Existing R packages allow users to easily fit a large variety of models and extract and visualize the posterior draws. However, most of these packages only return a limited set of indices (e.g., point-estimates and CIs). bayestestR provides a comprehensive and consistent set of functions to analyze and describe posterior distributions generated by a variety of models objects, including popular modeling packages such as rstanarm, brms or BayesFactor.
References:
Makowski et al. (2019) tools:::Rd_expr_doi("10.21105/joss.01541")
Makowski et al. (2019) tools:::Rd_expr_doi("10.3389/fpsyg.2019.02767")
Maintainer: Dominique Makowski dom.makowski@gmail.com (ORCID) (@Dom_Makowski)
Authors:
Daniel Lüdecke d.luedecke@uke.de (ORCID) (@strengejacke)
Mattan S. Ben-Shachar matanshm@post.bgu.ac.il (ORCID) (@mattansb)
Indrajeet Patil patilindrajeet.science@gmail.com (ORCID) (@patilindrajeets)
Michael D. Wilson michael.d.wilson@curtin.edu.au (ORCID)
Brenton M. Wiernik brenton@wiernik.org (ORCID) (@bmwiernik)
Other contributors:
Paul-Christian Bürkner paul.buerkner@gmail.com [reviewer]
Tristan Mahr tristan.mahr@wisc.edu (ORCID) [reviewer]
Henrik Singmann singmann@gmail.com (ORCID) [contributor]
Quentin F. Gronau (ORCID) [contributor]
Sam Crawley sam@crawley.nz (ORCID) [contributor]
bayestestR
Useful links: