Hello Stan users,

I am trying to simulate some fake data for regression and I have come up with two codes:

**The first code is:**

```
data {
int<lower=0> N; // Number of obs
int<lower=0> P; // Number of expla
matrix[N,P] X; // matrix for fake explanatory variables
}
generated quantities {
vector[N] yhat;
vector[P] beta;
real alpha;
real<lower = 0> sigma;
alpha = normal_rng(0.05,0.02);
beta[1] = normal_rng(-0.40,0.15);
beta[2] = normal_rng(-0.60,0.15);
beta[3] = normal_rng(0.15,0.05);
beta[4] = normal_rng(0.10,0.03);
beta[5] = normal_rng(0.05,0.02);
beta[6] = normal_rng(0.06,0.02);
beta[7] = normal_rng(-0.01,0.01);
beta[8] = normal_rng(-0.001,0.02);
beta[9] = normal_rng(0.02,0.01);
beta[10] = normal_rng(0.01,0.02);
beta[11] = normal_rng(-0.02,0.001);
sigma = gamma_rng(1,1);
for (i in 1:N) {
yhat[i] = normal_rng(alpha + X[i]*beta , sigma);
}
}
****
**The second code is**
data {
int<lower=0> N; // Number of obs
int<lower=0> P; // Number of expla
matrix[N,P] X; // matrix for fake explanatory variables
}
parameters {
vector[P] beta;
real alpha;
real<lower = 0> sigma;
}
model {
beta[1] ~ normal(-0.40,0.15);
beta[2] ~ normal(-0.60,0.15);
beta[3] ~ normal(0.15,0.05);
beta[4] ~ normal(0.10,0.03);
beta[5] ~ normal(0.05,0.02);
beta[6] ~ normal(0.06,0.02);
beta[7] ~ normal(-0.01,0.01);
beta[8] ~ normal(-0.001,0.02);
beta[9] ~ normal(0.02,0.01);
beta[10] ~ normal(0.01,0.02);
beta[11] ~ normal(-0.02,0.001);
sigma ~ gamma(1, 1);
}
generated quantities {
vector[N] yhat;
for (i in 1:N) {
yhat[i] = normal_rng(alpha + X[i]*beta - sigma);
}
}
****
I am wondering which of these two simulation code should I use if I intend to recover the model parameters in the next step.
Any suggestion will be greatly appreciated.
Cheers
AA
```