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]);

}