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).
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]
,
Sam Crawley [ctb]