bayesplot v1.9.0

Lots of new features in this release!

• New module PPD (posterior/prior predictive distribution) with a lot of new
  plotting functions with ppd_ prefix. These functions plot draws from the prior
  or posterior predictive distributions (PPD) without comparing to observed data
  (i.e., no y argument). Because these are not "checks" against the observed
  data we use PPD instead of PPC. These plots are essentially the same as the
  corresponding PPC plots but without showing any observed data (e.g.,
  ppd_intervals() is like ppc_intervals() but without plotting y). See
  help("PPD-overview") for details. (#151, #222)

• All PPC categories now have one or more _data() functions that return the
  data frame used for plotting (#97, #222). Many of these have already been in
  previous releases, but the new ones in this release are:

  • ppc_bars_data()
  • ppc_error_data()
  • ppc_error_binnned_data()
  • ppc_scatter_data()
  • ppc_scatter_avg_data()
  • ppc_stat_data()

• Many functions gain an argument facet_args for controlling ggplot2 faceting
  (many other functions have had this argument for a long time).
  The ones that just now got the argument are:

  • ppc_scatter()
  • ppc_scatter_avg_grouped()
  • ppc_error_hist()
  • ppc_error_hist_grouped()
  • ppc_error_scatter()
  • ppc_error_binned()

• New plotting function ppc_km_overlay_grouped(), the grouped variant of
  ppc_km_overlay(). (#260, @fweber144)

• ppc_scatter(), ppc_scatter_avg(), and ppc_scatter_avg_grouped() gain an
  argument ref_line, which can be set to FALSE to turn off the x=y line
  drawn behind the scatterplot.

• ppc_ribbon() and ppc_ribbon_grouped() gain argument y_draw that specifies whether the observed y should be plotted using a point, line, or both. (#257, @charlesm93)

• mcmc_*() functions now support all draws formats from the posterior package. (#277, @Ozan147)

• mcmc_dens() and mcmc_dens_overlay() gain arguments for controlling the
  the density calculation. (#258)

• mcmc_hist() and mcmc_dens() gain argument alpha for controlling transparency. (#244)

• mcmc_areas() and mcmc_areas_ridges() gain an argument border_size for
  controlling the thickness of the ridgelines. (#224)