Nicholas Clark

## Package Review *Please check off boxes as applicable, and elaborate in comments below. Your review is not limited to these topics, as described in the reviewer guide* - **Briefly...

> Thank you for your review, @nicholasjclark! I note you used the non-statistical reviewer template. Would you be able to use the statistical one at https://stats-devguide.ropensci.org/pkgreview.html#pkgrev-template? My apologies, it looks...

Need to also update `loo.mvgam` to use posterior predictions rather than the draws generated from Stan. This is better for getting a less biased view of model fit, particularly for...

Thanks @jonathonmellor, yes absolutely. I'm planning to include Binomial and Beta-Binomial. Happy to make that a first priority if it can be useful to you

Hi again @jonathonmellor, I've pushed a new release that brings support for Binomial, Bernoulli and Beta-Binomial. Still working on documentation to show how these work but you can try them...

Thanks @jonathonmellor for the explanation. That does sound interesting and challenging. Would you mind sharing an example of what the data might look like so I can think about whether...

If this goes ahead it'll undoubtedly need the noncentred parameterisation

Hi @A108669, unfortunately this can't be done currently with the `mvgam` interface. However it wouldn't be too difficult to do so by modifying the returned model code and then fitting...

Hi @A108669, sorry about the slow reply. Good to see that you've worked out all the modification and sampling steps. As you have probably notices, `mvgam` uses a rather clunky...