
data {
  int<lower=0> n_i;
  int<lower=0> n_k;
  int y[n_i,n_k];
}


parameters {
  vector[n_i] alphas;
  vector[n_k] betas;
  vector<lower=0, upper=1>[n_k] inv_omegas;
  real<lower=0> sigma_alpha;
  real mu_beta;
  real<lower=0> sigma_beta;
}

transformed parameters {
  vector<lower=0>[n_k] omegas = 1.0 ./ inv_omegas;
  matrix<lower=0>[n_i,n_k] par1;
  vector<lower=0>[n_k] par2;
  
  for(i in 1:n_i){
	for(k in 1:n_k){
		par1[i,k] = exp(alphas[i] + betas[k]) / (omegas[k] - 1.0);
	}
  }
  
  for(k in 1:n_k){
	par2[k] = 1.0 / (omegas[k] - 1.0);
  }
}

model {
  alphas ~ normal(0, sigma_alpha);
  betas ~ normal(mu_beta, sigma_beta);
  
  for(k in 1:n_k) {
    for (i in 1:n_i) {
      y[i,k] ~ neg_binomial(par1[i,k], par2[k]);
    }
  }
}
