bayesplot v1.3.0

Release notes

(GitHub issue/PR numbers in parentheses)

The biggest change is:

• bayesplot::theme_default is now set as the default ggplot2 plotting theme
  when bayesplot is loaded instead of hardcoded for each plot. This makes
  changing the default theme using ggplot2::theme_set possible.
  Thanks to @gavinsimpson. (#87)

Some minor changes:

• mcmc_hist and mcmc_hist_by_chain now take a freq argument that defaults
  to TRUE (behavior is like freq argument to R's hist function).
• Using a ts object for y in PPC plots no longer results in an error. Thanks
  to @helske. (#94)
• mcmc_intervals doesn't use round lineends anymore as they slightly
  exaggerate the width of the intervals. Thanks to @tjmahr. (#96)

bayesplot v1.2.0

bayesplot v1.2.0 is now on CRAN and can be installed with install.packages("bayesplot").
There is a lot of new stuff in this release!

Release notes

(GitHub issue/PR numbers in parentheses)

Fixes

• Avoid error in some cases when divergences is specified in call to
  mcmc_trace but there are not actually any divergent transitions.
• The merge_chains argument to mcmc_nuts_energy now defaults to FALSE.

New features in existing functions

• For mcmc_* functions, transformations are recycled if transformations
  argument is specified as a single function rather than a named list. Thanks to @tklebel. (#64)
• For ppc_violin_grouped there is now the option of showing y as a violin,
  points, or both. Thanks to @silberzwiebel. (#74)
• color_scheme_get now has an optional argument i for selecting only a
  subset of the colors.
• New color schemes: darkgray, orange, viridis, viridisA, viridisB, viridisC.
  The viridis schemes are better than the other schemes for trace plots (the
  colors are very distinct from each other).

New functions

• mcmc_pairs, which is essentially a ggplot2+grid implementation of rstan's
  pairs.stanfit method. (#67)
• mcmc_hex, which is similar to mcmc_scatter but using geom_hex instead of
  geom_point. This can be used to avoid overplotting. (#67)
• overlay_function convenience function. Example usage: add a Gaussian (or any
  distribution) density curve to a plot made with mcmc_hist.
• mcmc_recover_scatter and mcmc_recover_hist, which are similar to mcmc_recover_intervals and compare estimates to "true" values used to simulate data. (#81, #83)
• New PPC category Discrete with functions:
  • ppc_rootogram for use with models for count data. Thanks to @paul-buerkner. (#28)
  • ppc_bars, ppc_bars_grouped for use with models for ordinal, categorical
    and multinomial data. Thanks to @silberzwiebel. (#73)
• New PPC category LOO (thanks to suggestions from @avehtari) with functions:
  • ppc_loo_pit for assessing the calibration of marginal predictions. (#72)
  • ppc_loo_intervals, ppc_loo_ribbon for plotting intervals of the LOO predictive distribution. (#72)

bayesplot v1.1.0

bayesplot v1.1.0 is now on CRAN and can be installed using install.packages("bayesplot").

Release notes

(GitHub issue/PR numbers in parentheses)

Fixes

• Images in vignettes should now render properly using png device. Thanks to
  TJ Mahr. (#51)
• xaxis_title(FALSE) and yaxis_title(FALSE) now set axis titles to NULL
  rather than changing theme elements to element_blank(). This makes it easier
  to add axis titles to plots that don’t have them by default. Thanks to Bill
  Harris. (#53)

New Features

• Introduce ppc_error_hist_grouped for plotting predictive errors
  by level of a grouping variable. (#40)
• Introduce mcmc_recover_intervals for comparing MCMC estimates to "true"
  parameter values used to simulate the data. (#56)
• Add argument divergences to mcmc_trace function. For models fit using
  HMC/NUTS this can be used to display divergences as a rug at the bottom of the
  trace plot. (#42)
• Introduce bayesplot_grid function for juxtaposing plots and enforcing shared
  axis limits. (#59)
• The stat argument for all ppc_stat_* functions now accepts a function
  instead of only the name of a function. (#31)

Initial CRAN release

Update README.md

[ci skip]

Beta Release

To install this beta release of the bayespot package you will also need the preview version of the
upcoming ggplot2 update (not the CRAN version):

if (!require("devtools"))
  install.packages("devtools")

devtools::install_github("hadley/ggplot2")
devtools::install_github("stan-dev/bayesplot", build_vignettes = TRUE)