Graded Response Model: R for Windows terminal front-end has stopped working

Hi All,
I am trying to fit a graded response model in rstan. Unfortunately, R keeps crashing with the error “R for Windows terminal front-end has stopped working.”

I get the following output before the crash happens:

> stanout <- stan('latent-factor-model.stan'
+               , data=standat
+               , iter=4000
+               , chains=1)
hash mismatch so recompiling; make sure Stan code ends with a blank line
In file included from C:/Users/CURTS025/programs/R/library/BH/include/boost/config.hpp:39:0,
                 from C:/Users/CURTS025/programs/R/library/BH/include/boost/math/tools/config.hpp:13,
                 from C:/Users/CURTS025/programs/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:7,
                 from C:/Users/CURTS025/programs/R/library/StanHeaders/include/stan/math/rev/core/gevv_vvv_vari.hpp:5,
                 from C:/Users/CURTS025/programs/R/library/StanHeaders/include/stan/math/rev/core.hpp:12,
                 from C:/Users/CURTS025/programs/R/library/StanHeaders/include/stan/math/rev/mat.hpp:4,
                 from C:/Users/CURTS025/programs/R/library/StanHeaders/include/stan/math.hpp:4,
                 from C:/Users/CURTS025/programs/R/library/StanHeaders/include/src/stan/model/model_header.hpp:4,
                 from file46d031c2faa.cpp:8:
C:/Users/CURTS025/programs/R/library/BH/include/boost/config/compiler/gcc.hpp:186:0: warning: "BOOST_NO_CXX11_RVALUE_REFERENCES" redefined
<command-line>:0:0: note: this is the location of the previous definition
SAMPLING FOR MODEL 'latent-factor-model' NOW (CHAIN 1).
Gradient evaluation took 0 seconds
1000 transitions using 10 leapfrog steps per transition would take 0 seconds.
Adjust your expectations accordingly!
Iteration:    1 / 4000 [  0%]  (Warmup)

My R code and Stan code are below.

## Simulated data
simgrm <- function(n_subj, n_items, n_cat){
    item_prob <- function(t, a, k){
        c(0, plogis(k - a*t), 1) %>%
    item_sample <- function(t, a, k){
        item_prob(t, a, k) %>% sample(1:length(.), 1, prob=.)
    theta <- rnorm(n_subj)
    alpha <- rnorm(n_items)
    kappa <- t(sapply(1:n_items
                    , function(j){
                        sort(c(rnorm(n_cat - 1)))
    out <- data_frame(Respondent_Idx=1:n_subj) %>%
        crossing(Item_Idx=1:n_items) %>%
                      , t=theta[Respondent_Idx]
                      , a=alpha[Item_Idx]
                      , k=as.list(data.frame(t(kappa[Item_Idx, ])))))
n_cat <- 3L
n_respondents <- 500L
n_items <- 5L
tmpdat <- simgrm(n_respondents, n_items, n_cat)
standat <- list(
  , n_respondents=length(unique(tmpdat$Respondent_Idx))
  , n_items=length(unique(tmpdat$Item_Idx))
  , n_cat=n_cat
  , Respondent_Idx=tmpdat$Respondent_Idx
  , Item_Idx=tmpdat$Item_Idx
  , Y=tmpdat$Y
stanout <- stan('latent-factor-model.stan'
              , data=standat
              , iter=4000
              , chains=1)

data {
    int <lower=1> n_data;
    int <lower=1> n_items;
    int <lower=1> n_respondents;
    int <lower=1> n_cat;
    int <lower=1, upper=n_items>       Item_Idx[n_data];
    int <lower=1, upper=n_respondents> Respondent_Idx[n_data];
    int <lower=1, upper=n_cat>         Y[n_data];
parameters {
    vector[n_respondents] theta;
    real<lower=0> alpha[n_items];
    ordered[n_cat - 1] kappa[n_items];
    real mu_kappa;
    real<lower=0> sigma_kappa;
model {
    theta ~ normal(0.0, 1.0);
    alpha ~ cauchy(0.0, 5.0);
    mu_kappa ~ normal(0.0, 5.0);
    sigma_kappa ~ cauchy(0.0, 5.0);
    for (j in 1:n_items){
       for (k in 1:(n_cat - 1)){
           kappa[j, k] ~ normal(mu_kappa, sigma_kappa);
    for (n in 1:n_data) {
        Y[n] ~ ordered_logistic(theta[Respondent_Idx[n]] * alpha[Item_Idx[n]], kappa[Item_Idx[n]]);

Any help would be appreciated!

Thank you,

[edited to set off code]

I edited the post to add triple back-ticks to wrap code so it displays fixed width.

It would help if you gave us your sessionInfo() output. I don’t even have a guess as to what’s going on, but the RStan devs should.

Thanks for fixing my formatting! (I’m not familiar with this interface…).

Results of sessionInfo() just before calling the stan function:

> sessionInfo()
R version 3.4.0 (2017-04-21)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 7 x64 (build 7601) Service Pack 1
Matrix products: default
[1] LC_COLLATE=English_United States.1252
[2] LC_CTYPE=English_United States.1252  
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                         
[5] LC_TIME=English_United States.1252   
attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base    
other attached packages:
[1] bindrcpp_0.2         rstan_2.15.1         StanHeaders_2.15.0-1
[4] dplyr_0.7.0          purrr_0.2.2.2        readr_1.1.1        
 [7] tidyr_0.6.3          tibble_1.3.3         ggplot2_2.2.1      
[10] tidyverse_1.1.1    
loaded via a namespace (and not attached):
[1] Rcpp_0.12.11     bindr_0.1        compiler_3.4.0   cellranger_1.1.0
[5] plyr_1.8.4       forcats_0.2.0    tools_3.4.0      jsonlite_1.5   
 [9] lubridate_1.6.0  gtable_0.2.0     nlme_3.1-131     lattice_0.20-35
[13] rlang_0.1.1      psych_1.7.5      parallel_3.4.0   haven_1.0.0    
[17] gridExtra_2.2.1  stringr_1.2.0    httr_1.2.1       xml2_1.1.1     
[21] hms_0.3          stats4_3.4.0     grid_3.4.0       inline_0.3.14  
[25] glue_1.1.0       R6_2.2.2         readxl_1.0.0     foreign_0.8-68 
[29] reshape2_1.4.2   modelr_0.1.0     magrittr_1.5     scales_0.4.1   
[33] assertthat_0.2.0 mnormt_1.5-5     rvest_0.3.2      colorspace_1.3-2
[37] stringi_1.1.5    lazyeval_0.2.0   munsell_0.4.3    broom_0.4.2    

Thanks. @bgoodri or @jonah are probably going to have to answer this one.

It worked for me on Windows.

Bummer. Thanks for looking at this. After I read your response, I tried running the code on a different computer and it worked for me too. Not sure what is wrong with my laptop… Thanks again.