Is there a way to constrain samples from a multivariate normal rng to be positive so they can be used as a rate parameter to a Poisson? According to the manual, T[L,U] can be added to sample statements, but I don’t see anything about RNGs. Or is there a better way to do something like:
vector[2] y_sim[N];
vector<lower=0>[2] lambda_sim; //getting negative numbers when run
for(i in 1:N) {
lambda_sim = multi_normal_cholesky_rng(mu, sigma)T[0.01,];
y_sim[i,1] = poisson_rng(lambda_sim[1]);
y_sim[i,2] = poisson_rng(lambda_sim[2]);
}