Interface for ensembles

(I'm not sure where this lives, so I'm putting it here because at least I know the relevant folks will see it and then we can discuss ;).)

I think it might be helpful to have a lightweight class for ensembles of models with weights. Perhaps something that contains a list of models and weights, and implements calls to most of the generic model functions (posterior_predict(), etc; basically the list here: #39) by resampling output from the model list according to those weights.

Unless I've missed something, current approaches to this seem to be duplicated across several packages (loo, brms, marginaleffects, ...); see some discussion on this twitter thread.

The advantage of what I am proposing is that packages that build on top of the generic model functions (#39) would then automatically support ensembles. Currently such packages have to be "ensemble-aware" in a non-generic way; e.g. for ensembles of brms models they have to use brms::pp_average() instead of posterior_predict() / etc.

Not sure where such a class should live (here? rstantools?). I guess this partly depends on if the generic functions from rstantools eventually get moved here per #39.

Thoughts? Pinging @avehtari @paul-buerkner @jgabry.

Start with the generic model functions discussion in issue #39, then compare the ensemble approaches referenced in loo, brms, and marginaleffects. Determine whether the interface belongs in posterior or rstantools and define the model-and-weight behavior and supported functions before implementation; done requires an agreed design and project location.