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, 2014 ) and indices used for null-hypothesis testing (such as ROPE percentage and pd).


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Reference manual

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install.packages("bayestestR")

0.1.0 by Dominique Makowski, 10 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]


Documentation:   PDF Manual  


GPL-3 license


Imports insight

Depends on stats

Suggests brms, broom, covr, dplyr, tidyr, ggplot2, ggridges, knitr, rmarkdown, rstanarm, stringr, testthat


See at CRAN