Function reference • bayesplot

Aesthetics Functions for setting the color scheme and ggplot theme used by bayesplot. (Also see the separate ggplot helpers section below.)
`color_scheme_set()` `color_scheme_get()` `color_scheme_view()`	Set, get, or view bayesplot color schemes
`bayesplot_theme_get()` `bayesplot_theme_set()` `bayesplot_theme_update()` `bayesplot_theme_replace()`	Get, set, and modify the active bayesplot theme
`theme_default()`	Default bayesplot plotting theme
PPC Functions for carrying out a wide variety of graphical model checks based on comparing observed data to draws from the posterior (or prior) predictive distribution.
`PPC-overview`	Graphical posterior predictive checking
`ppc_bars()` `ppc_bars_grouped()` `ppc_rootogram()`	PPCs for discrete outcomes
`ppc_data()` `ppc_hist()` `ppc_boxplot()` `ppc_freqpoly()` `ppc_freqpoly_grouped()` `ppc_dens()` `ppc_dens_overlay()` `ppc_ecdf_overlay()` `ppc_violin_grouped()`	PPC distributions
`ppc_error_hist()` `ppc_error_hist_grouped()` `ppc_error_scatter()` `ppc_error_scatter_avg()` `ppc_error_scatter_avg_vs_x()` `ppc_error_binned()`	PPC errors
`ppc_intervals()` `ppc_intervals_grouped()` `ppc_ribbon()` `ppc_ribbon_grouped()` `ppc_intervals_data()` `ppc_ribbon_data()`	PPC intervals
`ppc_loo_pit_overlay()` `ppc_loo_pit_qq()` `ppc_loo_pit()` `ppc_loo_intervals()` `ppc_loo_ribbon()`	LOO predictive checks
`ppc_scatter()` `ppc_scatter_avg()` `ppc_scatter_avg_grouped()`	PPC scatterplots
`ppc_stat()` `ppc_stat_grouped()` `ppc_stat_freqpoly_grouped()` `ppc_stat_2d()`	PPC test statistics
`pp_check()`	Posterior (or prior) predictive checks (S3 generic and default method)
MCMC Functions for creating plots of MCMC draws of model parameters and general MCMC diagnostics.
`MCMC-overview`	Plots for Markov chain Monte Carlo simulations
`mcmc_rhat()` `mcmc_rhat_hist()` `mcmc_rhat_data()` `mcmc_neff()` `mcmc_neff_hist()` `mcmc_neff_data()` `mcmc_acf()` `mcmc_acf_bar()`	General MCMC diagnostics
`mcmc_hist()` `mcmc_dens()` `mcmc_hist_by_chain()` `mcmc_dens_overlay()` `mcmc_dens_chains()` `mcmc_dens_chains_data()` `mcmc_violin()`	Histograms and kernel density plots of MCMC draws
`mcmc_intervals()` `mcmc_areas()` `mcmc_areas_ridges()` `mcmc_intervals_data()` `mcmc_areas_data()` `mcmc_areas_ridges_data()`	Plot interval estimates from MCMC draws
`mcmc_recover_intervals()` `mcmc_recover_scatter()` `mcmc_recover_hist()`	Compare MCMC estimates to "true" parameter values
`mcmc_scatter()` `mcmc_hex()` `mcmc_pairs()` `scatter_style_np()` `pairs_style_np()` `pairs_condition()`	Scatterplots of MCMC draws
`mcmc_parcoord()` `mcmc_parcoord_data()` `parcoord_style_np()`	Parallel coordinates plot of MCMC draws
`mcmc_trace()` `mcmc_trace_highlight()` `trace_style_np()` `mcmc_rank_overlay()` `mcmc_rank_hist()` `mcmc_trace_data()`	Trace plots of MCMC draws
`mcmc_combo()`	Combination plots
HMC/NUTS diagnostics Functions for plotting diagnostics specific to Hamiltonian Monte Carlo (HMC) and the No-U-Turn Sampler (NUTS). Some of the general MCMC plotting functions (`mcmc_parcoord()`, `mcmc_pairs()`, `mcmc_scatter()`, `mcmc_trace()`) can also show HMC/NUTS diagnostic information if optional arguments are specified, but the special functions below are only intended for use with HMC/NUTS.
`mcmc_nuts_acceptance()` `mcmc_nuts_divergence()` `mcmc_nuts_stepsize()` `mcmc_nuts_treedepth()` `mcmc_nuts_energy()`	Diagnostic plots for the No-U-Turn-Sampler (NUTS)
Tidy parameter selection for MCMC plots Helper functions for tidy parameter selection and examples of using bayesplot with dplyr.
`param_range()` `param_glue()`	Tidy parameter selection
ggplot helpers Convenience functions for arranging multiple plots, adding features to plots, and shortcuts for modifying individual ggplot theme elements.
`bayesplot_grid()`	Arrange plots in a grid
`vline_at()` `hline_at()` `vline_0()` `hline_0()` `abline_01()` `lbub()` `legend_move()` `legend_none()` `legend_text()` `xaxis_title()` `xaxis_text()` `xaxis_ticks()` `yaxis_title()` `yaxis_text()` `yaxis_ticks()` `facet_text()` `facet_bg()` `panel_bg()` `plot_bg()` `grid_lines()` `overlay_function()`	Convenience functions for adding or changing plot details
Extractors Functions extracting various quantities needed for plotting from different types of fitted model objects.
`log_posterior()` `nuts_params()` `rhat()` `neff_ratio()`	Extract quantities needed for plotting from model objects
Miscellaneous Functions for generating data for examples and listing available plotting functions.
`example_mcmc_draws()` `example_yrep_draws()` `example_y_data()` `example_x_data()` `example_group_data()`	Example draws to use in demonstrations and tests
`available_ppc()` `available_mcmc()`	Get or view the names of available plotting functions

Reference

Aesthetics

PPC

MCMC

HMC/NUTS diagnostics

Tidy parameter selection for MCMC plots

ggplot helpers

Extractors

Miscellaneous