -14.783181 -12.2854846 2
#> 4 1 -14.20 -0.55 1.4778072 -0.27886641 -12.722193 -0.8288664 2
#> 5 1 -5.40 -3.30 0.3420663 0.03481497 -5.057934 -3.2651850 2
#> 6 1 -4.10 -2.55 1.4400400 2.38262639 -2.659960 -0.1673736 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6540 -34850 5800
#> initial value 998.131940
#> iter 2 value 882.130379
#> iter 3 value 881.206294
#> iter 4 value 880.116894
#> iter 5 value 824.564986
#> iter 6 value 815.250934
#> iter 7 value 813.300353
#> iter 8 value 813.254731
#> iter 9 value 813.254604
#> iter 10 value 813.254575
#> iter 11 value 813.254526
#> iter 12 value 813.254490
#> iter 12 value 813.254490
#> iter 12 value 813.254490
#> final value 813.254490
#> converged
#> This is Run number 309
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.6972253 -0.06040688 0.1472253 -13.2604069 1
#> 2 1 -3.10 -5.40 3.4914246 1.01083573 0.3914246 -4.3891643 1
#> 3 1 -14.60 -12.20 1.2617031 2.64390820 -13.3382969 -9.5560918 2
#> 4 1 -14.20 -0.55 0.1050001 0.43774738 -14.0949999 -0.1122526 2
#> 5 1 -5.40 -3.30 0.5930827 0.93942415 -4.8069173 -2.3605758 2
#> 6 1 -4.10 -2.55 -0.8009591 3.01225607 -4.9009591 0.4622561 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6360 -35975 6650
#> initial value 998.131940
#> iter 2 value 863.949951
#> iter 3 value 860.930625
#> iter 4 value 858.993822
#> iter 5 value 805.318542
#> iter 6 value 795.356984
#> iter 7 value 793.635916
#> iter 8 value 793.600047
#> iter 9 value 793.599998
#> iter 10 value 793.599971
#> iter 11 value 793.599918
#> iter 12 value 793.599884
#> iter 12 value 793.599884
#> iter 12 value 793.599884
#> final value 793.599884
#> converged
#> This is Run number 310
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.3163379 3.0526006 -0.2336621 -10.1473994 1
#> 2 1 -3.10 -5.40 0.3422784 -0.2752521 -2.7577216 -5.6752521 1
#> 3 1 -14.60 -12.20 -1.2621855 0.6792826 -15.8621855 -11.5207174 2
#> 4 1 -14.20 -0.55 -0.2052565 1.1684141 -14.4052565 0.6184141 2
#> 5 1 -5.40 -3.30 0.5513315 -0.9160649 -4.8486685 -4.2160649 2
#> 6 1 -4.10 -2.55 3.6462543 -0.4256594 -0.4537457 -2.9756594 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6500 -35825 4900
#> initial value 998.131940
#> iter 2 value 874.839738
#> iter 3 value 871.500597
#> iter 4 value 867.200391
#> iter 5 value 816.948226
#> iter 6 value 807.364833
#> iter 7 value 805.055493
#> iter 8 value 804.990147
#> iter 9 value 804.989915
#> iter 10 value 804.989901
#> iter 10 value 804.989897
#> iter 10 value 804.989892
#> final value 804.989892
#> converged
#> This is Run number 311
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.06644129 -1.610594 -0.61644129 -14.81059367 1
#> 2 1 -3.10 -5.40 3.07250546 4.147580 -0.02749454 -1.25242011 1
#> 3 1 -14.60 -12.20 -0.90934327 1.619909 -15.50934327 -10.58009068 2
#> 4 1 -14.20 -0.55 -0.09385742 1.531726 -14.29385742 0.98172611 2
#> 5 1 -5.40 -3.30 0.77297354 -1.116755 -4.62702646 -4.41675496 2
#> 6 1 -4.10 -2.55 1.51590646 2.501717 -2.58409354 -0.04828296 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6800 -35750 6125
#> initial value 998.131940
#> iter 2 value 869.467970
#> iter 3 value 867.810551
#> iter 4 value 867.129521
#> iter 5 value 813.399582
#> iter 6 value 803.521860
#> iter 7 value 801.639115
#> iter 8 value 801.594295
#> iter 9 value 801.594186
#> iter 9 value 801.594175
#> iter 9 value 801.594175
#> final value 801.594175
#> converged
#> This is Run number 312
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.38304627 0.8371866 -0.1669537 -12.362813 1
#> 2 1 -3.10 -5.40 3.83051701 0.1119824 0.7305170 -5.288018 1
#> 3 1 -14.60 -12.20 -0.08535074 -1.0916941 -14.6853507 -13.291694 2
#> 4 1 -14.20 -0.55 0.21169331 1.8297366 -13.9883067 1.279737 2
#> 5 1 -5.40 -3.30 -0.76842594 -0.5730646 -6.1684259 -3.873065 2
#> 6 1 -4.10 -2.55 -0.18614546 0.6077177 -4.2861455 -1.942282 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6480 -36075 5850
#> initial value 998.131940
#> iter 2 value 867.120452
#> iter 3 value 864.010524
#> iter 4 value 861.182815
#> iter 5 value 809.429060
#> iter 6 value 799.495625
#> iter 7 value 797.571389
#> iter 8 value 797.523895
#> iter 9 value 797.523794
#> iter 10 value 797.523771
#> iter 11 value 797.523736
#> iter 12 value 797.523709
#> iter 12 value 797.523709
#> iter 12 value 797.523709
#> final value 797.523709
#> converged
#> This is Run number 313
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.1812784 3.14153854 -0.3687216 -10.05846146 1
#> 2 1 -3.10 -5.40 1.2064234 -0.28848391 -1.8935766 -5.68848391 1
#> 3 1 -14.60 -12.20 0.3506477 2.04198342 -14.2493523 -10.15801658 2
#> 4 1 -14.20 -0.55 0.8648307 0.03645946 -13.3351693 -0.51354054 2
#> 5 1 -5.40 -3.30 -0.8402308 3.38834154 -6.2402308 0.08834154 2
#> 6 1 -4.10 -2.55 0.4767253 -1.13861373 -3.6232747 -3.68861373 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7320 -37500 5950
#> initial value 998.131940
#> iter 2 value 847.233405
#> iter 3 value 844.052024
#> iter 4 value 843.372579
#> iter 5 value 795.089989
#> iter 6 value 784.405810
#> iter 7 value 782.552223
#> iter 8 value 782.503983
#> iter 9 value 782.503896
#> iter 10 value 782.503869
#> iter 11 value 782.503828
#> iter 12 value 782.503790
#> iter 12 value 782.503790
#> iter 12 value 782.503790
#> final value 782.503790
#> converged
#> This is Run number 314
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -1.1565779 0.02391549 -1.706578 -13.1760845 1
#> 2 1 -3.10 -5.40 0.5004852 0.72217363 -2.599515 -4.6778264 1
#> 3 1 -14.60 -12.20 1.2310982 0.70994081 -13.368902 -11.4900592 2
#> 4 1 -14.20 -0.55 -0.2802186 3.52746538 -14.480219 2.9774654 2
#> 5 1 -5.40 -3.30 0.1463632 2.32545293 -5.253637 -0.9745471 2
#> 6 1 -4.10 -2.55 0.2170628 2.21287501 -3.882937 -0.3371250 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6220 -36650 8725
#> initial value 998.131940
#> iter 2 value 841.256397
#> iter 3 value 835.599384
#> iter 4 value 834.888615
#> iter 5 value 779.601080
#> iter 6 value 769.622138
#> iter 7 value 768.066257
#> iter 8 value 768.042823
#> iter 9 value 768.042580
#> iter 10 value 768.042564
#> iter 11 value 768.042552
#> iter 11 value 768.042548
#> iter 11 value 768.042548
#> final value 768.042548
#> converged
#> This is Run number 315
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 3.76183564 -0.70460996 3.211836 -13.904610 1
#> 2 1 -3.10 -5.40 1.18268001 0.32461025 -1.917320 -5.075390 1
#> 3 1 -14.60 -12.20 2.53802686 -0.03736845 -12.061973 -12.237368 1
#> 4 1 -14.20 -0.55 -1.57995906 2.05770659 -15.779959 1.507707 2
#> 5 1 -5.40 -3.30 -0.56439736 -1.28150305 -5.964397 -4.581503 2
#> 6 1 -4.10 -2.55 0.08279016 -0.20182162 -4.017210 -2.751822 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6940 -37650 6050
#> initial value 998.131940
#> iter 2 value 845.012479
#> iter 3 value 840.602550
#> iter 4 value 838.327648
#> iter 5 value 790.784414
#> iter 6 value 780.121874
#> iter 7 value 778.338038
#> iter 8 value 778.293589
#> iter 9 value 778.293538
#> iter 10 value 778.293517
#> iter 11 value 778.293477
#> iter 12 value 778.293446
#> iter 12 value 778.293446
#> iter 12 value 778.293446
#> final value 778.293446
#> converged
#> This is Run number 316
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.7965552 -1.064002657 -1.346555 -14.264003 1
#> 2 1 -3.10 -5.40 -0.4131647 -0.422543383 -3.513165 -5.822543 1
#> 3 1 -14.60 -12.20 0.1422531 0.400053263 -14.457747 -11.799947 2
#> 4 1 -14.20 -0.55 -0.7639814 -0.860508955 -14.963981 -1.410509 2
#> 5 1 -5.40 -3.30 0.2891939 0.246995319 -5.110806 -3.053005 2
#> 6 1 -4.10 -2.55 -1.2621039 -0.005546835 -5.362104 -2.555547 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7240 -38325 6050
#> initial value 998.131940
#> iter 2 value 835.243313
#> iter 3 value 830.554364
#> iter 4 value 828.869619
#> iter 5 value 783.287371
#> iter 6 value 772.372588
#> iter 7 value 770.652945
#> iter 8 value 770.610299
#> iter 9 value 770.610259
#> iter 10 value 770.610243
#> iter 11 value 770.610200
#> iter 12 value 770.610161
#> iter 12 value 770.610161
#> iter 12 value 770.610161
#> final value 770.610161
#> converged
#> This is Run number 317
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.4787110 2.5210636 -1.028711 -10.678936 1
#> 2 1 -3.10 -5.40 1.8811728 3.5635479 -1.218827 -1.836452 1
#> 3 1 -14.60 -12.20 0.4335318 -0.7818748 -14.166468 -12.981875 2
#> 4 1 -14.20 -0.55 0.1360821 2.4380137 -14.063918 1.888014 2
#> 5 1 -5.40 -3.30 -0.1798512 -0.4477006 -5.579851 -3.747701 2
#> 6 1 -4.10 -2.55 -0.5850508 0.8954721 -4.685051 -1.654528 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6340 -37050 6375
#> initial value 998.131940
#> iter 2 value 851.670293
#> iter 3 value 846.244125
#> iter 4 value 841.887347
#> iter 5 value 792.727061
#> iter 6 value 782.390529
#> iter 7 value 780.665492
#> iter 8 value 780.626280
#> iter 9 value 780.626248
#> iter 10 value 780.626231
#> iter 11 value 780.626195
#> iter 12 value 780.626170
#> iter 12 value 780.626170
#> iter 12 value 780.626170
#> final value 780.626170
#> converged
#> This is Run number 318
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.4165370 0.1441647 -0.133463 -13.0558353 1
#> 2 1 -3.10 -5.40 -0.8596713 0.6372407 -3.959671 -4.7627593 1
#> 3 1 -14.60 -12.20 -0.2495381 0.3451971 -14.849538 -11.8548029 2
#> 4 1 -14.20 -0.55 1.0513664 -0.7406339 -13.148634 -1.2906339 2
#> 5 1 -5.40 -3.30 -0.6927812 0.4121404 -6.092781 -2.8878596 2
#> 6 1 -4.10 -2.55 -0.4702430 1.6540793 -4.570243 -0.8959207 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6980 -37200 6700
#> initial value 998.131940
#> iter 2 value 847.359030
#> iter 3 value 843.638954
#> iter 4 value 842.921754
#> iter 5 value 792.615623
#> iter 6 value 782.061783
#> iter 7 value 780.388493
#> iter 8 value 780.353349
#> iter 9 value 780.353307
#> iter 10 value 780.353289
#> iter 11 value 780.353228
#> iter 12 value 780.353179
#> iter 12 value 780.353179
#> iter 12 value 780.353179
#> final value 780.353179
#> converged
#> This is Run number 319
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -1.320309407 -1.26284480 -1.8703094 -14.4628448 1
#> 2 1 -3.10 -5.40 -0.052450588 -0.09790543 -3.1524506 -5.4979054 1
#> 3 1 -14.60 -12.20 0.157832740 -0.05840505 -14.4421673 -12.2584051 2
#> 4 1 -14.20 -0.55 0.003431272 -1.43599400 -14.1965687 -1.9859940 2
#> 5 1 -5.40 -3.30 0.578315675 0.28074591 -4.8216843 -3.0192541 2
#> 6 1 -4.10 -2.55 3.174421096 2.22212364 -0.9255789 -0.3278764 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6740 -36100 5900
#> initial value 998.131940
#> iter 2 value 866.387334
#> iter 3 value 864.041425
#> iter 4 value 862.563045
#> iter 5 value 810.352070
#> iter 6 value 800.359431
#> iter 7 value 798.425098
#> iter 8 value 798.376894
#> iter 9 value 798.376779
#> iter 10 value 798.376757
#> iter 11 value 798.376714
#> iter 12 value 798.376675
#> iter 12 value 798.376675
#> iter 12 value 798.376675
#> final value 798.376675
#> converged
#> This is Run number 320
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.5828485 -0.26292506 -1.1328485 -13.4629251 1
#> 2 1 -3.10 -5.40 2.1204388 -0.53889334 -0.9795612 -5.9388933 1
#> 3 1 -14.60 -12.20 1.1707142 -0.27666801 -13.4292858 -12.4766680 2
#> 4 1 -14.20 -0.55 0.5277857 0.42647471 -13.6722143 -0.1235253 2
#> 5 1 -5.40 -3.30 0.7663105 -0.02191014 -4.6336895 -3.3219101 2
#> 6 1 -4.10 -2.55 0.3915405 0.99996541 -3.7084595 -1.5500346 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6200 -34625 5750
#> initial value 998.131940
#> iter 2 value 885.132638
#> iter 3 value 883.637827
#> iter 4 value 881.260600
#> iter 5 value 825.614068
#> iter 6 value 816.463495
#> iter 7 value 814.549715
#> iter 8 value 814.506696
#> iter 9 value 814.506592
#> iter 10 value 814.506562
#> iter 11 value 814.506521
#> iter 12 value 814.506499
#> iter 12 value 814.506499
#> iter 12 value 814.506499
#> final value 814.506499
#> converged
#> This is Run number 321
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.77679396 0.40989701 1.226794 -12.7901030 1
#> 2 1 -3.10 -5.40 0.42052211 1.33957815 -2.679478 -4.0604219 1
#> 3 1 -14.60 -12.20 0.39058497 -1.02432659 -14.209415 -13.2243266 2
#> 4 1 -14.20 -0.55 0.77436910 -0.07658757 -13.425631 -0.6265876 2
#> 5 1 -5.40 -3.30 -0.07679589 0.43632000 -5.476796 -2.8636800 2
#> 6 1 -4.10 -2.55 -0.10277564 1.20572344 -4.202776 -1.3442766 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6500 -37625 5850
#> initial value 998.131940
#> iter 2 value 846.700362
#> iter 3 value 840.476295
#> iter 4 value 834.749417
#> iter 5 value 788.769440
#> iter 6 value 778.239398
#> iter 7 value 776.428852
#> iter 8 value 776.381528
#> iter 9 value 776.381477
#> iter 9 value 776.381469
#> iter 9 value 776.381469
#> final value 776.381469
#> converged
#> This is Run number 322
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 3.3601056 0.20431077 2.8101056 -12.995689 1
#> 2 1 -3.10 -5.40 2.6879679 1.34184766 -0.4120321 -4.058152 1
#> 3 1 -14.60 -12.20 -0.4859990 0.09479664 -15.0859990 -12.105203 2
#> 4 1 -14.20 -0.55 -0.2415782 -1.03656624 -14.4415782 -1.586566 2
#> 5 1 -5.40 -3.30 2.0034138 0.15708329 -3.3965862 -3.142917 2
#> 6 1 -4.10 -2.55 0.1912403 -0.02744892 -3.9087597 -2.577449 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6840 -36950 5525
#> initial value 998.131940
#> iter 2 value 857.301291
#> iter 3 value 853.717144
#> iter 4 value 850.955814
#> iter 5 value 802.252132
#> iter 6 value 791.935707
#> iter 7 value 789.917337
#> iter 8 value 789.861543
#> iter 9 value 789.861405
#> iter 10 value 789.861389
#> iter 11 value 789.861364
#> iter 12 value 789.861338
#> iter 12 value 789.861338
#> iter 12 value 789.861338
#> final value 789.861338
#> converged
#> This is Run number 323
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 3.477773320 1.6820412 2.9277733 -11.517959 1
#> 2 1 -3.10 -5.40 2.474225605 1.1308427 -0.6257744 -4.269157 1
#> 3 1 -14.60 -12.20 3.444567338 -0.9016612 -11.1554327 -13.101661 1
#> 4 1 -14.20 -0.55 -0.569735221 -0.7182572 -14.7697352 -1.268257 2
#> 5 1 -5.40 -3.30 -0.003410661 1.5393109 -5.4034107 -1.760689 2
#> 6 1 -4.10 -2.55 -0.625506367 -0.6192034 -4.7255064 -3.169203 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7040 -37450 5950
#> initial value 998.131940
#> iter 2 value 848.210284
#> iter 3 value 844.457574
#> iter 4 value 842.779210
#> iter 5 value 794.577063
#> iter 6 value 783.964476
#> iter 7 value 782.123613
#> iter 8 value 782.076381
#> iter 9 value 782.076308
#> iter 9 value 782.076299
#> iter 9 value 782.076299
#> final value 782.076299
#> converged
#> This is Run number 324
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.6922533 -0.7118201 0.1422533 -13.911820 1
#> 2 1 -3.10 -5.40 1.6152205 1.0988518 -1.4847795 -4.301148 1
#> 3 1 -14.60 -12.20 -0.4396902 0.8235662 -15.0396902 -11.376434 2
#> 4 1 -14.20 -0.55 -0.3271572 -0.4989556 -14.5271572 -1.048956 2
#> 5 1 -5.40 -3.30 0.2422978 -0.6870420 -5.1577022 -3.987042 2
#> 6 1 -4.10 -2.55 -0.3264343 0.4908997 -4.4264343 -2.059100 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5960 -34950 6575
#> initial value 998.131940
#> iter 2 value 876.898694
#> iter 3 value 874.635747
#> iter 4 value 871.921528
#> iter 5 value 815.728582
#> iter 6 value 806.313812
#> iter 7 value 804.602128
#> iter 8 value 804.568056
#> iter 9 value 804.568003
#> iter 9 value 804.567996
#> iter 9 value 804.567996
#> final value 804.567996
#> converged
#> This is Run number 325
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.6533699 1.0398707 1.103370 -12.1601293 1
#> 2 1 -3.10 -5.40 0.7668371 -0.3214538 -2.333163 -5.7214538 1
#> 3 1 -14.60 -12.20 4.9687825 0.1822031 -9.631217 -12.0177969 1
#> 4 1 -14.20 -0.55 0.7293928 1.4161462 -13.470607 0.8661462 2
#> 5 1 -5.40 -3.30 -0.0960637 -0.2829810 -5.496064 -3.5829810 2
#> 6 1 -4.10 -2.55 -0.9057041 0.7796319 -5.005704 -1.7703681 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7180 -37300 6300
#> initial value 998.131940
#> iter 2 value 848.158469
#> iter 3 value 844.855892
#> iter 4 value 844.259752
#> iter 5 value 794.843103
#> iter 6 value 784.224178
#> iter 7 value 782.461724
#> iter 8 value 782.420051
#> iter 9 value 782.419991
#> iter 10 value 782.419964
#> iter 11 value 782.419914
#> iter 12 value 782.419873
#> iter 12 value 782.419873
#> iter 12 value 782.419873
#> final value 782.419873
#> converged
#> This is Run number 326
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.5687432 -0.5163382 1.018743 -13.7163382 1
#> 2 1 -3.10 -5.40 1.0769285 -0.2275984 -2.023071 -5.6275984 1
#> 3 1 -14.60 -12.20 0.2391273 0.8879006 -14.360873 -11.3120994 2
#> 4 1 -14.20 -0.55 -0.9400285 -0.1940973 -15.140028 -0.7440973 2
#> 5 1 -5.40 -3.30 -0.1523930 0.7417426 -5.552393 -2.5582574 2
#> 6 1 -4.10 -2.55 2.2610371 1.2101477 -1.838963 -1.3398523 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7880 -37025 4400
#> initial value 998.131940
#> iter 2 value 860.222230
#> iter 3 value 858.793161
#> iter 4 value 858.482216
#> iter 5 value 810.783143
#> iter 6 value 800.812862
#> iter 7 value 798.031069
#> iter 8 value 797.935592
#> iter 9 value 797.935071
#> iter 10 value 797.935041
#> iter 10 value 797.935032
#> iter 10 value 797.935023
#> final value 797.935023
#> converged
#> This is Run number 327
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.7401877 0.3937127 -1.290188 -12.8062873 1
#> 2 1 -3.10 -5.40 0.1067211 2.4577625 -2.993279 -2.9422375 2
#> 3 1 -14.60 -12.20 -0.0443529 1.5546421 -14.644353 -10.6453579 2
#> 4 1 -14.20 -0.55 0.8787433 1.4802802 -13.321257 0.9302802 2
#> 5 1 -5.40 -3.30 0.5968406 0.8527617 -4.803159 -2.4472383 2
#> 6 1 -4.10 -2.55 0.2133033 1.6452012 -3.886697 -0.9047988 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5840 -34600 7100
#> initial value 998.131940
#> iter 2 value 877.796478
#> iter 3 value 876.218733
#> iter 4 value 874.210384
#> iter 5 value 815.856901
#> iter 6 value 806.580116
#> iter 7 value 804.959078
#> iter 8 value 804.930557
#> iter 9 value 804.930517
#> iter 10 value 804.930494
#> iter 11 value 804.930442
#> iter 12 value 804.930410
#> iter 12 value 804.930410
#> iter 12 value 804.930410
#> final value 804.930410
#> converged
#> This is Run number 328
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 3.88035693 1.1249819 3.330357 -12.075018 1
#> 2 1 -3.10 -5.40 -0.01387095 1.3667530 -3.113871 -4.033247 1
#> 3 1 -14.60 -12.20 1.78581237 -1.5394749 -12.814188 -13.739475 1
#> 4 1 -14.20 -0.55 2.82692899 -0.7107197 -11.373071 -1.260720 2
#> 5 1 -5.40 -3.30 1.34738580 0.7189761 -4.052614 -2.581024 2
#> 6 1 -4.10 -2.55 2.06591899 0.5023476 -2.034081 -2.047652 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6820 -36900 6775
#> initial value 998.131940
#> iter 2 value 851.038133
#> iter 3 value 847.466795
#> iter 4 value 846.569805
#> iter 5 value 795.241974
#> iter 6 value 784.821044
#> iter 7 value 783.145602
#> iter 8 value 783.111073
#> iter 9 value 783.111020
#> iter 10 value 783.110996
#> iter 11 value 783.110958
#> iter 12 value 783.110906
#> iter 12 value 783.110906
#> iter 12 value 783.110906
#> final value 783.110906
#> converged
#> This is Run number 329
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.9243466 0.61506952 0.3743466 -12.584930 1
#> 2 1 -3.10 -5.40 -0.8114387 -0.08396695 -3.9114387 -5.483967 1
#> 3 1 -14.60 -12.20 0.9238880 -0.88102291 -13.6761120 -13.081023 2
#> 4 1 -14.20 -0.55 -0.5476386 2.35922462 -14.7476386 1.809225 2
#> 5 1 -5.40 -3.30 0.1578739 1.67923096 -5.2421261 -1.620769 2
#> 6 1 -4.10 -2.55 0.2014683 -0.10528051 -3.8985317 -2.655281 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6740 -36425 5975
#> initial value 998.131940
#> iter 2 value 861.863634
#> iter 3 value 858.996987
#> iter 4 value 857.244589
#> iter 5 value 805.934973
#> iter 6 value 795.781703
#> iter 7 value 793.887061
#> iter 8 value 793.840055
#> iter 9 value 793.839958
#> iter 10 value 793.839938
#> iter 11 value 793.839896
#> iter 12 value 793.839857
#> iter 12 value 793.839857
#> iter 12 value 793.839857
#> final value 793.839857
#> converged
#> This is Run number 330
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 4.86369893 -0.77027938 4.313699 -13.9702794 1
#> 2 1 -3.10 -5.40 -0.08605307 -1.03514888 -3.186053 -6.4351489 1
#> 3 1 -14.60 -12.20 0.08191019 1.74048399 -14.518090 -10.4595160 2
#> 4 1 -14.20 -0.55 0.50364376 -0.44592656 -13.696356 -0.9959266 2
#> 5 1 -5.40 -3.30 1.65134193 0.06401909 -3.748658 -3.2359809 2
#> 6 1 -4.10 -2.55 1.51790053 0.48842721 -2.582099 -2.0615728 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6140 -35600 5875
#> initial value 998.131940
#> iter 2 value 872.977279
#> iter 3 value 869.506667
#> iter 4 value 865.401330
#> iter 5 value 812.772718
#> iter 6 value 803.106256
#> iter 7 value 801.211693
#> iter 8 value 801.167057
#> iter 9 value 801.166970
#> iter 10 value 801.166950
#> iter 11 value 801.166921
#> iter 12 value 801.166900
#> iter 12 value 801.166900
#> iter 12 value 801.166900
#> final value 801.166900
#> converged
#> This is Run number 331
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.2788926 0.1661272 -0.8288926 -13.033873 1
#> 2 1 -3.10 -5.40 0.5271074 -0.1462079 -2.5728926 -5.546208 1
#> 3 1 -14.60 -12.20 -1.1741855 2.3301869 -15.7741855 -9.869813 2
#> 4 1 -14.20 -0.55 0.4341872 3.1122496 -13.7658128 2.562250 2
#> 5 1 -5.40 -3.30 0.9628985 -1.2478687 -4.4371015 -4.547869 1
#> 6 1 -4.10 -2.55 0.2032959 0.2691603 -3.8967041 -2.280840 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6700 -36450 5800
#> initial value 998.131940
#> iter 2 value 862.500254
#> iter 3 value 859.426003
#> iter 4 value 857.156861
#> iter 5 value 806.366057
#> iter 6 value 796.237467
#> iter 7 value 794.292971
#> iter 8 value 794.243183
#> iter 9 value 794.243073
#> iter 10 value 794.243051
#> iter 11 value 794.243015
#> iter 12 value 794.242985
#> iter 12 value 794.242985
#> iter 12 value 794.242985
#> final value 794.242985
#> converged
#> This is Run number 332
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -1.2678060 0.8262941 -1.817806 -12.3737059 1
#> 2 1 -3.10 -5.40 0.9470088 0.6969125 -2.152991 -4.7030875 1
#> 3 1 -14.60 -12.20 0.1231191 -0.8676516 -14.476881 -13.0676516 2
#> 4 1 -14.20 -0.55 1.2798466 -0.1999124 -12.920153 -0.7499124 2
#> 5 1 -5.40 -3.30 -1.1269882 0.8529508 -6.526988 -2.4470492 2
#> 6 1 -4.10 -2.55 0.3764545 -1.5433221 -3.723546 -4.0933221 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7480 -38650 5700
#> initial value 998.131940
#> iter 2 value 832.152077
#> iter 3 value 827.717087
#> iter 4 value 826.180275
#> iter 5 value 782.103999
#> iter 6 value 771.066560
#> iter 7 value 769.283406
#> iter 8 value 769.234872
#> iter 9 value 769.234821
#> iter 10 value 769.234802
#> iter 11 value 769.234768
#> iter 12 value 769.234737
#> iter 12 value 769.234737
#> iter 12 value 769.234737
#> final value 769.234737
#> converged
#> This is Run number 333
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.3490310 -0.1273812 1.799031 -13.3273812 1
#> 2 1 -3.10 -5.40 0.2766099 0.5252859 -2.823390 -4.8747141 1
#> 3 1 -14.60 -12.20 -0.1884944 1.9358245 -14.788494 -10.2641755 2
#> 4 1 -14.20 -0.55 1.0864238 1.4427597 -13.113576 0.8927597 2
#> 5 1 -5.40 -3.30 0.7354794 1.0999689 -4.664521 -2.2000311 2
#> 6 1 -4.10 -2.55 1.4017279 -0.3080822 -2.698272 -2.8580822 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6940 -38225 6675
#> initial value 998.131940
#> iter 2 value 833.350457
#> iter 3 value 827.691716
#> iter 4 value 825.699386
#> iter 5 value 778.969330
#> iter 6 value 768.198504
#> iter 7 value 766.596741
#> iter 8 value 766.563097
#> iter 9 value 766.563029
#> iter 10 value 766.562973
#> iter 11 value 766.562919
#> iter 11 value 766.562913
#> iter 11 value 766.562913
#> final value 766.562913
#> converged
#> This is Run number 334
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -1.7090186 0.6004960 -2.2590186 -12.59950403 1
#> 2 1 -3.10 -5.40 1.5617609 -0.1184189 -1.5382391 -5.51841892 1
#> 3 1 -14.60 -12.20 -0.1111119 0.8438491 -14.7111119 -11.35615086 2
#> 4 1 -14.20 -0.55 -1.0824296 0.5921102 -15.2824296 0.04211023 2
#> 5 1 -5.40 -3.30 1.6890253 1.2933114 -3.7109747 -2.00668860 2
#> 6 1 -4.10 -2.55 4.8490447 0.2966792 0.7490447 -2.25332077 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6780 -37600 6550
#> initial value 998.131940
#> iter 2 value 842.977454
#> iter 3 value 838.081294
#> iter 4 value 835.913238
#> iter 5 value 787.418903
#> iter 6 value 776.807664
#> iter 7 value 775.137978
#> iter 8 value 775.101500
#> iter 9 value 775.101479
#> iter 10 value 775.101459
#> iter 11 value 775.101405
#> iter 12 value 775.101355
#> iter 12 value 775.101355
#> iter 12 value 775.101355
#> final value 775.101355
#> converged
#> This is Run number 335
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.3281021 -1.3112394 -0.8781021 -14.511239 1
#> 2 1 -3.10 -5.40 0.3326677 -0.5025566 -2.7673323 -5.902557 1
#> 3 1 -14.60 -12.20 0.1542210 0.1821192 -14.4457790 -12.017881 2
#> 4 1 -14.20 -0.55 2.1667916 -0.6395718 -12.0332084 -1.189572 2
#> 5 1 -5.40 -3.30 0.5547510 0.2075830 -4.8452490 -3.092417 2
#> 6 1 -4.10 -2.55 2.8869171 -0.9764866 -1.2130829 -3.526487 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6840 -36100 6525
#> initial value 998.131940
#> iter 2 value 862.816079
#> iter 3 value 860.657450
#> iter 4 value 860.180099
#> iter 5 value 806.806410
#> iter 6 value 796.700011
#> iter 7 value 794.934644
#> iter 8 value 794.895682
#> iter 9 value 794.895611
#> iter 10 value 794.895579
#> iter 11 value 794.895528
#> iter 12 value 794.895488
#> iter 12 value 794.895488
#> iter 12 value 794.895488
#> final value 794.895488
#> converged
#> This is Run number 336
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.8061927 1.85988252 -1.356193 -11.340117 1
#> 2 1 -3.10 -5.40 2.3151210 2.46655237 -0.784879 -2.933448 1
#> 3 1 -14.60 -12.20 -0.6566790 -0.36423295 -15.256679 -12.564233 2
#> 4 1 -14.20 -0.55 0.5354102 -0.85796837 -13.664590 -1.407968 2
#> 5 1 -5.40 -3.30 -0.9513831 0.09034961 -6.351383 -3.209650 2
#> 6 1 -4.10 -2.55 -0.8303970 0.14312035 -4.930397 -2.406880 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6140 -36150 6025
#> initial value 998.131940
#> iter 2 value 865.349596
#> iter 3 value 860.826827
#> iter 4 value 855.974086
#> iter 5 value 804.934936
#> iter 6 value 794.999117
#> iter 7 value 793.156420
#> iter 8 value 793.112827
#> iter 9 value 793.112759
#> iter 10 value 793.112743
#> iter 11 value 793.112716
#> iter 12 value 793.112696
#> iter 12 value 793.112696
#> iter 12 value 793.112696
#> final value 793.112696
#> converged
#> This is Run number 337
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.7310877 -0.05659193 1.181088 -13.256592 1
#> 2 1 -3.10 -5.40 1.3311154 0.14351938 -1.768885 -5.256481 1
#> 3 1 -14.60 -12.20 0.8490185 2.93607672 -13.750982 -9.263923 2
#> 4 1 -14.20 -0.55 2.2298945 -0.62429104 -11.970105 -1.174291 2
#> 5 1 -5.40 -3.30 1.9368174 0.60068157 -3.463183 -2.699318 2
#> 6 1 -4.10 -2.55 -0.6851195 -0.18779266 -4.785119 -2.737793 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6680 -36550 6425
#> initial value 998.131940
#> iter 2 value 857.785737
#> iter 3 value 854.573551
#> iter 4 value 853.064724
#> iter 5 value 801.344041
#> iter 6 value 791.097609
#> iter 7 value 789.334383
#> iter 8 value 789.294740
#> iter 9 value 789.294683
#> iter 10 value 789.294655
#> iter 11 value 789.294604
#> iter 12 value 789.294568
#> iter 12 value 789.294568
#> iter 12 value 789.294568
#> final value 789.294568
#> converged
#> This is Run number 338
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.0585384 1.1270471 1.508538 -12.0729529 1
#> 2 1 -3.10 -5.40 0.9335246 -0.5797469 -2.166475 -5.9797469 1
#> 3 1 -14.60 -12.20 0.2799264 1.1041563 -14.320074 -11.0958437 2
#> 4 1 -14.20 -0.55 0.4603624 1.2807361 -13.739638 0.7307361 2
#> 5 1 -5.40 -3.30 0.8458892 0.3991329 -4.554111 -2.9008671 2
#> 6 1 -4.10 -2.55 -0.4037477 2.3670843 -4.503748 -0.1829157 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6780 -36750 6300
#> initial value 998.131940
#> iter 2 value 855.830369
#> iter 3 value 852.536172
#> iter 4 value 851.052111
#> iter 5 value 800.122730
#> iter 6 value 789.787930
#> iter 7 value 788.000720
#> iter 8 value 787.959075
#> iter 9 value 787.959013
#> iter 10 value 787.958985
#> iter 11 value 787.958937
#> iter 12 value 787.958901
#> iter 12 value 787.958901
#> iter 12 value 787.958901
#> final value 787.958901
#> converged
#> This is Run number 339
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.674421758 -0.03332946 1.124422 -13.2333295 1
#> 2 1 -3.10 -5.40 -0.006626869 1.19711314 -3.106627 -4.2028869 1
#> 3 1 -14.60 -12.20 0.844177777 0.41942712 -13.755822 -11.7805729 2
#> 4 1 -14.20 -0.55 0.498850478 1.00589564 -13.701150 0.4558956 2
#> 5 1 -5.40 -3.30 1.023675092 1.12510686 -4.376325 -2.1748931 2
#> 6 1 -4.10 -2.55 1.047682841 1.28008706 -3.052317 -1.2699129 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7000 -38100 6125
#> initial value 998.131940
#> iter 2 value 838.261722
#> iter 3 value 833.209904
#> iter 4 value 830.735112
#> iter 5 value 784.568077
#> iter 6 value 773.768717
#> iter 7 value 772.051082
#> iter 8 value 772.009227
#> iter 9 value 772.009192
#> iter 9 value 772.009181
#> iter 9 value 772.009179
#> final value 772.009179
#> converged
#> This is Run number 340
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.3323933 3.7790035 0.7823933 -9.4209965 1
#> 2 1 -3.10 -5.40 0.9628483 1.7376527 -2.1371517 -3.6623473 1
#> 3 1 -14.60 -12.20 0.8653982 3.5633200 -13.7346018 -8.6366800 2
#> 4 1 -14.20 -0.55 0.1901031 0.7382501 -14.0098969 0.1882501 2
#> 5 1 -5.40 -3.30 0.4164907 -0.2249676 -4.9835093 -3.5249676 2
#> 6 1 -4.10 -2.55 -0.3265686 -0.6020052 -4.4265686 -3.1520052 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6980 -37375 6175
#> initial value 998.131940
#> iter 2 value 848.047080
#> iter 3 value 844.225332
#> iter 4 value 842.706047
#> iter 5 value 793.889404
#> iter 6 value 783.296606
#> iter 7 value 781.515671
#> iter 8 value 781.472537
#> iter 9 value 781.472481
#> iter 10 value 781.472456
#> iter 11 value 781.472410
#> iter 12 value 781.472375
#> iter 12 value 781.472375
#> iter 12 value 781.472375
#> final value 781.472375
#> converged
#> This is Run number 341
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.52744460 0.01829748 1.977445 -13.181703 1
#> 2 1 -3.10 -5.40 1.45029588 0.03812024 -1.649704 -5.361880 1
#> 3 1 -14.60 -12.20 -0.86298530 -0.48867726 -15.462985 -12.688677 2
#> 4 1 -14.20 -0.55 0.41982488 -0.74962364 -13.780175 -1.299624 2
#> 5 1 -5.40 -3.30 0.61552352 -0.59714879 -4.784476 -3.897149 2
#> 6 1 -4.10 -2.55 -0.08952698 -0.32314967 -4.189527 -2.873150 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7180 -36325 5925
#> initial value 998.131940
#> iter 2 value 863.005745
#> iter 3 value 861.165583
#> iter 4 value 860.870269
#> iter 5 value 809.066118
#> iter 6 value 798.910615
#> iter 7 value 796.956560
#> iter 8 value 796.906102
#> iter 9 value 796.905965
#> iter 9 value 796.905958
#> iter 9 value 796.905958
#> final value 796.905958
#> converged
#> This is Run number 342
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.8355194 0.4169671 1.285519 -12.7830329 1
#> 2 1 -3.10 -5.40 1.1297618 1.5492209 -1.970238 -3.8507791 1
#> 3 1 -14.60 -12.20 2.5621876 0.4998519 -12.037812 -11.7001481 2
#> 4 1 -14.20 -0.55 1.2979801 0.2619773 -12.902020 -0.2880227 2
#> 5 1 -5.40 -3.30 0.6539847 0.4072520 -4.746015 -2.8927480 2
#> 6 1 -4.10 -2.55 0.5487674 -0.5478714 -3.551233 -3.0978714 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6460 -36325 6075
#> initial value 998.131940
#> iter 2 value 862.761014
#> iter 3 value 859.213783
#> iter 4 value 856.306253
#> iter 5 value 804.928603
#> iter 6 value 794.854917
#> iter 7 value 793.008264
#> iter 8 value 792.964207
#> iter 9 value 792.964133
#> iter 10 value 792.964112
#> iter 11 value 792.964074
#> iter 12 value 792.964043
#> iter 12 value 792.964043
#> iter 12 value 792.964043
#> final value 792.964043
#> converged
#> This is Run number 343
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.2295212 0.21847166 -0.3204788 -12.981528 1
#> 2 1 -3.10 -5.40 -0.4953123 -0.22118975 -3.5953123 -5.621190 1
#> 3 1 -14.60 -12.20 -0.8800290 2.55215614 -15.4800290 -9.647844 2
#> 4 1 -14.20 -0.55 -0.3294425 0.04112903 -14.5294425 -0.508871 2
#> 5 1 -5.40 -3.30 -1.8748826 0.65144095 -7.2748826 -2.648559 2
#> 6 1 -4.10 -2.55 3.0667117 -0.96996217 -1.0332883 -3.519962 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6920 -36375 6125
#> initial value 998.131940
#> iter 2 value 861.541055
#> iter 3 value 859.185717
#> iter 4 value 858.372102
#> iter 5 value 806.454631
#> iter 6 value 796.268691
#> iter 7 value 794.401164
#> iter 8 value 794.355664
#> iter 9 value 794.355567
#> iter 9 value 794.355560
#> iter 9 value 794.355560
#> final value 794.355560
#> converged
#> This is Run number 344
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.7481315 3.9447042 0.1981315 -9.255296 1
#> 2 1 -3.10 -5.40 4.1343684 0.2203945 1.0343684 -5.179606 1
#> 3 1 -14.60 -12.20 1.0995466 -0.7916516 -13.5004534 -12.991652 2
#> 4 1 -14.20 -0.55 1.5062887 2.0732973 -12.6937113 1.523297 2
#> 5 1 -5.40 -3.30 2.0736835 1.2483351 -3.3263165 -2.051665 2
#> 6 1 -4.10 -2.55 0.1650350 0.9455100 -3.9349650 -1.604490 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7140 -36700 4975
#> initial value 998.131940
#> iter 2 value 862.956548
#> iter 3 value 860.501850
#> iter 4 value 858.684685
#> iter 5 value 809.731413
#> iter 6 value 799.651774
#> iter 7 value 797.324421
#> iter 8 value 797.253722
#> iter 9 value 797.253453
#> iter 9 value 797.253446
#> iter 9 value 797.253446
#> final value 797.253446
#> converged
#> This is Run number 345
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.8483482 1.4056669 1.298348 -11.7943331 1
#> 2 1 -3.10 -5.40 -0.7017529 0.4537667 -3.801753 -4.9462333 1
#> 3 1 -14.60 -12.20 2.1008405 -0.2794852 -12.499160 -12.4794852 2
#> 4 1 -14.20 -0.55 0.4400984 -0.1488819 -13.759902 -0.6988819 2
#> 5 1 -5.40 -3.30 1.8471636 0.4465670 -3.552836 -2.8534330 2
#> 6 1 -4.10 -2.55 -0.6267707 -0.5182024 -4.726771 -3.0682024 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6360 -36625 6100
#> initial value 998.131940
#> iter 2 value 858.800511
#> iter 3 value 854.265904
#> iter 4 value 850.238674
#> iter 5 value 800.125492
#> iter 6 value 789.946990
#> iter 7 value 788.130225
#> iter 8 value 788.086831
#> iter 9 value 788.086772
#> iter 10 value 788.086756
#> iter 11 value 788.086723
#> iter 12 value 788.086697
#> iter 12 value 788.086697
#> iter 12 value 788.086697
#> final value 788.086697
#> converged
#> This is Run number 346
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.1268414 2.6699857 -0.6768414 -10.530014 1
#> 2 1 -3.10 -5.40 -0.9129302 0.1019073 -4.0129302 -5.298093 1
#> 3 1 -14.60 -12.20 2.8007915 -0.5240713 -11.7992085 -12.724071 1
#> 4 1 -14.20 -0.55 1.1652598 4.1467267 -13.0347402 3.596727 2
#> 5 1 -5.40 -3.30 -0.7647148 0.2333420 -6.1647148 -3.066658 2
#> 6 1 -4.10 -2.55 -0.2827098 1.1321729 -4.3827098 -1.417827 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6800 -35500 5750
#> initial value 998.131940
#> iter 2 value 874.517526
#> iter 3 value 873.171951
#> iter 4 value 872.319539
#> iter 5 value 818.521104
#> iter 6 value 808.851673
#> iter 7 value 806.844802
#> iter 8 value 806.794623
#> iter 9 value 806.794476
#> iter 10 value 806.794452
#> iter 11 value 806.794407
#> iter 12 value 806.794364
#> iter 12 value 806.794364
#> iter 12 value 806.794364
#> final value 806.794364
#> converged
#> This is Run number 347
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.07966505 1.0340553 -0.4703349 -12.165945 1
#> 2 1 -3.10 -5.40 0.24596058 0.9481243 -2.8540394 -4.451876 1
#> 3 1 -14.60 -12.20 -1.05707164 3.9435037 -15.6570716 -8.256496 2
#> 4 1 -14.20 -0.55 -0.33636937 -0.6591795 -14.5363694 -1.209180 2
#> 5 1 -5.40 -3.30 0.50275639 0.1545426 -4.8972436 -3.145457 2
#> 6 1 -4.10 -2.55 5.05992452 0.8976008 0.9599245 -1.652399 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6500 -34250 6000
#> initial value 998.131940
#> iter 2 value 887.911971
#> iter 3 value 887.849669
#> iter 4 value 887.307283
#> iter 5 value 829.816722
#> iter 6 value 820.783622
#> iter 7 value 818.920288
#> iter 8 value 818.879420
#> iter 9 value 818.879304
#> iter 10 value 818.879279
#> iter 11 value 818.879225
#> iter 12 value 818.879180
#> iter 12 value 818.879180
#> iter 12 value 818.879180
#> final value 818.879180
#> converged
#> This is Run number 348
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.1155899 1.5461079 0.5655899 -11.6538921 1
#> 2 1 -3.10 -5.40 0.3547130 -0.7116878 -2.7452870 -6.1116878 1
#> 3 1 -14.60 -12.20 -1.1648864 0.5369384 -15.7648864 -11.6630616 2
#> 4 1 -14.20 -0.55 1.9973436 1.3239339 -12.2026564 0.7739339 2
#> 5 1 -5.40 -3.30 0.5961842 0.0501009 -4.8038158 -3.2498991 2
#> 6 1 -4.10 -2.55 -0.1939945 0.4701786 -4.2939945 -2.0798214 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6420 -38175 6100
#> initial value 998.131940
#> iter 2 value 837.667834
#> iter 3 value 829.849849
#> iter 4 value 822.780107
#> iter 5 value 778.671889
#> iter 6 value 768.042070
#> iter 7 value 766.358792
#> iter 8 value 766.316439
#> iter 9 value 766.316422
#> iter 9 value 766.316413
#> iter 9 value 766.316406
#> final value 766.316406
#> converged
#> This is Run number 349
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.7029792 -0.0988008 1.152979 -13.2988008 1
#> 2 1 -3.10 -5.40 -0.1123530 1.6538453 -3.212353 -3.7461547 1
#> 3 1 -14.60 -12.20 0.1896419 1.0037815 -14.410358 -11.1962185 2
#> 4 1 -14.20 -0.55 -0.2192503 1.2866075 -14.419250 0.7366075 2
#> 5 1 -5.40 -3.30 1.2603471 0.5987349 -4.139653 -2.7012651 2
#> 6 1 -4.10 -2.55 0.4200912 1.5273118 -3.679909 -1.0226882 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6940 -36950 6100
#> initial value 998.131940
#> iter 2 value 854.190668
#> iter 3 value 850.984537
#> iter 4 value 849.667960
#> iter 5 value 799.608553
#> iter 6 value 789.183832
#> iter 7 value 787.346995
#> iter 8 value 787.301725
#> iter 9 value 787.301647
#> iter 9 value 787.301642
#> iter 9 value 787.301642
#> final value 787.301642
#> converged
#> This is Run number 350
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.5925671 -0.3569697 1.042567 -13.5569697 1
#> 2 1 -3.10 -5.40 -0.2509530 -0.1001341 -3.350953 -5.5001341 1
#> 3 1 -14.60 -12.20 2.5742240 1.5028503 -12.025776 -10.6971497 2
#> 4 1 -14.20 -0.55 1.5946475 0.3375163 -12.605352 -0.2124837 2
#> 5 1 -5.40 -3.30 -0.3300060 0.7734244 -5.730006 -2.5265756 2
#> 6 1 -4.10 -2.55 0.4122108 -0.4385951 -3.687789 -2.9885951 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7000 -37750 7300
#> initial value 998.131940
#> iter 2 value 836.054231
#> iter 3 value 830.970623
#> iter 4 value 830.447175
#> iter 5 value 780.989341
#> iter 6 value 770.357409
#> iter 7 value 768.803849
#> iter 8 value 768.776971
#> iter 9 value 768.776841
#> iter 10 value 768.776777
#> iter 11 value 768.776725
#> iter 11 value 768.776719
#> iter 11 value 768.776719
#> final value 768.776719
#> converged
#> This is Run number 351
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 4.7357772 -0.6093652 4.185777 -13.8093652 1
#> 2 1 -3.10 -5.40 0.4560364 0.5928229 -2.643964 -4.8071771 1
#> 3 1 -14.60 -12.20 2.6142595 0.3600993 -11.985740 -11.8399007 2
#> 4 1 -14.20 -0.55 -0.6158031 0.4438068 -14.815803 -0.1061932 2
#> 5 1 -5.40 -3.30 2.8403811 -0.3627608 -2.559619 -3.6627608 1
#> 6 1 -4.10 -2.55 -0.6131471 -0.8030670 -4.713147 -3.3530670 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6240 -33600 5850
#> initial value 998.131940
#> iter 2 value 895.917061
#> iter 3 value 884.643172
#> iter 4 value 883.984413
#> iter 5 value 835.508989
#> iter 6 value 827.863542
#> iter 7 value 826.173295
#> iter 8 value 826.133193
#> iter 9 value 826.132928
#> iter 10 value 826.132840
#> iter 11 value 826.132716
#> iter 12 value 826.132628
#> iter 12 value 826.132628
#> iter 12 value 826.132628
#> final value 826.132628
#> converged
#> This is Run number 352
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.6564722 1.6132702 0.1064722 -11.586730 1
#> 2 1 -3.10 -5.40 -0.2951973 0.2309208 -3.3951973 -5.169079 1
#> 3 1 -14.60 -12.20 0.2405241 0.8813364 -14.3594759 -11.318664 2
#> 4 1 -14.20 -0.55 1.3703930 -1.3122565 -12.8296070 -1.862257 2
#> 5 1 -5.40 -3.30 2.7699399 7.8872398 -2.6300601 4.587240 2
#> 6 1 -4.10 -2.55 2.4620000 -0.5411362 -1.6380000 -3.091136 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6800 -37475 6650
#> initial value 998.131940
#> iter 2 value 844.083484
#> iter 3 value 839.462896
#> iter 4 value 837.720874
#> iter 5 value 788.558092
#> iter 6 value 777.975617
#> iter 7 value 776.313692
#> iter 8 value 776.278347
#> iter 8 value 776.278345
#> final value 776.278345
#> converged
#> This is Run number 353
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.3487052 -0.3780692 -0.8987052 -13.578069 1
#> 2 1 -3.10 -5.40 -1.4592476 -0.1786644 -4.5592476 -5.578664 1
#> 3 1 -14.60 -12.20 1.7816391 -0.0113116 -12.8183609 -12.211312 2
#> 4 1 -14.20 -0.55 -0.6715584 1.6247415 -14.8715584 1.074742 2
#> 5 1 -5.40 -3.30 -0.4436832 1.1222299 -5.8436832 -2.177770 2
#> 6 1 -4.10 -2.55 -0.2669139 -0.4567685 -4.3669139 -3.006769 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6100 -34425 5575
#> initial value 998.131940
#> iter 2 value 888.314861
#> iter 3 value 886.673214
#> iter 4 value 883.738901
#> iter 5 value 828.120985
#> iter 6 value 819.123427
#> iter 7 value 817.180754
#> iter 8 value 817.137230
#> iter 9 value 817.137124
#> iter 10 value 817.137100
#> iter 11 value 817.137066
#> iter 12 value 817.137046
#> iter 12 value 817.137046
#> iter 12 value 817.137046
#> final value 817.137046
#> converged
#> This is Run number 354
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.0068591 -0.2577364 1.456859 -13.4577364 1
#> 2 1 -3.10 -5.40 -0.5597225 -0.5274556 -3.659723 -5.9274556 1
#> 3 1 -14.60 -12.20 0.4229382 -1.3983646 -14.177062 -13.5983646 2
#> 4 1 -14.20 -0.55 0.3209951 -0.2103262 -13.879005 -0.7603262 2
#> 5 1 -5.40 -3.30 0.8443052 0.6141424 -4.555695 -2.6858576 2
#> 6 1 -4.10 -2.55 2.7378523 -0.1122094 -1.362148 -2.6622094 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6140 -34100 6100
#> initial value 998.131940
#> iter 2 value 889.202909
#> iter 3 value 888.719209
#> iter 4 value 887.237924
#> iter 5 value 829.367255
#> iter 6 value 820.434416
#> iter 7 value 818.646496
#> iter 8 value 818.609543
#> iter 9 value 818.609456
#> iter 10 value 818.609425
#> iter 11 value 818.609371
#> iter 12 value 818.609342
#> iter 12 value 818.609342
#> iter 12 value 818.609342
#> final value 818.609342
#> converged
#> This is Run number 355
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.9068675 -0.16353509 0.3568675 -13.3635351 1
#> 2 1 -3.10 -5.40 1.5485945 -0.05504465 -1.5514055 -5.4550447 1
#> 3 1 -14.60 -12.20 -0.4292956 0.87337201 -15.0292956 -11.3266280 2
#> 4 1 -14.20 -0.55 -0.3012264 1.49658416 -14.5012264 0.9465842 2
#> 5 1 -5.40 -3.30 0.5244595 0.01939414 -4.8755405 -3.2806059 2
#> 6 1 -4.10 -2.55 2.3365857 -0.84324948 -1.7634143 -3.3932495 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6560 -36450 5950
#> initial value 998.131940
#> iter 2 value 861.788052
#> iter 3 value 858.303730
#> iter 4 value 855.539653
#> iter 5 value 804.681229
#> iter 6 value 794.552357
#> iter 7 value 792.668111
#> iter 8 value 792.621602
#> iter 9 value 792.621515
#> iter 10 value 792.621494
#> iter 11 value 792.621457
#> iter 12 value 792.621428
#> iter 12 value 792.621428
#> iter 12 value 792.621428
#> final value 792.621428
#> converged
#> This is Run number 356
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.3721821 -1.39813468 -0.1778179 -14.598135 1
#> 2 1 -3.10 -5.40 1.3791780 0.68997495 -1.7208220 -4.710025 1
#> 3 1 -14.60 -12.20 0.4846243 2.01472330 -14.1153757 -10.185277 2
#> 4 1 -14.20 -0.55 -1.0064552 0.06382003 -15.2064552 -0.486180 2
#> 5 1 -5.40 -3.30 3.4175654 -0.69804739 -1.9824346 -3.998047 1
#> 6 1 -4.10 -2.55 -0.7669203 -0.48198514 -4.8669203 -3.031985 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7300 -38400 6125
#> initial value 998.131940
#> iter 2 value 833.685157
#> iter 3 value 829.003390
#> iter 4 value 827.608937
#> iter 5 value 782.081259
#> iter 6 value 771.135820
#> iter 7 value 769.441735
#> iter 8 value 769.400694
#> iter 9 value 769.400646
#> iter 10 value 769.400616
#> iter 11 value 769.400596
#> iter 12 value 769.400548
#> iter 12 value 769.400548
#> iter 12 value 769.400548
#> final value 769.400548
#> converged
#> This is Run number 357
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.59417822 2.2579210 0.04417822 -10.9420790 1
#> 2 1 -3.10 -5.40 1.50804659 0.9298502 -1.59195341 -4.4701498 1
#> 3 1 -14.60 -12.20 -0.04171116 6.7183823 -14.64171116 -5.4816177 2
#> 4 1 -14.20 -0.55 -0.75281914 -0.2352762 -14.95281914 -0.7852762 2
#> 5 1 -5.40 -3.30 -0.11263101 -1.0312995 -5.51263101 -4.3312995 2
#> 6 1 -4.10 -2.55 0.60391149 0.7774452 -3.49608851 -1.7725548 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6280 -35425 6825
#> initial value 998.131940
#> iter 2 value 869.687396
#> iter 3 value 867.538538
#> iter 4 value 866.135847
#> iter 5 value 810.442041
#> iter 6 value 800.716522
#> iter 7 value 799.024210
#> iter 8 value 798.990871
#> iter 9 value 798.990820
#> iter 10 value 798.990792
#> iter 11 value 798.990738
#> iter 12 value 798.990703
#> iter 12 value 798.990703
#> iter 12 value 798.990703
#> final value 798.990703
#> converged
#> This is Run number 358
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.102055959 1.06050025 -0.652056 -12.1394997 1
#> 2 1 -3.10 -5.40 0.002257989 -0.53829562 -3.097742 -5.9382956 1
#> 3 1 -14.60 -12.20 1.190130450 1.29024981 -13.409870 -10.9097502 2
#> 4 1 -14.20 -0.55 1.228287141 0.02338714 -12.971713 -0.5266129 2
#> 5 1 -5.40 -3.30 -0.012954657 1.55317728 -5.412955 -1.7468227 2
#> 6 1 -4.10 -2.55 0.297812149 -1.19067602 -3.802188 -3.7406760 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7120 -38200 7750
#> initial value 998.131940
#> iter 2 value 826.564945
#> iter 3 value 820.308028
#> iter 4 value 820.091458
#> iter 5 value 771.477496
#> iter 6 value 760.893610
#> iter 7 value 759.393242
#> iter 8 value 759.370160
#> iter 9 value 759.369861
#> iter 10 value 759.369800
#> iter 11 value 759.369785
#> iter 12 value 759.369746
#> iter 12 value 759.369746
#> iter 12 value 759.369746
#> final value 759.369746
#> converged
#> This is Run number 359
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.361376074 0.81718045 0.8113761 -12.382819551 1
#> 2 1 -3.10 -5.40 -0.692678626 -0.69777938 -3.7926786 -6.097779377 1
#> 3 1 -14.60 -12.20 -0.446571428 0.47055002 -15.0465714 -11.729449980 2
#> 4 1 -14.20 -0.55 0.007104863 0.55266287 -14.1928951 0.002662869 2
#> 5 1 -5.40 -3.30 0.378809551 0.69400274 -5.0211904 -2.605997260 2
#> 6 1 -4.10 -2.55 -0.384882529 -0.02863621 -4.4848825 -2.578636208 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6220 -35800 5400
#> initial value 998.131940
#> iter 2 value 872.909893
#> iter 3 value 868.910826
#> iter 4 value 863.842292
#> iter 5 value 813.007836
#> iter 6 value 803.322332
#> iter 7 value 801.260313
#> iter 8 value 801.206638
#> iter 9 value 801.206497
#> iter 9 value 801.206491
#> iter 9 value 801.206491
#> final value 801.206491
#> converged
#> This is Run number 360
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.06129973 -0.02704335 -0.6112997 -13.2270433 1
#> 2 1 -3.10 -5.40 -0.00527531 3.31397336 -3.1052753 -2.0860266 2
#> 3 1 -14.60 -12.20 -0.23005017 0.50591375 -14.8300502 -11.6940863 2
#> 4 1 -14.20 -0.55 0.07396399 -0.56464816 -14.1260360 -1.1146482 2
#> 5 1 -5.40 -3.30 -1.13464272 3.19145133 -6.5346427 -0.1085487 2
#> 6 1 -4.10 -2.55 -0.21706630 3.32225109 -4.3170663 0.7722511 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6520 -37775 6450
#> initial value 998.131940
#> iter 2 value 841.287606
#> iter 3 value 835.035157
#> iter 4 value 830.723024
#> iter 5 value 783.682128
#> iter 6 value 773.105610
#> iter 7 value 771.442773
#> iter 8 value 771.405148
#> iter 8 value 771.405143
#> final value 771.405143
#> converged
#> This is Run number 361
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.21964606 -1.4139900 -0.3303539 -14.613990 1
#> 2 1 -3.10 -5.40 -0.04649336 -0.7049580 -3.1464934 -6.104958 1
#> 3 1 -14.60 -12.20 1.51790921 -0.7929801 -13.0820908 -12.992980 2
#> 4 1 -14.20 -0.55 0.90580090 1.7815181 -13.2941991 1.231518 2
#> 5 1 -5.40 -3.30 0.09964957 -0.8592025 -5.3003504 -4.159203 2
#> 6 1 -4.10 -2.55 1.33973480 -0.4142311 -2.7602652 -2.964231 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7020 -36350 5750
#> initial value 998.131940
#> iter 2 value 863.781644
#> iter 3 value 861.678897
#> iter 4 value 860.808197
#> iter 5 value 809.399817
#> iter 6 value 799.282920
#> iter 7 value 797.280242
#> iter 8 value 797.227473
#> iter 9 value 797.227328
#> iter 10 value 797.227309
#> iter 11 value 797.227268
#> iter 12 value 797.227223
#> iter 12 value 797.227223
#> iter 12 value 797.227223
#> final value 797.227223
#> converged
#> This is Run number 362
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.5696725 -0.1423596 0.01967252 -13.3423596 1
#> 2 1 -3.10 -5.40 5.2902971 1.2575433 2.19029705 -4.1424567 1
#> 3 1 -14.60 -12.20 0.5261466 0.5170688 -14.07385342 -11.6829312 2
#> 4 1 -14.20 -0.55 -0.5775133 0.9986807 -14.77751333 0.4486807 2
#> 5 1 -5.40 -3.30 0.7100522 -1.3775940 -4.68994775 -4.6775940 2
#> 6 1 -4.10 -2.55 1.3183086 2.0202015 -2.78169142 -0.5297985 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6100 -36100 6025
#> initial value 998.131940
#> iter 2 value 865.985802
#> iter 3 value 861.388810
#> iter 4 value 856.336566
#> iter 5 value 805.236968
#> iter 6 value 795.329397
#> iter 7 value 793.487860
#> iter 8 value 793.444439
#> iter 9 value 793.444372
#> iter 10 value 793.444356
#> iter 11 value 793.444331
#> iter 12 value 793.444311
#> iter 12 value 793.444311
#> iter 12 value 793.444311
#> final value 793.444311
#> converged
#> This is Run number 363
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.9841202 -0.5914546 1.434120 -13.7914546 1
#> 2 1 -3.10 -5.40 -0.8890539 2.2907894 -3.989054 -3.1092106 2
#> 3 1 -14.60 -12.20 -0.6184924 2.4931550 -15.218492 -9.7068450 2
#> 4 1 -14.20 -0.55 -0.7904921 1.0970654 -14.990492 0.5470654 2
#> 5 1 -5.40 -3.30 0.9831671 -0.8651421 -4.416833 -4.1651421 2
#> 6 1 -4.10 -2.55 1.0922103 -0.2549639 -3.007790 -2.8049639 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7140 -35325 5325
#> initial value 998.131940
#> iter 2 value 878.421475
#> iter 3 value 877.730134
#> iter 4 value 877.474827
#> iter 5 value 823.784825
#> iter 6 value 814.328736
#> iter 7 value 812.111988
#> iter 8 value 812.052741
#> iter 9 value 812.052515
#> iter 10 value 812.052497
#> iter 11 value 812.052456
#> iter 12 value 812.052403
#> iter 12 value 812.052403
#> iter 12 value 812.052403
#> final value 812.052403
#> converged
#> This is Run number 364
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.6093994 1.57381011 0.05939938 -11.6261899 1
#> 2 1 -3.10 -5.40 1.1584261 -0.24034911 -1.94157391 -5.6403491 1
#> 3 1 -14.60 -12.20 1.7796183 0.04261426 -12.82038168 -12.1573857 2
#> 4 1 -14.20 -0.55 0.9852640 -0.27717865 -13.21473605 -0.8271787 2
#> 5 1 -5.40 -3.30 0.4048628 2.14943596 -4.99513715 -1.1505640 2
#> 6 1 -4.10 -2.55 -1.7274464 0.95476095 -5.82744643 -1.5952391 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6840 -37625 6125
#> initial value 998.131940
#> iter 2 value 845.021076
#> iter 3 value 840.320996
#> iter 4 value 837.668044
#> iter 5 value 790.059118
#> iter 6 value 779.425585
#> iter 7 value 777.664621
#> iter 8 value 777.621654
#> iter 9 value 777.621612
#> iter 10 value 777.621591
#> iter 11 value 777.621551
#> iter 12 value 777.621521
#> iter 12 value 777.621521
#> iter 12 value 777.621521
#> final value 777.621521
#> converged
#> This is Run number 365
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.33970913 -1.9514608 -0.8897091 -15.151461 1
#> 2 1 -3.10 -5.40 0.64169571 -0.1077322 -2.4583043 -5.507732 1
#> 3 1 -14.60 -12.20 -1.45740193 2.0090476 -16.0574019 -10.190952 2
#> 4 1 -14.20 -0.55 -0.03527376 1.8745211 -14.2352738 1.324521 2
#> 5 1 -5.40 -3.30 2.96379126 0.6926719 -2.4362087 -2.607328 1
#> 6 1 -4.10 -2.55 3.28880005 0.1669183 -0.8111999 -2.383082 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7300 -37025 5275
#> initial value 998.131940
#> iter 2 value 857.107144
#> iter 3 value 854.661940
#> iter 4 value 853.578040
#> iter 5 value 804.903660
#> iter 6 value 794.560660
#> iter 7 value 792.385891
#> iter 8 value 792.321229
#> iter 9 value 792.321011
#> iter 10 value 792.320998
#> iter 11 value 792.320972
#> iter 12 value 792.320933
#> iter 12 value 792.320933
#> iter 12 value 792.320933
#> final value 792.320933
#> converged
#> This is Run number 366
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 4.5994536 0.2317935 4.049454 -12.9682065 1
#> 2 1 -3.10 -5.40 1.0648082 0.7830543 -2.035192 -4.6169457 1
#> 3 1 -14.60 -12.20 1.8206327 1.5031083 -12.779367 -10.6968917 2
#> 4 1 -14.20 -0.55 -0.6988336 -0.3872181 -14.898834 -0.9372181 2
#> 5 1 -5.40 -3.30 -0.6884480 0.2801375 -6.088448 -3.0198625 2
#> 6 1 -4.10 -2.55 0.4071055 -0.3185551 -3.692895 -2.8685551 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7820 -38025 4950
#> initial value 998.131940
#> iter 2 value 844.301020
#> iter 3 value 841.688569
#> iter 4 value 841.053587
#> iter 5 value 795.770360
#> iter 6 value 785.041942
#> iter 7 value 782.783263
#> iter 8 value 782.708101
#> iter 9 value 782.707809
#> iter 9 value 782.707805
#> iter 9 value 782.707805
#> final value 782.707805
#> converged
#> This is Run number 367
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 4.8798860 0.34970325 4.3298860 -12.850297 1
#> 2 1 -3.10 -5.40 2.2268228 -1.15427674 -0.8731772 -6.554277 1
#> 3 1 -14.60 -12.20 0.3365616 0.03761497 -14.2634384 -12.162385 2
#> 4 1 -14.20 -0.55 1.1201358 1.42342802 -13.0798642 0.873428 2
#> 5 1 -5.40 -3.30 3.7567178 -0.64069928 -1.6432822 -3.940699 1
#> 6 1 -4.10 -2.55 0.4806919 1.05618230 -3.6193081 -1.493818 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7480 -37225 5625
#> initial value 998.131940
#> iter 2 value 852.468365
#> iter 3 value 850.029105
#> iter 4 value 849.659616
#> iter 5 value 800.956038
#> iter 6 value 790.420237
#> iter 7 value 788.402302
#> iter 8 value 788.345090
#> iter 9 value 788.344929
#> iter 9 value 788.344919
#> iter 9 value 788.344919
#> final value 788.344919
#> converged
#> This is Run number 368
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.3485120 1.78368835 1.798512 -11.4163116 1
#> 2 1 -3.10 -5.40 1.0053941 0.03980291 -2.094606 -5.3601971 1
#> 3 1 -14.60 -12.20 1.3760258 2.38309451 -13.223974 -9.8169055 2
#> 4 1 -14.20 -0.55 1.1961354 0.28234741 -13.003865 -0.2676526 2
#> 5 1 -5.40 -3.30 0.7803861 0.38910651 -4.619614 -2.9108935 2
#> 6 1 -4.10 -2.55 1.0921639 -1.40317233 -3.007836 -3.9531723 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6760 -36800 5475
#> initial value 998.131940
#> iter 2 value 859.581648
#> iter 3 value 855.956626
#> iter 4 value 852.862454
#> iter 5 value 803.920882
#> iter 6 value 793.691341
#> iter 7 value 791.649425
#> iter 8 value 791.592943
#> iter 9 value 791.592799
#> iter 10 value 791.592784
#> iter 11 value 791.592761
#> iter 12 value 791.592736
#> iter 12 value 791.592736
#> iter 12 value 791.592736
#> final value 791.592736
#> converged
#> This is Run number 369
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.1555607 0.38254696 -0.7055607 -12.817453 1
#> 2 1 -3.10 -5.40 0.4966237 -0.91855979 -2.6033763 -6.318560 1
#> 3 1 -14.60 -12.20 0.6564322 0.03175973 -13.9435678 -12.168240 2
#> 4 1 -14.20 -0.55 -0.7493219 -0.07781498 -14.9493219 -0.627815 2
#> 5 1 -5.40 -3.30 0.9675763 -0.17084859 -4.4324237 -3.470849 2
#> 6 1 -4.10 -2.55 -1.5882530 1.02273340 -5.6882530 -1.527267 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6500 -36400 5850
#> initial value 998.131940
#> iter 2 value 862.990505
#> iter 3 value 859.337388
#> iter 4 value 856.095229
#> iter 5 value 805.432658
#> iter 6 value 795.350171
#> iter 7 value 793.438365
#> iter 8 value 793.390465
#> iter 9 value 793.390371
#> iter 10 value 793.390351
#> iter 11 value 793.390319
#> iter 12 value 793.390294
#> iter 12 value 793.390294
#> iter 12 value 793.390294
#> final value 793.390294
#> converged
#> This is Run number 370
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.21172576 1.6518344 -0.7617258 -11.548166 1
#> 2 1 -3.10 -5.40 2.38969603 2.2480174 -0.7103040 -3.151983 1
#> 3 1 -14.60 -12.20 -0.60369399 0.2516953 -15.2036940 -11.948305 2
#> 4 1 -14.20 -0.55 0.54379298 2.0987438 -13.6562070 1.548744 2
#> 5 1 -5.40 -3.30 0.05276855 0.3163992 -5.3472315 -2.983601 2
#> 6 1 -4.10 -2.55 0.39276349 -1.2509865 -3.7072365 -3.800987 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6160 -36650 7150
#> initial value 998.131940
#> iter 2 value 852.322478
#> iter 3 value 847.240419
#> iter 4 value 844.091983
#> iter 5 value 791.981406
#> iter 6 value 781.832590
#> iter 7 value 780.209722
#> iter 8 value 780.179083
#> iter 9 value 780.179047
#> iter 10 value 780.179028
#> iter 11 value 780.178981
#> iter 12 value 780.178949
#> iter 12 value 780.178949
#> iter 12 value 780.178949
#> final value 780.178949
#> converged
#> This is Run number 371
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.8194047 0.94696431 0.2694047 -12.2530357 1
#> 2 1 -3.10 -5.40 6.6306883 0.25167073 3.5306883 -5.1483293 1
#> 3 1 -14.60 -12.20 0.4956553 1.86008391 -14.1043447 -10.3399161 2
#> 4 1 -14.20 -0.55 -0.6707791 0.09890618 -14.8707791 -0.4510938 2
#> 5 1 -5.40 -3.30 -0.5787289 -0.10847633 -5.9787289 -3.4084763 2
#> 6 1 -4.10 -2.55 0.3685645 0.77202972 -3.7314355 -1.7779703 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7260 -37725 6650
#> initial value 998.131940
#> iter 2 value 840.209503
#> iter 3 value 836.175063
#> iter 4 value 835.785948
#> iter 5 value 787.189670
#> iter 6 value 776.426694
#> iter 7 value 774.783764
#> iter 8 value 774.749292
#> iter 9 value 774.749239
#> iter 10 value 774.749210
#> iter 11 value 774.749152
#> iter 12 value 774.749111
#> iter 12 value 774.749111
#> iter 12 value 774.749111
#> final value 774.749111
#> converged
#> This is Run number 372
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.67590023 0.2924278 2.125900 -12.9075722 1
#> 2 1 -3.10 -5.40 1.91449773 3.0404622 -1.185502 -2.3595378 1
#> 3 1 -14.60 -12.20 3.43680445 -0.1903183 -11.163196 -12.3903183 1
#> 4 1 -14.20 -0.55 0.93465343 -0.1120168 -13.265347 -0.6620168 2
#> 5 1 -5.40 -3.30 -0.76060569 2.1569509 -6.160606 -1.1430491 2
#> 6 1 -4.10 -2.55 0.07346083 0.9604533 -4.026539 -1.5895467 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6060 -35850 7300
#> initial value 998.131940
#> iter 2 value 861.572426
#> iter 3 value 857.991491
#> iter 4 value 855.746648
#> iter 5 value 800.666848
#> iter 6 value 790.808577
#> iter 7 value 789.186710
#> iter 8 value 789.157868
#> iter 9 value 789.157832
#> iter 10 value 789.157809
#> iter 11 value 789.157760
#> iter 12 value 789.157729
#> iter 12 value 789.157729
#> iter 12 value 789.157729
#> final value 789.157729
#> converged
#> This is Run number 373
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.7763274 -0.7855703 0.2263274 -13.9855703 1
#> 2 1 -3.10 -5.40 3.3700005 -0.9081530 0.2700005 -6.3081530 1
#> 3 1 -14.60 -12.20 2.9911348 -1.3246932 -11.6088652 -13.5246932 1
#> 4 1 -14.20 -0.55 0.1058017 -0.8986712 -14.0941983 -1.4486712 2
#> 5 1 -5.40 -3.30 0.9934824 -1.1611003 -4.4065176 -4.4611003 1
#> 6 1 -4.10 -2.55 -0.4212217 3.0053261 -4.5212217 0.4553261 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6780 -35700 5800
#> initial value 998.131940
#> iter 2 value 871.842255
#> iter 3 value 870.181808
#> iter 4 value 869.140996
#> iter 5 value 815.851488
#> iter 6 value 806.069743
#> iter 7 value 804.085383
#> iter 8 value 804.035741
#> iter 9 value 804.035604
#> iter 10 value 804.035580
#> iter 11 value 804.035535
#> iter 12 value 804.035494
#> iter 12 value 804.035494
#> iter 12 value 804.035494
#> final value 804.035494
#> converged
#> This is Run number 374
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.04131067 1.0717210 -0.5086893 -12.1282790 1
#> 2 1 -3.10 -5.40 1.49557633 -0.4311967 -1.6044237 -5.8311967 1
#> 3 1 -14.60 -12.20 0.83695134 -1.6681346 -13.7630487 -13.8681346 1
#> 4 1 -14.20 -0.55 0.70174826 1.3105491 -13.4982517 0.7605491 2
#> 5 1 -5.40 -3.30 -0.85419698 1.3496188 -6.2541970 -1.9503812 2
#> 6 1 -4.10 -2.55 0.85611569 1.5364953 -3.2438843 -1.0135047 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7260 -37450 5825
#> initial value 998.131940
#> iter 2 value 848.654754
#> iter 3 value 845.466833
#> iter 4 value 844.503627
#> iter 5 value 796.298136
#> iter 6 value 785.658797
#> iter 7 value 783.760973
#> iter 8 value 783.710214
#> iter 9 value 783.710113
#> iter 9 value 783.710102
#> iter 9 value 783.710102
#> final value 783.710102
#> converged
#> This is Run number 375
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.51141240 -0.02319859 -1.061412 -13.2231986 1
#> 2 1 -3.10 -5.40 0.12820851 -1.15178452 -2.971791 -6.5517845 1
#> 3 1 -14.60 -12.20 -0.06290801 1.66005661 -14.662908 -10.5399434 2
#> 4 1 -14.20 -0.55 0.97296955 0.10896857 -13.227030 -0.4410314 2
#> 5 1 -5.40 -3.30 -0.06765655 -0.28512771 -5.467657 -3.5851277 2
#> 6 1 -4.10 -2.55 2.15475931 -0.89532243 -1.945241 -3.4453224 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6820 -36450 7250
#> initial value 998.131940
#> iter 2 value 853.919032
#> iter 3 value 850.839789
#> iter 4 value 850.604033
#> iter 5 value 797.151495
#> iter 6 value 786.885441
#> iter 7 value 785.279965
#> iter 8 value 785.251514
#> iter 9 value 785.251458
#> iter 10 value 785.251430
#> iter 11 value 785.251381
#> iter 12 value 785.251346
#> iter 12 value 785.251346
#> iter 12 value 785.251346
#> final value 785.251346
#> converged
#> This is Run number 376
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.8423649 -0.08341085 0.2923649 -13.2834109 1
#> 2 1 -3.10 -5.40 -0.4554585 2.70875687 -3.5554585 -2.6912431 2
#> 3 1 -14.60 -12.20 1.9208162 1.24184447 -12.6791838 -10.9581555 2
#> 4 1 -14.20 -0.55 -0.1727329 0.92980384 -14.3727329 0.3798038 2
#> 5 1 -5.40 -3.30 -0.5425783 1.20129073 -5.9425783 -2.0987093 2
#> 6 1 -4.10 -2.55 -1.4287840 1.30847199 -5.5287840 -1.2415280 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7540 -38300 5350
#> initial value 998.131940
#> iter 2 value 838.903108
#> iter 3 value 835.246568
#> iter 4 value 833.853932
#> iter 5 value 789.103128
#> iter 6 value 778.191859
#> iter 7 value 776.215553
#> iter 8 value 776.156018
#> iter 9 value 776.155882
#> iter 9 value 776.155870
#> iter 9 value 776.155870
#> final value 776.155870
#> converged
#> This is Run number 377
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.6398955 1.0063367 0.08989546 -12.193663 1
#> 2 1 -3.10 -5.40 0.6739877 3.4796861 -2.42601229 -1.920314 2
#> 3 1 -14.60 -12.20 0.4839745 1.5279169 -14.11602548 -10.672083 2
#> 4 1 -14.20 -0.55 -0.3188919 4.2593160 -14.51889194 3.709316 2
#> 5 1 -5.40 -3.30 0.2822392 0.1005376 -5.11776081 -3.199462 2
#> 6 1 -4.10 -2.55 2.2102199 -0.4763352 -1.88978014 -3.026335 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6820 -37025 6700
#> initial value 998.131940
#> iter 2 value 849.835330
#> iter 3 value 846.074742
#> iter 4 value 844.978984
#> iter 5 value 794.184743
#> iter 6 value 783.725042
#> iter 7 value 782.042253
#> iter 8 value 782.006859
#> iter 9 value 782.006801
#> iter 10 value 782.006759
#> iter 11 value 782.006730
#> iter 12 value 782.006695
#> iter 12 value 782.006695
#> iter 12 value 782.006695
#> final value 782.006695
#> converged
#> This is Run number 378
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -1.2640406 1.22488463 -1.814041 -11.9751154 1
#> 2 1 -3.10 -5.40 0.3439653 0.63605551 -2.756035 -4.7639445 1
#> 3 1 -14.60 -12.20 -1.5681418 0.21434403 -16.168142 -11.9856560 2
#> 4 1 -14.20 -0.55 -0.6632564 -0.31363370 -14.863256 -0.8636337 2
#> 5 1 -5.40 -3.30 0.1927014 -0.04378289 -5.207299 -3.3437829 2
#> 6 1 -4.10 -2.55 -0.2305085 2.35313760 -4.330509 -0.1968624 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6340 -37175 6900
#> initial value 998.131940
#> iter 2 value 846.879241
#> iter 3 value 841.271938
#> iter 4 value 837.864044
#> iter 5 value 787.886447
#> iter 6 value 777.528535
#> iter 7 value 775.896096
#> iter 8 value 775.863168
#> iter 9 value 775.863133
#> iter 10 value 775.863112
#> iter 11 value 775.863066
#> iter 12 value 775.863036
#> iter 12 value 775.863036
#> iter 12 value 775.863036
#> final value 775.863036
#> converged
#> This is Run number 379
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.6482673 -0.4418714 1.098267 -13.641871 1
#> 2 1 -3.10 -5.40 0.6418091 -0.8982420 -2.458191 -6.298242 1
#> 3 1 -14.60 -12.20 1.2104646 -1.1635889 -13.389535 -13.363589 2
#> 4 1 -14.20 -0.55 -0.9895729 3.7527684 -15.189573 3.202768 2
#> 5 1 -5.40 -3.30 -0.5661864 -0.3103772 -5.966186 -3.610377 2
#> 6 1 -4.10 -2.55 0.2286540 0.3571501 -3.871346 -2.192850 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7400 -37550 5275
#> initial value 998.131940
#> iter 2 value 849.923792
#> iter 3 value 846.993149
#> iter 4 value 845.750998
#> iter 5 value 798.712956
#> iter 6 value 788.124251
#> iter 7 value 786.005293
#> iter 8 value 785.941052
#> iter 9 value 785.940853
#> iter 10 value 785.940841
#> iter 11 value 785.940818
#> iter 12 value 785.940782
#> iter 12 value 785.940782
#> iter 12 value 785.940782
#> final value 785.940782
#> converged
#> This is Run number 380
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.5913419 0.8591500 0.04134187 -12.340850 1
#> 2 1 -3.10 -5.40 0.5663890 3.6410982 -2.53361096 -1.758902 2
#> 3 1 -14.60 -12.20 0.4704529 0.4076591 -14.12954705 -11.792341 2
#> 4 1 -14.20 -0.55 0.8549917 2.0658797 -13.34500832 1.515880 2
#> 5 1 -5.40 -3.30 2.3817379 -0.5722615 -3.01826214 -3.872262 1
#> 6 1 -4.10 -2.55 -0.8420066 0.8012722 -4.94200657 -1.748728 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6500 -37375 6975
#> initial value 998.131940
#> iter 2 value 843.643601
#> iter 3 value 838.180128
#> iter 4 value 835.569497
#> iter 5 value 785.840938
#> iter 6 value 775.392088
#> iter 7 value 773.776304
#> iter 8 value 773.744396
#> iter 9 value 773.744348
#> iter 10 value 773.744304
#> iter 11 value 773.744254
#> iter 12 value 773.744242
#> iter 12 value 773.744242
#> iter 12 value 773.744242
#> final value 773.744242
#> converged
#> This is Run number 381
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.4064340 0.5553603 1.856434 -12.64463975 1
#> 2 1 -3.10 -5.40 -0.5543782 -0.2414972 -3.654378 -5.64149722 1
#> 3 1 -14.60 -12.20 -0.4472946 1.0161194 -15.047295 -11.18388064 2
#> 4 1 -14.20 -0.55 -1.0409524 0.5101768 -15.240952 -0.03982320 2
#> 5 1 -5.40 -3.30 -0.8885856 0.1085566 -6.288586 -3.19144345 2
#> 6 1 -4.10 -2.55 0.1570972 2.6090115 -3.942903 0.05901152 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6740 -37975 6125
#> initial value 998.131940
#> iter 2 value 840.216218
#> iter 3 value 834.428423
#> iter 4 value 830.524080
#> iter 5 value 784.471355
#> iter 6 value 773.775574
#> iter 7 value 772.057761
#> iter 8 value 772.015782
#> iter 9 value 772.015766
#> iter 10 value 772.015754
#> iter 11 value 772.015717
#> iter 12 value 772.015679
#> iter 12 value 772.015679
#> iter 12 value 772.015679
#> final value 772.015679
#> converged
#> This is Run number 382
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -1.04153905 0.6770564 -1.5915391 -12.522944 1
#> 2 1 -3.10 -5.40 2.31438670 -0.1314758 -0.7856133 -5.531476 1
#> 3 1 -14.60 -12.20 -0.42294321 0.5442649 -15.0229432 -11.655735 2
#> 4 1 -14.20 -0.55 -0.33988791 1.6903700 -14.5398879 1.140370 2
#> 5 1 -5.40 -3.30 -0.01752929 0.9388331 -5.4175293 -2.361167 2
#> 6 1 -4.10 -2.55 0.18171791 3.7016463 -3.9182821 1.151646 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7120 -38425 6175
#> initial value 998.131940
#> iter 2 value 833.232303
#> iter 3 value 827.960398
#> iter 4 value 825.754147
#> iter 5 value 780.470378
#> iter 6 value 769.572754
#> iter 7 value 767.899190
#> iter 8 value 767.859177
#> iter 8 value 767.859167
#> final value 767.859167
#> converged
#> This is Run number 383
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.7427350 0.56399015 1.192735 -12.636010 1
#> 2 1 -3.10 -5.40 1.9155275 1.03323422 -1.184473 -4.366766 1
#> 3 1 -14.60 -12.20 -1.0557249 -0.07745315 -15.655725 -12.277453 2
#> 4 1 -14.20 -0.55 0.6046827 7.37232381 -13.595317 6.822324 2
#> 5 1 -5.40 -3.30 -0.7274459 0.17800397 -6.127446 -3.121996 2
#> 6 1 -4.10 -2.55 -0.6949834 0.13773659 -4.794983 -2.412263 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7740 -39350 4425
#> initial value 998.131940
#> iter 2 value 827.424203
#> iter 3 value 822.708202
#> iter 4 value 818.976846
#> iter 5 value 779.798415
#> iter 6 value 768.776887
#> iter 7 value 766.577718
#> iter 8 value 766.495143
#> iter 9 value 766.494796
#> iter 9 value 766.494788
#> iter 9 value 766.494783
#> final value 766.494783
#> converged
#> This is Run number 384
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.8115721 1.1004025 0.2615721 -12.099598 1
#> 2 1 -3.10 -5.40 0.8256616 -1.3238528 -2.2743384 -6.723853 1
#> 3 1 -14.60 -12.20 0.8726621 0.7724812 -13.7273379 -11.427519 2
#> 4 1 -14.20 -0.55 2.0507235 -1.3486172 -12.1492765 -1.898617 2
#> 5 1 -5.40 -3.30 1.1133976 2.5937190 -4.2866024 -0.706281 2
#> 6 1 -4.10 -2.55 3.6308088 1.1881128 -0.4691912 -1.361887 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6880 -36300 5325
#> initial value 998.131940
#> iter 2 value 866.679681
#> iter 3 value 864.218248
#> iter 4 value 862.254243
#> iter 5 value 811.673300
#> iter 6 value 801.701079
#> iter 7 value 799.547435
#> iter 8 value 799.487480
#> iter 9 value 799.487292
#> iter 10 value 799.487275
#> iter 11 value 799.487248
#> iter 12 value 799.487216
#> iter 12 value 799.487216
#> iter 12 value 799.487216
#> final value 799.487216
#> converged
#> This is Run number 385
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.60850788 1.57661064 1.058508 -11.6233894 1
#> 2 1 -3.10 -5.40 0.08698909 0.72350881 -3.013011 -4.6764912 1
#> 3 1 -14.60 -12.20 -0.47789314 0.03796487 -15.077893 -12.1620351 2
#> 4 1 -14.20 -0.55 0.64111377 -0.32523293 -13.558886 -0.8752329 2
#> 5 1 -5.40 -3.30 -1.13894988 0.49421141 -6.538950 -2.8057886 2
#> 6 1 -4.10 -2.55 2.22847781 -0.99244022 -1.871522 -3.5424402 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6820 -37475 5600
#> initial value 998.131940
#> iter 2 value 849.883778
#> iter 3 value 845.289012
#> iter 4 value 841.658193
#> iter 5 value 794.761464
#> iter 6 value 784.229511
#> iter 7 value 782.297142
#> iter 8 value 782.243806
#> iter 9 value 782.243704
#> iter 10 value 782.243691
#> iter 11 value 782.243669
#> iter 12 value 782.243647
#> iter 12 value 782.243647
#> iter 12 value 782.243647
#> final value 782.243647
#> converged
#> This is Run number 386
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.02579991 -0.7087983 -0.5757999 -13.9087983 1
#> 2 1 -3.10 -5.40 0.66662677 2.4421075 -2.4333732 -2.9578925 1
#> 3 1 -14.60 -12.20 0.24822450 -0.5104779 -14.3517755 -12.7104779 2
#> 4 1 -14.20 -0.55 5.43179944 1.0732607 -8.7682006 0.5232607 2
#> 5 1 -5.40 -3.30 1.80192769 2.3543845 -3.5980723 -0.9456155 2
#> 6 1 -4.10 -2.55 -1.07181723 -0.1049788 -5.1718172 -2.6549788 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6340 -36575 6175
#> initial value 998.131940
#> iter 2 value 859.043298
#> iter 3 value 854.570130
#> iter 4 value 850.670792
#> iter 5 value 800.233942
#> iter 6 value 790.072779
#> iter 7 value 788.273557
#> iter 8 value 788.231364
#> iter 9 value 788.231310
#> iter 10 value 788.231295
#> iter 11 value 788.231260
#> iter 12 value 788.231230
#> iter 12 value 788.231230
#> iter 12 value 788.231230
#> final value 788.231230
#> converged
#> This is Run number 387
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.5937007 1.0553617 -1.143701 -12.144638 1
#> 2 1 -3.10 -5.40 0.1414100 -0.3178081 -2.958590 -5.717808 1
#> 3 1 -14.60 -12.20 2.8443825 3.1243634 -11.755617 -9.075637 2
#> 4 1 -14.20 -0.55 1.4763160 2.2306441 -12.723684 1.680644 2
#> 5 1 -5.40 -3.30 0.9374540 -0.2787169 -4.462546 -3.578717 2
#> 6 1 -4.10 -2.55 0.6807364 -0.2342607 -3.419264 -2.784261 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6160 -36375 6900
#> initial value 998.131940
#> iter 2 value 857.440913
#> iter 3 value 852.956125
#> iter 4 value 849.772052
#> iter 5 value 797.253596
#> iter 6 value 787.183801
#> iter 7 value 785.522528
#> iter 8 value 785.489651
#> iter 9 value 785.489600
#> iter 10 value 785.489558
#> iter 11 value 785.489537
#> iter 12 value 785.489519
#> iter 12 value 785.489519
#> iter 12 value 785.489519
#> final value 785.489519
#> converged
#> This is Run number 388
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.36174480 2.7714974 -0.9117448 -10.428503 1
#> 2 1 -3.10 -5.40 4.52591694 0.7494141 1.4259169 -4.650586 1
#> 3 1 -14.60 -12.20 1.18732072 -0.6703147 -13.4126793 -12.870315 2
#> 4 1 -14.20 -0.55 0.02045354 -1.2137956 -14.1795465 -1.763796 2
#> 5 1 -5.40 -3.30 -1.14195155 -0.1284578 -6.5419516 -3.428458 2
#> 6 1 -4.10 -2.55 -0.36668462 0.6685271 -4.4666846 -1.881473 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6700 -37425 7250
#> initial value 998.131940
#> iter 2 value 841.098085
#> iter 3 value 836.023028
#> iter 4 value 834.743978
#> iter 5 value 784.402702
#> iter 6 value 773.907471
#> iter 7 value 772.324222
#> iter 8 value 772.295524
#> iter 9 value 772.295439
#> iter 10 value 772.295382
#> iter 11 value 772.295329
#> iter 11 value 772.295325
#> iter 11 value 772.295325
#> final value 772.295325
#> converged
#> This is Run number 389
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 3.1351235 -1.0196000 2.585124 -14.219600 1
#> 2 1 -3.10 -5.40 0.6471258 1.1239794 -2.452874 -4.276021 1
#> 3 1 -14.60 -12.20 -1.3715849 1.7895763 -15.971585 -10.410424 2
#> 4 1 -14.20 -0.55 0.1268548 2.7886226 -14.073145 2.238623 2
#> 5 1 -5.40 -3.30 -1.2344047 0.8716523 -6.634405 -2.428348 2
#> 6 1 -4.10 -2.55 0.8286841 -0.2080549 -3.271316 -2.758055 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6200 -37450 6975
#> initial value 998.131940
#> iter 2 value 842.718842
#> iter 3 value 835.851092
#> iter 4 value 831.089809
#> iter 5 value 782.349490
#> iter 6 value 771.982758
#> iter 7 value 770.377198
#> iter 8 value 770.344590
#> iter 9 value 770.344547
#> iter 10 value 770.344509
#> iter 11 value 770.344471
#> iter 11 value 770.344467
#> iter 11 value 770.344467
#> final value 770.344467
#> converged
#> This is Run number 390
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.3394136 2.2706698 -0.8894136 -10.9293302 1
#> 2 1 -3.10 -5.40 -0.3372620 -0.2321140 -3.4372620 -5.6321140 1
#> 3 1 -14.60 -12.20 0.5585245 0.4357659 -14.0414755 -11.7642341 2
#> 4 1 -14.20 -0.55 0.8460921 1.0686805 -13.3539079 0.5186805 2
#> 5 1 -5.40 -3.30 1.0522216 0.6795299 -4.3477784 -2.6204701 2
#> 6 1 -4.10 -2.55 1.2893080 0.7687677 -2.8106920 -1.7812323 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6760 -36750 7350
#> initial value 998.131940
#> iter 2 value 849.425263
#> iter 3 value 845.682913
#> iter 4 value 845.238072
#> iter 5 value 792.528336
#> iter 6 value 782.183668
#> iter 7 value 780.592927
#> iter 8 value 780.565435
#> iter 9 value 780.565368
#> iter 10 value 780.565327
#> iter 11 value 780.565277
#> iter 12 value 780.565257
#> iter 12 value 780.565257
#> iter 12 value 780.565257
#> final value 780.565257
#> converged
#> This is Run number 391
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 1.1525636 0.18692029 0.6025636 -13.013080 1
#> 2 1 -3.10 -5.40 1.0966209 0.13489647 -2.0033791 -5.265104 1
#> 3 1 -14.60 -12.20 1.1558770 -1.12718710 -13.4441230 -13.327187 2
#> 4 1 -14.20 -0.55 -0.5647706 3.29213805 -14.7647706 2.742138 2
#> 5 1 -5.40 -3.30 1.8951711 -0.01545755 -3.5048289 -3.315458 2
#> 6 1 -4.10 -2.55 -0.4961300 0.71161185 -4.5961300 -1.838388 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6800 -35500 6225
#> initial value 998.131940
#> iter 2 value 871.957676
#> iter 3 value 870.651828
#> iter 4 value 870.218846
#> iter 5 value 815.616871
#> iter 6 value 805.843147
#> iter 7 value 803.985905
#> iter 8 value 803.942829
#> iter 9 value 803.942722
#> iter 9 value 803.942720
#> iter 9 value 803.942720
#> final value 803.942720
#> converged
#> This is Run number 392
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -1.77607401 0.9134904 -2.326074 -12.2865096 1
#> 2 1 -3.10 -5.40 0.05643062 1.6030656 -3.043569 -3.7969344 1
#> 3 1 -14.60 -12.20 -0.93336345 1.6214816 -15.533363 -10.5785184 2
#> 4 1 -14.20 -0.55 0.93513806 0.2221048 -13.264862 -0.3278952 2
#> 5 1 -5.40 -3.30 1.50119954 -0.1111514 -3.898800 -3.4111514 2
#> 6 1 -4.10 -2.55 0.70646955 4.3717692 -3.393530 1.8217692 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7000 -36475 6350
#> initial value 998.131940
#> iter 2 value 858.920639
#> iter 3 value 856.506114
#> iter 4 value 856.042396
#> iter 5 value 804.042021
#> iter 6 value 793.768601
#> iter 7 value 791.967662
#> iter 8 value 791.925713
#> iter 9 value 791.925634
#> iter 10 value 791.925602
#> iter 11 value 791.925553
#> iter 12 value 791.925513
#> iter 12 value 791.925513
#> iter 12 value 791.925513
#> final value 791.925513
#> converged
#> This is Run number 393
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.4779866 0.2095971 -0.07201338 -12.990403 1
#> 2 1 -3.10 -5.40 -1.1946745 -0.9929681 -4.29467448 -6.392968 1
#> 3 1 -14.60 -12.20 2.7704088 -0.5104771 -11.82959117 -12.710477 1
#> 4 1 -14.20 -0.55 1.6459159 -0.7470388 -12.55408405 -1.297039 2
#> 5 1 -5.40 -3.30 3.1864978 3.1039150 -2.21350219 -0.196085 2
#> 6 1 -4.10 -2.55 0.1068132 1.1973759 -3.99318675 -1.352624 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7580 -38650 5475
#> initial value 998.131940
#> iter 2 value 833.180233
#> iter 3 value 829.082262
#> iter 4 value 827.641781
#> iter 5 value 783.853059
#> iter 6 value 772.811777
#> iter 7 value 770.945472
#> iter 8 value 770.891289
#> iter 9 value 770.891205
#> iter 9 value 770.891197
#> iter 9 value 770.891197
#> final value 770.891197
#> converged
#> This is Run number 394
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.5032735 0.47128796 -1.053273 -12.72871204 1
#> 2 1 -3.10 -5.40 1.5885672 4.21126681 -1.511433 -1.18873319 2
#> 3 1 -14.60 -12.20 2.0099078 -0.84221577 -12.590092 -13.04221577 1
#> 4 1 -14.20 -0.55 1.4191837 0.50368591 -12.780816 -0.04631409 2
#> 5 1 -5.40 -3.30 -0.2454420 0.03204142 -5.645442 -3.26795858 2
#> 6 1 -4.10 -2.55 -1.0393022 2.26193351 -5.139302 -0.28806649 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7180 -37925 4975
#> initial value 998.131940
#> iter 2 value 846.397776
#> iter 3 value 842.131543
#> iter 4 value 838.630315
#> iter 5 value 794.026839
#> iter 6 value 783.396314
#> iter 7 value 781.228182
#> iter 8 value 781.158327
#> iter 9 value 781.158095
#> iter 9 value 781.158091
#> iter 9 value 781.158091
#> final value 781.158091
#> converged
#> This is Run number 395
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -1.0495120 0.1425386 -1.599512 -13.057461 1
#> 2 1 -3.10 -5.40 0.1347887 -0.1501871 -2.965211 -5.550187 1
#> 3 1 -14.60 -12.20 0.6885262 0.7470109 -13.911474 -11.452989 2
#> 4 1 -14.20 -0.55 -0.0289465 -0.9971809 -14.228947 -1.547181 2
#> 5 1 -5.40 -3.30 -0.3519413 -1.1957222 -5.751941 -4.495722 2
#> 6 1 -4.10 -2.55 1.1761328 0.1407550 -2.923867 -2.409245 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6360 -36300 6375
#> initial value 998.131940
#> iter 2 value 861.447568
#> iter 3 value 857.708665
#> iter 4 value 854.831919
#> iter 5 value 802.870214
#> iter 6 value 792.797613
#> iter 7 value 791.030795
#> iter 8 value 790.991400
#> iter 9 value 790.991348
#> iter 9 value 790.991344
#> iter 9 value 790.991344
#> final value 790.991344
#> converged
#> This is Run number 396
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 2.4755021 0.06237016 1.925502 -13.1376298 1
#> 2 1 -3.10 -5.40 0.4286479 1.94993959 -2.671352 -3.4500604 1
#> 3 1 -14.60 -12.20 2.3066034 0.45934110 -12.293397 -11.7406589 2
#> 4 1 -14.20 -0.55 -0.5589899 0.28153782 -14.758990 -0.2684622 2
#> 5 1 -5.40 -3.30 -0.7702897 3.72361751 -6.170290 0.4236175 2
#> 6 1 -4.10 -2.55 -0.6747313 -1.08871004 -4.774731 -3.6387100 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6380 -34525 6850
#> initial value 998.131940
#> iter 2 value 880.032608
#> iter 3 value 879.630250
#> iter 4 value 879.258997
#> iter 5 value 820.956237
#> iter 6 value 811.624250
#> iter 7 value 809.949813
#> iter 8 value 809.917764
#> iter 9 value 809.917699
#> iter 10 value 809.917667
#> iter 11 value 809.917618
#> iter 12 value 809.917583
#> iter 12 value 809.917583
#> iter 12 value 809.917583
#> final value 809.917583
#> converged
#> This is Run number 397
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 0.4127254 1.0696889 -0.1372746 -12.130311 1
#> 2 1 -3.10 -5.40 1.0890676 0.1471700 -2.0109324 -5.252830 1
#> 3 1 -14.60 -12.20 -0.9787259 -0.7755516 -15.5787259 -12.975552 2
#> 4 1 -14.20 -0.55 3.0508137 -0.4815260 -11.1491863 -1.031526 2
#> 5 1 -5.40 -3.30 0.3587291 1.0805386 -5.0412709 -2.219461 2
#> 6 1 -4.10 -2.55 -0.7615710 -0.5749595 -4.8615710 -3.124960 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7500 -38725 6350
#> initial value 998.131940
#> iter 2 value 827.446438
#> iter 3 value 822.558122
#> iter 4 value 821.851939
#> iter 5 value 776.924041
#> iter 6 value 765.888685
#> iter 7 value 764.279087
#> iter 8 value 764.243281
#> iter 9 value 764.243214
#> iter 10 value 764.243163
#> iter 11 value 764.243102
#> iter 12 value 764.243084
#> iter 12 value 764.243084
#> iter 12 value 764.243084
#> final value 764.243084
#> converged
#> This is Run number 398
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.19810697 0.7475267 -0.748107 -12.4524733 1
#> 2 1 -3.10 -5.40 0.21940071 0.6292710 -2.880599 -4.7707290 1
#> 3 1 -14.60 -12.20 -0.08426863 -0.5195433 -14.684269 -12.7195433 2
#> 4 1 -14.20 -0.55 0.06867569 -0.1503295 -14.131324 -0.7003295 2
#> 5 1 -5.40 -3.30 -0.98542122 0.3541618 -6.385421 -2.9458382 2
#> 6 1 -4.10 -2.55 -0.04739789 0.1743626 -4.147398 -2.3756374 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7920 -36975 3625
#> initial value 998.131940
#> iter 2 value 863.770383
#> iter 3 value 862.373377
#> iter 4 value 861.466073
#> iter 5 value 814.767267
#> iter 6 value 805.272728
#> iter 7 value 801.904964
#> iter 8 value 801.782109
#> iter 9 value 801.781256
#> iter 10 value 801.781222
#> iter 10 value 801.781219
#> iter 11 value 801.781207
#> iter 11 value 801.781203
#> iter 11 value 801.781203
#> final value 801.781203
#> converged
#> This is Run number 399
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.11338816 1.6303534 -0.6633882 -11.5696466 1
#> 2 1 -3.10 -5.40 -1.48652526 0.2084949 -4.5865253 -5.1915051 1
#> 3 1 -14.60 -12.20 -0.74340974 1.8836700 -15.3434097 -10.3163300 2
#> 4 1 -14.20 -0.55 -1.53333449 1.4059529 -15.7333345 0.8559529 2
#> 5 1 -5.40 -3.30 1.08601225 -0.9277652 -4.3139877 -4.2277652 2
#> 6 1 -4.10 -2.55 0.08235672 -0.1059771 -4.0176433 -2.6559771 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7740 -40300 5750
#> initial value 998.131940
#> iter 2 value 806.384143
#> iter 3 value 799.953898
#> iter 4 value 797.550839
#> iter 5 value 759.127767
#> iter 6 value 747.943856
#> iter 7 value 746.422014
#> iter 8 value 746.383027
#> iter 9 value 746.382851
#> iter 10 value 746.382800
#> iter 11 value 746.382766
#> iter 12 value 746.382747
#> iter 12 value 746.382747
#> iter 12 value 746.382747
#> final value 746.382747
#> converged
#> This is Run number 400
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation Block alt1_x1 alt2_x1 alt1_x2 alt2_x2 alt1_x3 alt2_x3
#> 1 1 1 1 80 20 25 200 100 50
#> 2 1 2 1 60 40 50 100 50 100
#> 3 1 3 1 60 20 200 200 0 100
#> 4 1 4 1 20 80 200 25 0 100
#> 5 1 5 1 40 80 100 50 100 50
#> 6 1 6 1 60 80 50 25 0 0
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -13.20 -0.6484114 -0.3797587 -1.198411 -13.579759 1
#> 2 1 -3.10 -5.40 1.3093953 -0.8788816 -1.790605 -6.278882 1
#> 3 1 -14.60 -12.20 3.1085922 0.1224695 -11.491408 -12.077531 1
#> 4 1 -14.20 -0.55 -0.1391515 -0.8204010 -14.339152 -1.370401 2
#> 5 1 -5.40 -3.30 0.5530511 0.1906169 -4.846949 -3.109383 2
#> 6 1 -4.10 -2.55 0.9200868 -0.5012580 -3.179913 -3.051258 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6860 -38450 6575
#> initial value 998.131940
#> iter 2 value 830.779526
#> iter 3 value 824.427579
#> iter 4 value 821.459793
#> iter 5 value 775.913457
#> iter 6 value 765.131017
#> iter 7 value 763.536066
#> iter 8 value 763.501323
#> iter 9 value 763.501252
#> iter 10 value 763.501202
#> iter 11 value 763.501155
#> iter 11 value 763.501150
#> iter 11 value 763.501150
#> final value 763.501150
#> converged
#>
#>
#> ================ ==== === ===== ==== ====== ===== ===== ===== ===== ======== ====
#> \ vars n mean sd median min max range skew kurtosis se
#> ================ ==== === ===== ==== ====== ===== ===== ===== ===== ======== ====
#> est_bpreis 1 400 -0.01 0.00 -0.01 -0.01 0.00 0.01 -0.16 0.09 0.00
#> est_blade 2 400 -0.01 0.00 -0.01 -0.02 -0.01 0.01 0.04 0.07 0.00
#> est_bwarte 3 400 0.01 0.00 0.01 0.00 0.01 0.01 0.00 0.31 0.00
#> rob_pval0_bpreis 4 400 0.11 0.17 0.04 0.00 0.99 0.99 2.71 8.17 0.01
#> rob_pval0_blade 5 400 0.00 0.00 0.00 0.00 0.00 0.00 NaN NaN 0.00
#> rob_pval0_bwarte 6 400 0.00 0.01 0.00 0.00 0.14 0.14 12.63 188.64 0.00
#> ================ ==== === ===== ==== ====== ===== ===== ===== ===== ======== ====
#>
#> FALSE TRUE
#> 47.25 52.75
#> 1923.439 sec elapsed
#> $tic
#> elapsed
#> 0.851
#>
#> $toc
#> elapsed
#> 1924.29
#>
#> $msg
#> logical(0)
#>
#> $callback_msg
#> [1] "1923.439 sec elapsed"
#> Trying tidyr::pivot_longer for reshaping...
```
<img src="man/figures/README-example-1.png" width="100%" /><img src="man/figures/README-example-2.png" width="100%" /><img src="man/figures/README-example-3.png" width="100%" />