tidybayes 2.0.2

Various minor forward and backward compatibility fixes:

• Fix stringsAsFactors() issues for R 4
• Fix issues with [[<- for R 4
• Fix minor issues with dplyr 1.0.0
• Use parse() instead of str2lang() for compatibility with R <= 3.6

tidybayes 2.0.1

• Various geoms and stats have been merged together under the geom_slabinterval() and stat_slabinterval() “meta-geom” (#84). This has enabled a bunch of new geoms to be created (see vignette("slabinterval") and fixed a number of outstanding issues:
  • Histogram geoms and histogram+interval geoms (#162)
  • CCDF bar charts and gradient plots
  • The alpha aesthetic can now be mapped on eye plots (and all related geoms) (#163)
  • Vertical version of eye plot (and vertical/horizontal variants of all slabinterval variants) (#56)
  • Intervals and densities are now correctly grouped in eye plots (e.g. when dodging) (#83)
  • Fill and color aesthetics can now be mapped within the slab part of eyes (and all slabintervals), allowing gradients to be made easily (#136) and regions of practical equivalence (ROPEs) to be annotated easily. Examples of ROPEs have been added to the main vignettes (#129).
  • Intervals and eyes support position = "dodge" correctly (#180)
  • The new geoms (and replacements for old ones) have custom scales allowing fine-grained targeting of fill, color, and size aesthetics of all the component parts of the composite geoms.
  • There is a new sub-family of auto-sizing Wilkinson dotplot stats and geoms, geom_dots() and geom_dotsinterval() (#210). These include a quantiles parameter on the stats to make it easy to create quantile dotplots.
• Analytical distributions can be visualized using the new stat_dist_... family of geoms for both the geom_slabinterval() family and geom_lineribbon() (see stat_dist_slabinterval() and stat_dist_lineribbon()).
• The new parse_dist(), which parses distribution specifications (like normal(0,1)) into tidy columns, can be combined with the stat_dist_... family of geoms to easily to visualize priors (e.g. from brms).
• New distribution functions for the marginal LKJ distribution (dlkjcorr_marginal() and company), combined with parse_dist() and the stat_dist_... family make it easy to visualize the marginal LKJ prior on a cell in a correlation matrix. (#191 #192)
• There is a new vignette on frequentist uncertainty visualization, vignette("freq-uncertainty-vis"), also made possible by the new stat_dist_... family of geoms (#188)
• tidy_draws() can now be applied to already-tidied data frames, allowing dependent functions (like spread_draws() and gather_draws()) to also be applied to data frames directly (#82). This can be a useful optimization in workflows where the initial tidying is slow but spreading/gathering is fast (see discussion in #144)
• Kruschke-style distribution-of-distribution plots are now easier to construct with stat_dist_slabh(). An example of this usage is in vignette("tidy-brms").
• hdi() now uses trimmed densities by default to avoid odd behavior with bounded distributions (#165).
• compare_levels(comparison = ) now uses a modern tidy approach to dealing with unevaluated expressions, so rlang::exprs() can be used in place of plyr::.() (#174, #175)
• geom_lineribbon() now works with ggnewscale (#178)
• fitted_draws()/predicted_draws() give more helpful error messages on unsupported models (#177)

tidybayes 1.1.0

New features and documentation:

• Support matrices, n-d arrays, and lists of vectors in compose_data (#159)
• Support nested vectors, matrices, n-d arrays, and ragged arrays through x[.,.] syntax in gather/spread_draws (#154)
• Add detached-line-ribbon HOPs example for ordinal models in brms vignette

Bug fixes:

• Fixed errors on CRAN from changes in brms
• Properly handle Dirichlet responses in predicted_draws (#164)

tidybayes 1.0.4

New features and documentation:

• Initial support for add_residual_draws, towards #133
• Add tidybayes-residuals vignette
• Add add_draws to support models that add_[fitted|predicted]_draws does not (closes #149)
• Add sample_draws to make it easier to take fewer draws anywhere in the pipeline (towards #144)
• Add hypothetical outcome plots (HOPs) to examples

Minor changes:

• Fixed errors on CRAN from changes in dplyr
• Fix bug to support multivariate models in predicted_draws(), closes #134
• Add support for emm_list in gather_emmeans_draws(), closes #126
• Default for show.legend no longer omits all guides
• Make default geom_lineribbon() color black, closes #153

tidybayes 1.0.3

• Added gather_pairs method for creating custom scatterplot matrices (and more!)
• Ordinal models in brms now use original category labels (#122)
• NA values are now better supported in point_interval, and it has an na.rm argument (#123)
• Added sampler diagnostics to tidy_draws() Stan output (#109)
• Added MCMCglmm+emmeans example to vignettes
• Add guards to prevent usage of packages listed in Suggests

tidybayes 1.0.0

Major changes:

• First CRAN release.
• Various function, argument, and column name changes towards unification with the Stan ecosystem. See help(“tidybayes-deprecated”) for more information.