I have run a brms model and would like to take a large number of posterior draws for prediction. The model was trained with 5000 total post-warmup draws, and that appears to be the limit of draws I get with posterior_predict. But the error message it gives suggests that I could take more draws if I allows for replacement. Any guidance on this method or what else would be best to do? Thanks!

```
pp <- posterior_predict(model1, newdata = dataset, seed = 7, ndraws = 30000)
Error in sample.int(length(x), size, replace, prob) :
cannot take a sample larger than the population when 'replace = FALSE'
```

The key thing to keep in mind here is what the `posterior_predict`

function does. For each iteration (draw), it calculates the posterior-implied outcome value (i.e., the value of the outcome implied by the parameter values at the current iteration). For this reason, you cannot request more samples than draws - because there are only a fixed number of iterations with parameter values to use for generating predictions.

The error there is not `brms`

indicating that you can get more draws if you use replacement, that’s an error from one of the internal functions - because `brms`

is assuming that the `ndraws`

value will always be smaller than the number of sampled iterations. I’ll open an issue on the `brms`

github so there should be a more informative error in the future

`brms`

has just updated the error for this case, if you install the github version:

```
if (!requireNamespace("remotes")) {
install.packages("remotes")
}
remotes::install_github("paul-buerkner/brms")
```

It should error more informatively

Thank you for the quick follow-up!