When using the non-centered parameterisation for the multivariate normal:

```
parameters {
vector[N] beta_raw;
vector[N] mu;
cholesky_factor_corr[N] L;
}
transformed parameters {
vector[N] beta = mu + L * beta_raw;
}
model{
beta_raw ~ normal(0,1);
...
}
```

Is there an equivalent for where the parameter (`beta`

) comes from a mixture of multivariate normals? For example, this is the centered parameterisation for what I’m referring to:

```
parameters {
simplex[K] theta;
vector[N] beta;
vector[N] mu[K];
cholesky_factor_corr[N] L[K];
}
model {
vector[K] log_theta = log(theta);
for (k in 1:K)
log_theta[k] += multi_normal_cholesky_lpdf(beta | mu[k], L[k]);
target += log_sum_exp(log_theta);
}
```

Thanks!