r - simple Gamma GLM in STAN -

i'm trying simple gamma glm in stan , r, crashes immediately

generate data:

set.seed(1) library(rstan) n<-500 #sample size dat<-data.frame(x1=runif(n,-1,1),x2=runif(n,-1,1)) #the model x<-model.matrix(~.,dat) k<-dim(x)[2] #number of regression params #the regression slopes betas<-runif(k,-1,1) shape <- 10 #simulate gamma data mus<-exp(x%*%betas) y<-rgamma(500,shape=shape,rate=shape/mus) 

this stan model:

model_string <- " data {   int<lower=0> n; //the number of observations   int<lower=0> k; //the number of columns in model matrix   matrix[n,k] x; //the model matrix   vector[n] y; //the response } parameters {   vector[k] betas; //the regression parameters   real<lower=0, upper=1000> shape; //the shape parameter } model {     y ~ gamma(shape, (shape/exp(x * betas))); }" 

when run model, r crashes:

m <- stan(model_code = model_string, data = list(x=x, k=3, n=500, y=y), chains = 1, cores=1) 

update : think problem somewhere in vectorization can running model pass every column of x vector.

update2: works

  for(i in 1:n)     y[i] ~ gamma(shape, (shape / exp(x[i,] * betas))); 

the problem original code there no operator defined in stan scalar divided vector. in case, shape / exp(x * betas) might able shape[1:n] ./ exp(x * betas) or failing that, (shape * ones_vector) ./ exp(x * betas)