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).


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Reference manual

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install.packages("bayestestR")

0.4.0 by Dominique Makowski, 2 months ago


https://github.com/easystats/bayestestR


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


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


Authors: Dominique Makowski [aut, cre] , Daniel Lüdecke [aut] , Mattan S. Ben-Shachar [aut] , Michael D. Wilson [aut] , Paul-Christian Bürkner [rev] , Tristan Mahr [rev] , Henrik Singmann [ctb] , Quentin F. Gronau [ctb]


Documentation:   PDF Manual  


GPL-3 license


Imports insight, methods, stats, utils

Suggests BayesFactor, bridgesampling, brms, broom, covr, dplyr, emmeans, GGally, ggplot2, ggridges, KernSmooth, knitr, MASS, mclust, lme4, logspline, performance, rmarkdown, rstan, rstanarm, see, stringr, testthat, tidyr


Imported by effectsize, parameters, performance, see, sjPlot, sjstats.

Suggested by insight.


See at CRAN