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

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install.packages("bayesplot")

1.4.0 by Jonah Gabry, 5 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

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

System requirements: pandoc


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

Depended on by walker.

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


See at CRAN