diff --git a/src/model_fitting/abundance_model.R b/src/model_fitting/abundance_model.R index cbb71191f168b932ad014acb481406fff1624168..8590860b9d69583c6a59022457994f4c16b74284 100644 --- a/src/model_fitting/abundance_model.R +++ b/src/model_fitting/abundance_model.R @@ -262,7 +262,7 @@ model_terms <- names(glm.nb(as.formula(paste("nr_nests~", paste(m_terms, "+ offset(offset_term)", sep = "")), data = predictors_obs, - control = glm.control(maxit = 500))$coefficients) + control = glm.control(maxit = 250))$coefficients) # prediction estimates intercept <- rep(1, nrow(predictors_obs)) predictor_estimates <- cbind( intercept, @@ -286,7 +286,7 @@ model <- as.formula( paste("nr_nests ~", full_model, "+ offset(offset_term)")) res_full <- glm.nb(model, data = predictors_obs, - control = glm.control(maxit = 500)) + control = glm.control(maxit = 250)) # HERE I CAN NOW USE THE OTHER FUNCTION dfbeta_frame <- data.frame(slope=res_full$coefficients, res_full$coefficients+ @@ -329,7 +329,7 @@ results_res <- foreach(i = 1:nrow(all_model_terms), paste(m_terms[all_model_terms[i, ] == 1], collapse = "+"), "+ offset(offset_term)")) res <- glm.nb(model, data = predictors_obs, - control = glm.control(maxit = 500)) + control = glm.control(maxit = 250)) # model