Plotting for Bayesian Models

Plotting functions for posterior analysis, model checking, and MCMC diagnostics. The package is designed not only to provide convenient functionality for users, but also a common set of functions that can be easily used by developers working on a variety of R packages for Bayesian modeling, particularly (but not exclusively) packages interfacing with 'Stan'.


News

bayesplot 1.4.0

(GitHub issue/PR numbers in parentheses)

  • New plotting function mcmc_parcoord() for parallel coordinates plots of MCMC draws (optionally including HMC/NUTS diagnostic information). (#108)
  • mcmc_scatter gains an np argument for specifying NUTS parameters, which allows highlighting divergences in the plot. (#112)
  • New functions with names ending with suffix _data don't make the plots, they just return the data prepared for plotting (more of these to come in future releases):
    • ppc_intervals_data() (#101)
    • ppc_ribbon_data() (#101)
    • mcmc_parcoord_data() (#108)
    • mcmc_rhat_data() (#110)
    • mcmc_neff_data() (#110)
  • ppc_stat_grouped(), ppc_stat_freqpoly_grouped() gain a facet_args argument for controlling ggplot2 faceting (many of the mcmc_ functions already have this).
  • The divergences argument to mcmc_trace() has been deprecated in favor of np (NUTS parameters) to match the other functions that have an np argument.
  • Fixed an issue where duplicated rhat values would break mcmc_rhat() (#105).

bayesplot 1.3.0

(GitHub issue/PR numbers in parentheses)

  • bayesplot::theme_default is now set as the default ggplot2 plotting theme when bayesplot is loaded, which makes changing the default theme using ggplot2::theme_set possible. Thanks to @gavinsimpson. (#87)
  • 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 1.2.0

(GitHub issue/PR numbers in parentheses)

A lot of new stuff in this release:

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 1.1.0

(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 in existing functions

  • 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)
  • The stat argument for all ppc_stat_* functions now accepts a function instead of only the name of a function. (#31)

New functions

  • ppc_error_hist_grouped for plotting predictive errors by level of a grouping variable. (#40)
  • mcmc_recover_intervals for comparing MCMC estimates to "true" parameter values used to simulate the data. (#56)
  • bayesplot_grid for juxtaposing plots and enforcing shared axis limits. (#59)

bayesplot 1.0.0

  • Initial CRAN release

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("bayesplot")

1.5.0 by Jonah Gabry, 2 months ago


http://mc-stan.org/bayesplot


Report a bug at https://github.com/stan-dev/bayesplot/issues/


Browse source code at https://github.com/cran/bayesplot


Authors: Jonah Gabry [aut, cre], Tristan Mahr [aut], Paul-Christian Buerkner [ctb]


Documentation:   PDF Manual  


GPL (>= 3) license


Imports dplyr, ggplot2, reshape2, stats, utils, rlang, ggridges

Suggests arm, gridExtra, knitr, loo, rmarkdown, rstan, rstanarm, rstantools, scales, shinystan, testthat, vdiffr

System requirements: pandoc


Imported by MixSIAR, RBesT, bang, brms, idealstan, nauf, revdbayes, rstanarm, shinystan, sjstats.

Depended on by walker.

Suggested by CopulaDTA, breathteststan, bssm, emmeans, greta, loo, projpred, rstan, rstantools.


See at CRAN