bayesplot v1.5.0

bayesplot v1.5.0 is now on CRAN.
See release notes below or at mc-stan.org/bayesplot/news.

Installation

After CRAN binaries are built (usually a few days) just use install.packages("bayesplot"). Before binaries are available the update can be installed from CRAN using

install.packages("bayesplot", type = "source", repos = "https://cran.rstudio.com/")

or from GitHub using

# note: setting build_vignettes=FALSE will be much faster and you can always access 
# the vignettes at mc-stan.org/bayesplot/articles/

devtools::install_github("stan-dev/bayesplot", ref = "v1.5.0", build_vignettes = TRUE) 

Release notes

(GitHub issue/PR numbers in parentheses)

• New package documentation website: http://mc-stan.org/bayesplot/

• Two new plots that visualize posterior density using ridgelines (ggridges pkg). These work well when parameters have similar values and similar densities, as in hierarchical models. (#104)

  • mcmc_dens_chains() draws the kernel density of each sampling chain.
  • mcmc_areas_ridges() draws the kernel density combined across chains.
  • Both functions have a corresponding _data() function to return the data plotted by
    each function.

• mcmc_intervals() and mcmc_areas() have been rewritten. (#103)

  • They now use a discrete y-axis. Previously, they used a continuous
    scale with numeric breaks relabelled with parameter names; this design
    caused some unexpected behavior when customizing these plots.
  • mcmc_areas() now uses geoms from the ggridges package to draw density
    curves.

• Added mcmc_intervals_data() and mcmc_areas_data() that return data
  plotted by mcmc_intervals() and mcmc_areas(). Similarly, ppc_data()
  returns data plotted ppc_hist() and other ppc plot. (Advances #97)

• Added ppc_loo_pit_overlay() function for a better LOO PIT predictive check.
  (#123)

• Started using vdiffr to add visual unit tests to the existing PPC unit tests. (#137)