I’m trying to familiarize myself with the projection predictive approach and projpred package, and thinking about implementing projpred methods for particular custom model class. However, the documentation on how to do this is somewhat sparse, scattered, and perhaps outdated (init_refmodel example with custom model · Issue #125 · stan-dev/projpred · GitHub). Any suggestions on how to decipher the minimal structure for this, or should I just try to mimic the implementations for brsm and/or rstanarm fits? Or are there cases where it could be more reasonable to just implement the whole method from scratch for specific model types according to the source literature? The models I am thinking are essentially constrained linear regression models.
Tagging @fweber144@avehtari as they seem to be actively working on Github on projpred and also present here.
The documentation for the use of the latent projection with custom families is pretty comprehensive and has a nice worked example for the negative binomial.