Hi,

I’m trying to code a model where group-level parameters are correlated and hence drawn from a multivariate normal. I am Below is my model:

```
data{
int<lower=1> N; // rows of observations
int<lower=0> sdl[N]; // observed response
int<lower=1> K; //no.of predictors
int<lower=1> J; //no.of groups
int<lower=1> L; // num group-level predictors
matrix[N,K] X; // population-level predictor
int<lower=1, upper=J> jj[N]; // number of groups
}
parameters{
corr_matrix[K] Omega; // correlation matrix
vector<lower=0>[K] tau; // scale
vector[K] beta[J]; // indiv coeffs per group
real<lower=0> phi; // shape parameter
}
model{
vector[N] x_beta_jj; // mean expectation
matrix[K,K] Sigma_beta;
vector[2] mu_beta;
Sigma_beta = quad_form_diag(Omega,tau);
tau ~ cauchy(0,5);
Omega ~ lkj_corr(2.0); // prior covariance
mu_a ~ normal(0, 10);
mu_b ~ normal(0, 10);
// random effect priors
for (j in 1:J)
mu_beta[1] = mu_a;
mu_beta[2] = mu_b;
beta ~ multi_normal(mu_beta, Sigma_beta);
phi ~ gamma(0.01, 0.01);
// Likelihood
for (n in 1:N)
x_beta_jj[n] = (X[n]*beta[jj[n]]); //log location
sdl ~ neg_binomial_2_log(x_beta_jj, phi);
}
```

With this model, I get the following error:

```
SYNTAX ERROR, MESSAGE(S) FROM PARSER:
variable "mu_a" does not exist.
```

I tried to tweak the multivariate specification based on the Stan User Manual, but was unsuccessful. Any help will be much appreciated!

Thanks,

Meghna