bayestestR: 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 <doi:10.1016/C2012-0-00477-2>) and indices used for null-hypothesis testing (such as ROPE percentage, pd and Bayes factors).

Version: 0.7.5
Depends: R (≥ 3.5)
Imports: insight (≥, methods, stats, utils
Suggests: BayesFactor, bayesQR, bridgesampling, brms, broom, covr, dplyr, effectsize, emmeans, GGally, ggplot2, ggridges, httr, KernSmooth, knitr, MASS, mclust, modelbased, lme4, logspline, mediation, parameters, performance, rmarkdown, rstan, rstanarm, see, stringr, testthat, tidyr, tweedie
Published: 2020-10-22
Author: Dominique Makowski ORCID iD [aut, cre], Daniel Lüdecke ORCID iD [aut], Mattan S. Ben-Shachar ORCID iD [aut], Michael D. Wilson ORCID iD [aut], Paul-Christian Bürkner [rev], Tristan Mahr ORCID iD [rev], Henrik Singmann ORCID iD [ctb], Quentin F. Gronau ORCID iD [ctb], Sam Crawley ORCID iD [ctb]
Maintainer: Dominique Makowski <dom.makowski at>
License: GPL-3
NeedsCompilation: no
Language: en-GB
Citation: bayestestR citation info
Materials: README NEWS
CRAN checks: bayestestR results


Reference manual: bayestestR.pdf
Vignettes: Bayes Factors
Get Started with Bayesian Analysis
Credible Intervals (CI)
Example 1: Initiation to Bayesian models
Example 2: Confirmation of Bayesian skills
Example 3: Become a Bayesian master
Reporting Guidelines
In-Depth 1: Comparison of Point-Estimates
In-Depth 2: Comparison of Indices of Effect Existence
Mediation Analysis using Bayesian Regression Models
Probability of Direction (pd)
Region of Practical Equivalence (ROPE)
Package source: bayestestR_0.7.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: bayestestR_0.7.5.tgz, r-oldrel: bayestestR_0.7.5.tgz
Old sources: bayestestR archive

Reverse dependencies:

Reverse imports: correlation, effectsize, eiCompare, fbst, modelbased, neatStats, parameters, performance, psycho, see, sjPlot, sjstats
Reverse suggests: coveffectsplot, insight


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