Daniel
The more I dive into the DHARMa topic, the more I realize that this approach is quite similar to what we aimed at with `check_predictions()`.
Maybe we can integrate with #574
What is not quite clear to me is the demonstration of the relationship between p and pd? Your introduction ends with > Many of these assumptions can be checked using...
Two questions: - is `check_zeroinflation()` useful / meaningful for `nbinom1` or `genpois`? If yes, we should find a package that computes such distributions (maybe _extraDistr_?) - should the function error...
@bwiernik any suggestions which model families to include/exclude when we speak of "count" models? When should `insight::model_info()$is_count` return `TRUE` or `FALSE`?
fixed in #643
> A more involved implementation would involve us adding a `simulate_residuals()` function that’s a wrapper of `DHARMa::simulateResiduals()`. We would give this function S3 methods for the different model classes we...
I'm not that familiar with the _DHARMa_ package - can we use those functions also for simple models, meaning that we could replace all base R `residuals()` functions with DHARMa...
Considering #367, how can we use DHARMa to plot a zero-inflation or overdispersion check?