Hello:

I have multiple sources available to construct informative priors for a single parameter. I was wondering whether it is logically correct to directly specify multiple priors in Stan model.

I tried specifying multiple priors in Stan and there was no error during the modeling. To check, I ran the model with individual prior 1, prior 2 and both prior 1+prior 2, and the results show that specifying two priors on the same parameter does yield results between those from individually specifying prior 1 and prior 2. Does Stan implicitly do a weighted mixture of multiple priors for the same parameter like 1:1 here?

To be more specific, I have more multiple priors for a parameter of interest (e.g., mean) from different information sources available, and I implemented in Stan as:

```
model {
mu ~ normal(mu0, sigma0) // prior from information source 1
mu ~ uniform(a, b) // prior from information source 2
y ~ normal (mu, sigma) // likelihood
}
```

Could anyone tell me if this is correct to do like this?

Many thanks.