Understand and Describe Bayesian Models and Posterior Distributions

Provides utilities to describe posterior distributions and Bayesian models. It includes point-estimates such as Maximum A Posteriori (MAP), measures of dispersion (Highest Density Interval - HDI; Kruschke, 2015 ) and indices used for null-hypothesis testing (such as ROPE percentage, pd and Bayes factors).


Reference manual

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0.11.0 by Dominique Makowski, 2 months ago


Report a bug at https://github.com/easystats/bayestestR/issues

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

Authors: Dominique Makowski [aut, cre] , @Dom_Makowski) , Daniel Lüdecke [aut] , @strengejacke) , Mattan S. Ben-Shachar [aut] , @mattansb) , Indrajeet Patil [aut] , @patilindrajeets) , Michael D. Wilson [aut] , Brenton M. Wiernik [aut] , @bmwiernik) , Paul-Christian Bürkner [rev] , Tristan Mahr [rev] , Henrik Singmann [ctb] , Quentin F. Gronau [ctb] , Sam Crawley [ctb]

Documentation:   PDF Manual  

Task views: Bayesian Inference

GPL-3 license

Imports insight, datawizard, methods, stats, utils

Suggests BayesFactor, bayesQR, blavaan, bridgesampling, brms, dplyr, effectsize, emmeans, GGally, ggdist, ggplot2, ggridges, httr, KernSmooth, knitr, lavaan, lme4, logspline, MASS, mclust, mediation, modelbased, parameters, performance, rmarkdown, rstan, rstanarm, see, spelling, stringr, testthat, tidyr, tweedie

Imported by correlation, effectsize, eiCompare, fbst, modelbased, multifear, neatStats, parameters, performance, psycho, report, see, sjPlot, sjstats.

Suggested by coveffectsplot, datawizard, emmeans, insight.

See at CRAN