Fit computational and measurement models using full Bayesian
inference. The package provides a simple and accessible interface by
translating complex domain-specific models into 'brms' syntax, a
powerful and flexible framework for fitting Bayesian regression models
using 'Stan'. The package is designed so that users can easily apply
state-of-the-art models in various research fields, and so that
researchers can use it as a new model development framework.
References: Frischkorn and Popov (2023) <doi:10.31234/osf.io/umt57>.
Version: |
1.0.1 |
Depends: |
R (≥ 3.6.0) |
Imports: |
brms (≥ 2.21.0), crayon, dplyr, fs, glue, magrittr, matrixStats, methods, parallel, stats, tidyr, withr |
Suggests: |
bookdown, cmdstanr (≥ 0.7.0), cowplot, fansi, ggplot2, ggthemes, knitr, mixtur, remotes, rmarkdown, stringr, testthat (≥ 3.0.0), tidybayes, usethis, waldo |
Published: |
2024-05-27 |
DOI: |
10.32614/CRAN.package.bmm |
Author: |
Vencislav Popov
[aut, cre, cph],
Gidon T. Frischkorn
[aut, cph],
Paul-Christian Bürkner [cph] (Creator of 'brms', code portions of which
are used in 'bmm'.) |
Maintainer: |
Vencislav Popov <vencislav.popov at gmail.com> |
BugReports: |
https://github.com/venpopov/bmm/issues |
License: |
GPL-2 |
URL: |
https://github.com/venpopov/bmm, https://venpopov.github.io/bmm/ |
NeedsCompilation: |
no |
Additional_repositories: |
https://mc-stan.org/r-packages/ |
Citation: |
bmm citation info |
Materials: |
README NEWS |
CRAN checks: |
bmm results |