Add Poetest and its documentation

put takedraws and getalldraws functions into the poetest function such that everything makes sense with roxygen and the documentation; add option to use the robust variance covariance matrix; update to version 0.3.3

R/poetest.R

-
-
-## Extract relevant elements of models
-
-takedraws <-function(n=10000, beta,vc) {
-
-
-  k=length(beta)
-  cholesky = chol(vc)
-
-  draw=matrix(nrow = n, ncol=k)
-
-  colnames(draw) <-names(beta)
-
-  for (d in 1:n) {
-    draw[d,] <- beta +t(cholesky)%*%stats::rnorm(k)
+# This function lets us perform the Poe (2005) test on WTP values
+
+
+#' Perform the Poe (2005) test on different discrete choice models
+#'
+#' @param n number of draws
+#' @param model1 Model from which to take the first WTP values
+#' @param model2 Model from which to take the second WTP values
+#' @param att Vector of attributes whose WTP values you want to compare
+#' @param price name of the price coefficient
+#' @param vcov which variance-covariance matrix to use. Either normal for the normal one, or rob for the robust one.
+#'
+#' @return a p value associated with "WTP1>WTP2"
+#' @export
+#'
+#' @examples \dontrun{
+#' poeresults<-poetest(n=5000, model1 = clmodels[[model_1]],model2 = clmodels[[model_2]],
+#'  att=attr, price = "bcost", vcov = "normal")
+#' }
+poetest <- function(n, model1, model2, att, price, vcov){
+  
+  #stop command for invalid variance covariance matrix
+  if (!vcov %in% c("rob", "normal")) {
+    stop("Invalid value for 'vcov'. Please use one of 'rob' or 'normal'.")
   }
-
-
-
-  return(draw)
-}
-
-
-getalldraws <- function(n, model1, model2, att, price) {
-
-  allmodels <- list(model1,model2)
-
-  model_draws <- list()
-
-  for (m in 1:2) {
-
-  model_draws[[m]] <-takedraws(n,allmodels[[m]][["estimate"]],allmodels[[m]][["varcov"]])
-
-  model_draws[[m]] <-cbind(model_draws[[m]], wtp= model_draws[[m]][,att]/model_draws[[m]][,price])
-     }
-
-  return(model_draws)
+  
+  ## Extract relevant elements of models
+  
+  takedraws <-function(n=10000, beta,vc) {
+    
+    
+    k=length(beta)
+    cholesky = chol(vc)
+    
+    draw=matrix(nrow = n, ncol=k)
+    
+    colnames(draw) <-names(beta)
+    
+    for (d in 1:n) {
+      draw[d,] <- beta +t(cholesky)%*%stats::rnorm(k)
+    }
+    
+    
+    
+    return(draw)
   }
+  
+  getalldraws <- function(n, model1, model2, att, price, vcov) {
+    
+    allmodels <- list(model1,model2)
+    
+    model_draws <- list()
+    
+    for (m in 1:2) {
+      
+      #implement the option to choose between the robust or the normal variance covariance matrix
+      varcov_matrix <- switch(vcov,
+                              rob = allmodels[[m]][["robvarcov"]],
+                              normal = allmodels[[m]][["varcov"]],
+                              stop("Invalid value for 'vcov'. Please use one of 'rob' or 'normal'.")
+      )
+      
+      model_draws[[m]] <-takedraws(n,allmodels[[m]][["estimate"]],varcov_matrix)
+      
+      model_draws[[m]] <-cbind(model_draws[[m]], wtp= model_draws[[m]][,att]/model_draws[[m]][,price])
+    }
+    
+    return(model_draws)
+  }
+  
+  
+  draws<-getalldraws(n, model1, model2, att, price, vcov)
 
-poetest <- function(n, model1, model2, att, price){
-
-draws<-getalldraws(n, model1, model2, att, price)
-
-wtpvec <- cbind(wtp1= draws[[1]][,"wtp"], wtp2= draws[[2]][,"wtp"])
+  wtpvec <- cbind(wtp1= draws[[1]][,"wtp"], wtp2= draws[[2]][,"wtp"])