Dear Stan folks,

I am wondering how Stan works during the warm-up phase. To do the prior predictive checks, I programmed the R code with the `blavaan`

package to draw samples from prior distributions. I did the work with the following R code (I omitted the model syntax since that is not the focus of this question).

```
library(blavaan)
fit <- bsem(model=model.syntax, data=dat, n.chains = 2, prisamp = TRUE,
burnin = 2500, sample = 2500)
```

With the `prisamp = TRUE`

argument, I get samples from the prior distributions. Meanwhile, I also specified the number of burn-ins for the sampling. Since the convergence is not the main interest in the prior predictive checks, I considered using `burnin=0`

instead of setting the number of burn-ins.

When I discussed this with Ed (author of the `blavaan`

package), he said it might still be safe to consider the warm-up since the starting values could have some influence on the draws. In this context, I would like to know how Stan actually works in the warm-up phase. Although I am keen on getting samples from the priors, does the Stan warm-up have effects on drawn samples? If any, how much? Furthermore, if it exists, how many burn-ins should be set? I know this indeed depends on the model specifications and data, but I want to get a rough sense of this.

Thanks!

Best,

Ihnwhi