Published January 28, 2020
| Version v2.0.1
Software
Open
tidybayes: Tidy Data and Geoms for Bayesian Models
Description
- Various geoms and stats have been merged together under the
geom_slabinterval()
andstat_slabinterval()
"meta-geom" (#84). This has enabled a bunch of new geoms to be created (seevignette("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()
andgeom_dotsinterval()
(#210). These include aquantiles
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 thegeom_slabinterval()
family andgeom_lineribbon()
(seestat_dist_slabinterval()
andstat_dist_lineribbon()
). - The new
parse_dist()
, which parses distribution specifications (likenormal(0,1)
) into tidy columns, can be combined with thestat_dist_...
family of geoms to easily to visualize priors (e.g. frombrms
). - New distribution functions for the marginal LKJ distribution (
dlkjcorr_marginal()
and company), combined withparse_dist()
and thestat_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 newstat_dist_...
family of geoms (#188) tidy_draws()
can now be applied to already-tidied data frames, allowing dependent functions (likespread_draws()
andgather_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 invignette("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, sorlang::exprs()
can be used in place ofplyr::.()
(#174, #175)geom_lineribbon()
now works withggnewscale
(#178)fitted_draws()
/predicted_draws()
give more helpful error messages on unsupported models (#177)
Files
mjskay/tidybayes-v2.0.1.zip
Files
(36.8 MB)
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Additional details
Related works
- Is supplement to
- https://github.com/mjskay/tidybayes/tree/v2.0.1 (URL)