bayestestR (0.5.3)

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).

Maintainer: Dominique Makowski
Author(s): Dominique Makowski [aut, cre] (<>), Daniel Ldecke [aut] (<>), Mattan S. Ben-Shachar [aut] (<>), Michael D. Wilson [aut] (<>), Paul-Christian Brkner [rev], Tristan Mahr [rev] (<>), Henrik Singmann [ctb] (<>), Quentin F. Gronau [ctb] (<>)

License: GPL-3

Uses: insight, KernSmooth, ggplot2, lme4, logspline, mclust, tweedie, MASS, stringr, testthat, GGally, knitr, BayesFactor, dplyr, tidyr, rmarkdown, broom, brms, covr, rstan, rstanarm, bridgesampling, ggridges, emmeans, performance, see, modelbased
Reverse suggests: coveffectsplot, insight, see

Released 11 days ago.