Collection of minor improvements #270
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…a `datafit` (the value of zero is probably correct).
consistent and easier to understand for beginners).
… (and also to enhance comprehensibility).
…tion of the **brms** tests in case of **brms** version <= 2.16.1 can be removed.
…y "submodel size").
consistency with the other `weights()` call which calls `loo::weights.importance_sampling()` in the background).
`psis()` have `loo::` prepended).
…his is basically already `list_cv`.
`cvfits` and `cvfun` are `NULL`. The reason is that `.get_kfold()` already throws such a warning and throwing an error in `init_refmodel()` would mean that a reference model which is never used for K-fold CV would require `cvfits` or `cvfun` nonetheless.
… custom reference model example.
reference models which lack an intercept.
…()` as everywhere else.
…dapt the decision of the final submodel size to the new results.
versions > 1.6.1 don't print the tibble correctly.
…two parts may also be entangled with each other." I'm not sure why I included it. We have `.get_submodels()` always called after `select()`, so the two parts are always separated. Perhaps I was thinking of the `refit_prj = FALSE` case, but that doesn't make sense either.
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These are multiple minor improvements. Sorry that I had to collect them into one PR again, but I couldn't find a sensible other way for submitting these changes (one PR per minor change would certainly have been overkill). I guess you need to check the commits here one-by-one to see if you want to accept them. Details may be found in the commit messages.