I already fitted a regression model with JAGS

```
model{
    for(i in 1:n) {
        y[i] ~ dbeta(alpha[i], beta[i])
        alpha[i] <- mu[i] * phi[i]
        beta[i]  <- (1 - mu[i]) * phi[i]
        log(phi[i]) <- -inprod(X2[i, ], delta[])
        cloglog(mu[i]) <- inprod(X1[i, ], B[])
    }

    for (j in 1:p){
        B[j] ~ dnorm(0, .001)
    }

    for(k in 1:s){
        delta[k] ~ dnorm(0, .001)
    }
}

```

But I need to simulate 50 samples of response variable where each one have size, to do some plots. How can I do it?

I found this thread a litle help [Estimating unknown response variable in JAGS - unsupervised learning](https://stackoverflow.com/questions/28533934/estimating-unknown-response-variable-in-jags-unsupervised-learning)

Should I run the chain again given the values of posterior estimates that I already have as inits?