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).


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("bayestestR")

0.2.2 by Dominique Makowski, 4 days 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 L├╝decke [aut] , Mattan S. Ben-Shachar [aut] , Michael D. Wilson [aut]


Documentation:   PDF Manual  


GPL-3 license


Imports insight

Depends on stats, methods, utils

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


Imported by performance, see, sjPlot, sjstats.


See at CRAN