tidybayes: Tidy Data and Geoms for Bayesian Models

Breaking changes and deprecations:

• The [add_]XXX_draws() (predicted_draws(), add_predicted_draws(), etc) functions have been substantially restructured:
  • add_fitted_draws() and fitted_draws() are now deprecated, along with the scale argument. Several years' teaching experience has demonstrated that "fitted" is a very confusing name for students. Use the more-specific [add_]linpred_draws() if you want draws from the linear predictor or the new [add_]epred_draws() if you want draws from the expectation of the posterior predictive (which is what fitted_draws() was most typically used for).
  • Arguments for renaming output columns are now all called value, but retain function-specific default column names. E.g. the prediction argument for predicted_draws() is now spelled value but has a default of ".prediction". One breaking change is that the default output column for linpred_draws() is now ".linpred" instead of ".value". This should make it easier to combine outputs across multiple functions while also making it easier to remember the name of the argument that changes the output column name.
  • The n argument is now spelled ndraws to be more consistent with terminology in the posterior package and to prevent partial argument name matching bugs with newdata.
  • The first argument to all of these functions is now object instead of model, in order to match with argument names in posterior_predict(), etc. This was necessary to prevent partial argument name matching bugs with certain model types in rstanarm that have an m argument to their prediction functions.

New features:

• Support for the new posterior package:
  • Several new _rvars counterparts to the _draws family of functions, including spread_rvars(), gather_rvars(), epred_rvars(), linpred_rvars(), and predicted_rvars(), which add columns of posterior::rvar() objects to data frames instead of long-format columns of draws. These can be easier to read and take up less memory than the long-format data frames of draws. See vignette("tidy-posterior") for examples.
  • The nest_rvars() and unnest_rvars() functions for converting between data frames of rvars and long format data frames of draws.
  • tidy_draws() has been rebuilt on top of posterior::as_draws_df(), which means it should support even more model types and benefit from efficiency improvements in posterior. This means that cmdstanr is now supported, for example.
  • An implementation of posterior::summarise_draws() for grouped data frames of draws: summarise_draws.grouped_df()
  • compare_levels() now supports data frames of posterior::rvar()s.
• The epred_draws(), linpred_draws(), and predicted_draws() functions should now support any models that implement posterior_epred(), posterior_linpred(), and posterior_predict() so long as they take a newdata argument.
• Several dependencies have been removed or demoted to Suggests, including forcats, plyr, and purrr.
• Added the option to set the seed when subsampling to several functions (#276).

New documentation:

• vignette("tidy-posterior") describing the use of tidybayes with posterior, and particularly the posterior::rvar() data type. This vignette also includes an updated version of the ordinal regression example from vignette("tidy-brms"), now with an illustration of the relationship between the latent linear predictor and the category-level probabilities.

Bug fixes:

• Omit sampler parameters in tidy_draws() if retrieving them results in an error (#244)