ggdist: Visualizations of distributions and uncertainty

Breaking changes: The positioning of geom_slabinterval() family geoms when using position_dodge() is now slightly different in order to match up with how other geoms are positioned (#85). This may slightly change existing charts that use position = "dodge", and in some cases may cause slabs to be drawn slightly outside plot boundaries, but makes it much easier to combine geom_slabinterval() with other geoms in the expected way. If dodging more similar to the old approach is needed, use the new "justification-preserving dodge", position_dodgejust(), in place of position_dodge(). New features: For geom_slabinterval(), side, justification, and scale can now be used as aesthetics instead of parameters, allowing them to vary across slabs within the same geom. Varying fills within a slab in geom_slabinterval() can now be drawn as true gradients rather than segmented polygons in R >= 4.1 by setting fill_type = "gradient". This substantially improves the appearance of gradient fills in graphics engines that support it (#44). Improved support for discrete distributions: stat_dist_slabinterval() and company now detect discrete distributions and display them as histograms (#19). geom_dotsinterval() now adjusts bin widths on discrete distributions when they would result in bins that are taller than the allocated space to ensure that they fit within the required space (#42). Allow user-specified lower and/or upper bounds on dynamic geom_dotsinterval() bin width by passing a vector of two values to the binwidth parameter. The automatic bin selection algorithm used by geom_dotsinterval() has been factored out and exported as find_dotplot_binwidth() and bin_dots() for others to use (#77). Previously, curve_interval() used a common (but naive) approach to finding a cutoff on data depth to identify the X% "deepest" curves, simply taking the envelope around the X% quantile of curves ranked by depth. This is quite conservative and tends to create intervals that are too wide; curve_interval() now searches for a cutoff in data depth such that X% of curves are contained within its envelope (#67). point_interval() and company now accept distributional objects and posterior::rvar()s (full support for distributional objects requires distributional > 0.2.2). Reduce dependencies substantially, making the geoms more suitable for use by other packages (thanks to Brenton Wiernik for the help). New documentation: Substantial improvements to the documentation of aesthetics and computed variables in geom_slabinterval(), stat_slabinterval(), and company, listing all custom aesthetics, computed variables, and their usage. Several new examples in vignette("slabinterval"), including "rain cloud" plots and an example of histograms for discrete analytical distributions. Bug fixes: Ensure stat_dist_slabinterval() preserves group order (#88). Improve test coverage up to ~96%. Restore computed variable n for stat_sample_slabinterval(). Various improvements in correct NA handling across the geoms (#74, #51)