Functions for carrying out a wide variety of graphical model checks based on comparing observed data to draws from the posterior predictive distribution.

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


Posterior predictive checks (S3 generic and default method)


Functions for creating plots of MCMC draws of model parameters and general MCMC diagnostics.

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()

Trace plot (time series plot) of MCMC draws


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)


Functions for setting color schemes, customizing various plot features, and arranging multiple plots.

color_scheme_set() color_scheme_get() color_scheme_view()

Set, get, or view color schemes


Arrange plots in a grid


Default bayesplot plotting theme

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


Functions for extracting various quantities needed for plotting from model objects, generating data for examples, and listing available plotting functions.

log_posterior() nuts_params() rhat() neff_ratio()

Extract quantities needed for plotting from model objects

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