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). References: Makowski et al. (2021) <doi:10.21105/joss.01541>.
insight (>= 1.5.0.6), datawizard (>= 1.3.1), graphics,
methods, stats, utils
BayesFactor (>= 0.9.12-4.4), bayesQR, bayesplot, betareg, BH,
blavaan, bridgesampling (>= 1.2-1), brms, collapse, curl,
effectsize, emmeans, gamm4, ggdist, ggplot2, glmmTMB, httr2,
KernSmooth, knitr, lavaan, lme4, logspline (>= 2.1.21),
marginaleffects (>= 0.29.0), MASS, mclust, mediation,
modelbased, ordbetareg, parameters, patchwork, performance,
posterior, quadprog, RcppEigen, rmarkdown, rstan, rstanarm, see
(>= 0.8.5), testthat, tinytable, tweedie, withr
Dominique Makowski [aut, cre] (ORCID:
    <https://orcid.org/0000-0001-5375-9967>),
  Daniel Lüdecke [aut] (ORCID: <https://orcid.org/0000-0002-8895-3206>),
  Mattan S. Ben-Shachar [aut] (ORCID:
    <https://orcid.org/0000-0002-4287-4801>),
  Indrajeet Patil [aut] (ORCID: <https://orcid.org/0000-0003-1995-6531>),
  Micah K. Wilson [aut] (ORCID: <https://orcid.org/0000-0003-4143-7308>),
  Brenton M. Wiernik [aut] (ORCID:
    <https://orcid.org/0000-0001-9560-6336>),
  Paul-Christian Bürkner [rev],
  Tristan Mahr [rev] (ORCID: <https://orcid.org/0000-0002-8890-5116>),
  Henrik Singmann [ctb] (ORCID: <https://orcid.org/0000-0002-4842-3657>),
  Quentin F. Gronau [ctb] (ORCID:
    <https://orcid.org/0000-0001-5510-6943>),
  Sam Crawley [ctb] (ORCID: <https://orcid.org/0000-0002-7847-0411>)