Package: bayesplot 1.11.1.9000
Jonah Gabry
bayesplot: Plotting for Bayesian Models
Plotting functions for posterior analysis, MCMC diagnostics, prior and posterior predictive checks, and other visualizations to support the applied Bayesian workflow advocated in Gabry, Simpson, Vehtari, Betancourt, and Gelman (2019) <doi:10.1111/rssa.12378>. 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'.
Authors:
bayesplot_1.11.1.9000.tar.gz
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bayesplot.pdf |bayesplot.html✨
bayesplot/json (API)
NEWS
| # Install 'bayesplot' in R: |
| install.packages('bayesplot', repos = c('https://stan-dev.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/stan-dev/bayesplot/issues
bayesianggplot2mcmcpandocstanstatistical-graphicsvisualization
Last updated 20 days agofrom:ce4f5d1a4f. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Aug 02 2024 |
| R-4.5-win | OK | Aug 02 2024 |
| R-4.5-linux | OK | Aug 02 2024 |
| R-4.4-win | OK | Aug 02 2024 |
| R-4.4-mac | OK | Aug 02 2024 |
| R-4.3-win | OK | Aug 02 2024 |
| R-4.3-mac | OK | Aug 02 2024 |
Exports:abline_01available_mcmcavailable_ppcavailable_ppdbayesplot_gridbayesplot_theme_getbayesplot_theme_replacebayesplot_theme_setbayesplot_theme_updatecolor_scheme_getcolor_scheme_setcolor_scheme_viewexample_group_dataexample_mcmc_drawsexample_x_dataexample_y_dataexample_yrep_drawsfacet_bgfacet_textgrid_lineshline_0hline_atlbublegend_movelegend_nonelegend_textlog_posteriormcmc_acfmcmc_acf_barmcmc_areasmcmc_areas_datamcmc_areas_ridgesmcmc_areas_ridges_datamcmc_combomcmc_densmcmc_dens_chainsmcmc_dens_chains_datamcmc_dens_overlaymcmc_hexmcmc_histmcmc_hist_by_chainmcmc_intervalsmcmc_intervals_datamcmc_neffmcmc_neff_datamcmc_neff_histmcmc_nuts_acceptancemcmc_nuts_divergencemcmc_nuts_energymcmc_nuts_stepsizemcmc_nuts_treedepthmcmc_pairsmcmc_parcoordmcmc_parcoord_datamcmc_rank_ecdfmcmc_rank_histmcmc_rank_overlaymcmc_recover_histmcmc_recover_intervalsmcmc_recover_scattermcmc_rhatmcmc_rhat_datamcmc_rhat_histmcmc_scattermcmc_tracemcmc_trace_datamcmc_trace_highlightmcmc_violinneff_rationuts_paramsoverlay_functionpairs_conditionpairs_style_nppanel_bgparam_glueparam_rangeparcoord_style_npplot_bgpp_checkppc_barsppc_bars_datappc_bars_groupedppc_boxplotppc_datappc_densppc_dens_overlayppc_dens_overlay_groupedppc_ecdf_overlayppc_ecdf_overlay_groupedppc_error_binnedppc_error_datappc_error_histppc_error_hist_groupedppc_error_scatterppc_error_scatter_avgppc_error_scatter_avg_groupedppc_error_scatter_avg_vs_xppc_freqpolyppc_freqpoly_groupedppc_histppc_intervalsppc_intervals_datappc_intervals_groupedppc_km_overlayppc_km_overlay_groupedppc_loo_intervalsppc_loo_pitppc_loo_pit_datappc_loo_pit_overlayppc_loo_pit_qqppc_loo_ribbonppc_pit_ecdfppc_pit_ecdf_groupedppc_ribbonppc_ribbon_datappc_ribbon_groupedppc_rootogramppc_scatterppc_scatter_avgppc_scatter_avg_datappc_scatter_avg_groupedppc_scatter_datappc_statppc_stat_2dppc_stat_datappc_stat_freqpolyppc_stat_freqpoly_groupedppc_stat_groupedppc_violin_groupedppd_boxplotppd_datappd_densppd_dens_overlayppd_ecdf_overlayppd_freqpolyppd_freqpoly_groupedppd_histppd_intervalsppd_intervals_datappd_intervals_groupedppd_ribbonppd_ribbon_datappd_ribbon_groupedppd_statppd_stat_2dppd_stat_datappd_stat_freqpolyppd_stat_freqpoly_groupedppd_stat_groupedrhatscatter_style_nptheme_defaulttrace_style_npvarsvline_0vline_atxaxis_textxaxis_ticksxaxis_titleyaxis_textyaxis_ticksyaxis_title
Dependencies:abindbackportscheckmateclicolorspacedistributionaldplyrfansifarvergenericsggplot2ggridgesgluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmatrixStatsmgcvmunsellnlmenumDerivpillarpkgconfigplyrposteriorR6RColorBrewerRcppreshape2rlangscalesstringistringrtensorAtibbletidyselectutf8vctrsviridisLitewithr
Graphical posterior predictive checks using the bayesplot package
Rendered fromgraphical-ppcs.Rmdusingknitr::rmarkdownon Aug 02 2024.Last update: 2021-01-07
Started: 2017-08-01
Plotting MCMC draws using the bayesplot package
Rendered fromplotting-mcmc-draws.Rmdusingknitr::rmarkdownon Aug 02 2024.Last update: 2022-11-15
Started: 2017-08-01
Visual MCMC diagnostics using the bayesplot package
Rendered fromvisual-mcmc-diagnostics.Rmdusingknitr::rmarkdownon Aug 02 2024.Last update: 2024-01-30
Started: 2017-08-01
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| *bayesplot*: Plotting for Bayesian Models | bayesplot-package bayesplot |
| Get or view the names of available plotting or data functions | available_mcmc available_ppc available_ppd |
| Arrange plots in a grid | bayesplot_grid |
| Get, set, and modify the active *bayesplot* theme | bayesplot_theme_get bayesplot_theme_replace bayesplot_theme_set bayesplot_theme_update |
| Set, get, or view *bayesplot* color schemes | bayesplot-colors color_scheme_get color_scheme_set color_scheme_view |
| Extract quantities needed for plotting from model objects | bayesplot-extractors log_posterior log_posterior.CmdStanMCMC log_posterior.stanfit log_posterior.stanreg neff_ratio neff_ratio.CmdStanMCMC neff_ratio.stanfit neff_ratio.stanreg nuts_params nuts_params.CmdStanMCMC nuts_params.list nuts_params.stanfit nuts_params.stanreg rhat rhat.CmdStanMCMC rhat.stanfit rhat.stanreg |
| Convenience functions for adding or changing plot details | abline_01 bayesplot-helpers facet_bg facet_text grid_lines hline_0 hline_at lbub legend_move legend_none legend_text overlay_function panel_bg plot_bg vline_0 vline_at xaxis_text xaxis_ticks xaxis_title yaxis_text yaxis_ticks yaxis_title |
| Combination plots | MCMC-combos mcmc_combo |
| General MCMC diagnostics | MCMC-diagnostics mcmc_acf mcmc_acf_bar mcmc_neff mcmc_neff_data mcmc_neff_hist mcmc_rhat mcmc_rhat_data mcmc_rhat_hist |
| Histograms and kernel density plots of MCMC draws | MCMC-distributions mcmc_dens mcmc_dens_chains mcmc_dens_chains_data mcmc_dens_overlay mcmc_hist mcmc_hist_by_chain mcmc_violin |
| Plot interval estimates from MCMC draws | MCMC-intervals mcmc_areas mcmc_areas_data mcmc_areas_ridges mcmc_areas_ridges_data mcmc_intervals mcmc_intervals_data |
| Diagnostic plots for the No-U-Turn-Sampler (NUTS) | MCMC-nuts mcmc_nuts_acceptance mcmc_nuts_divergence mcmc_nuts_energy mcmc_nuts_stepsize mcmc_nuts_treedepth NUTS |
| Plots for Markov chain Monte Carlo simulations | MCMC MCMC-overview |
| Parallel coordinates plot of MCMC draws | MCMC-parcoord mcmc_parcoord mcmc_parcoord_data parcoord_style_np |
| Compare MCMC estimates to "true" parameter values | MCMC-recover mcmc_recover_hist mcmc_recover_intervals mcmc_recover_scatter |
| Scatterplots of MCMC draws | MCMC-scatterplots mcmc_hex mcmc_pairs mcmc_scatter pairs_condition pairs_style_np scatter_style_np |
| Trace and rank plots of MCMC draws | MCMC-traces mcmc_rank_ecdf mcmc_rank_hist mcmc_rank_overlay mcmc_trace mcmc_trace_data mcmc_trace_highlight trace_style_np |
| Posterior (or prior) predictive checks (S3 generic and default method) | pp_check pp_check.default |
| PPC censoring | PPC-censoring ppc_km_overlay ppc_km_overlay_grouped |
| PPCs for discrete outcomes | PPC-discrete ppc_bars ppc_bars_data ppc_bars_grouped ppc_rootogram |
| PPC distributions | PPC-distributions ppc_boxplot ppc_data ppc_dens ppc_dens_overlay ppc_dens_overlay_grouped ppc_ecdf_overlay ppc_ecdf_overlay_grouped ppc_freqpoly ppc_freqpoly_grouped ppc_hist ppc_pit_ecdf ppc_pit_ecdf_grouped ppc_violin_grouped |
| PPC errors | PPC-errors ppc_error_binned ppc_error_data ppc_error_hist ppc_error_hist_grouped ppc_error_scatter ppc_error_scatter_avg ppc_error_scatter_avg_grouped ppc_error_scatter_avg_vs_x |
| PPC intervals | PPC-intervals ppc_intervals ppc_intervals_data ppc_intervals_grouped ppc_ribbon ppc_ribbon_data ppc_ribbon_grouped |
| LOO predictive checks | PPC-loo ppc_loo_intervals ppc_loo_pit ppc_loo_pit_data ppc_loo_pit_overlay ppc_loo_pit_qq ppc_loo_ribbon |
| Graphical posterior predictive checking | PPC PPC-overview |
| PPC scatterplots | PPC-scatterplots ppc_scatter ppc_scatter_avg ppc_scatter_avg_data ppc_scatter_avg_grouped ppc_scatter_data |
| PPC test statistics | PPC-statistics PPC-test-statistics ppc_stat ppc_stat_2d ppc_stat_data ppc_stat_freqpoly ppc_stat_freqpoly_grouped ppc_stat_grouped |
| PPD distributions | PPD-distributions ppd_boxplot ppd_data ppd_dens ppd_dens_overlay ppd_ecdf_overlay ppd_freqpoly ppd_freqpoly_grouped ppd_hist |
| PPD intervals | PPD-intervals ppd_intervals ppd_intervals_data ppd_intervals_grouped ppd_ribbon ppd_ribbon_data ppd_ribbon_grouped |
| Plots of posterior or prior predictive distributions | PPD PPD-overview |
| PPD test statistics | PPD-statistics PPD-test-statistics ppd_stat ppd_stat_2d ppd_stat_data ppd_stat_freqpoly ppd_stat_freqpoly_grouped ppd_stat_grouped |
| Default *bayesplot* plotting theme | theme_default |
| Tidy parameter selection | param_glue param_range tidy-params |
