Changelog

Source: NEWS.md

ggdist 2.3.0 Unreleased

New features and documentation:

Bug fixes:

  • Support dist aesthetics that are factors (#25)
  • Fix slab drawing order for overlapping (ggridges-style) slabs (#30)
  • Workaround for changes to {distributional} distribution functions until #31 is fixed.

ggdist 2.2.0 2020-07-12

  • Support for distributional, including new examples in vignette("slabinterval") (#14).
  • stat_dist_... geoms now calculate pdf and cdf columns to allow mashup geoms that involve both functions, such as Correll-style gradient plots combined with violins, as in Helske et al. (#11).
  • stat_dist_... geoms should now work with gganimate (#15).
  • Examples updated to fix errors introduced by broom::augment() defaulting to se_fit = FALSE.

ggdist 2.1.1 2020-06-14

  • Initial split from tidybayes: ggdist now contains all stats/geoms from tidybayes (except deprecated ones), all support functions for stats/geoms (such as point_interval()), vignette("slabinterval"), and vignette("freq-uncertainty-vis"). Tidybayes will retain all other functions, and will re-export all ggdist functions for now.
  • All stats and geoms now support automatic orientation determination. Thus, all h-suffix geoms are now deprecated. Those geoms have been left in tidybayes and give a deprecation warning when used; they cannot be used from ggdist directly.
  • geom_interval(), geom_pointinterval(), and geom_lineribbon() no longer automatically set the ymin and ymax aesthetics if .lower or .upper are present in the data. This allows them to work better with automatic orientation detection (and was a bad feature to have existed in the first place anyway). The deprecated tidybayes::geom_intervalh() and tidybayes::geom_pointintervalh() still automatically set those aesthetics, since they are deprecated anyway (so supporting the old behavior is fine in these functions).
  • geom_lineribbon()/stat_lineribbon() now supports a step argument for creating stepped lineribbons. H/T to Solomon Kurz for the suggestion.
  • ggdist now has its own implementation of the scaled and shifted Student’s t distribution (dstudent_t(), qstudent_t(), etc), since it is very useful for visualizing confidence distributions.