Issue in replicating stan model in Numpyro

numpyro
1

How can we implement such stan models in Numpyro where the parameter is contained to have a lower value of 0 and the prior that we are using for it is a Normal centered around 0. For example:

parameters {
  real<lower=0> sigma_y;
  real<lower=0> sigma_alpha;
  real<lower=0> sigma_beta;
}

model {
  vector[N] mu;
  // Prior
  sigma_y ~ normal(0,1);
  sigma_beta ~ normal(0,1);
  sigma_alpha ~ normal(0,1);
  mu_alpha ~ normal(0,10);
  mu_beta ~ normal(0,10);

  alpha ~ normal(mu_alpha, sigma_alpha);
  beta ~ normal(mu_beta, sigma_beta);
  for(n in 1:N){
    mu[n] = alpha[county_idx[n]] + floor_measure[n] * beta[county_idx[n]];
    target += normal_lpdf(log_radon[n] | mu[n], sigma_y);
  }
}

Is the closest possible solution for implementing it in Numpyro using HalfNormal, or is there some way to put constraints on the parameters in Numpyro similar to Stan?

2

in this case you can use the TruncatedNormal distribution. also see this tutorial

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