bmm: Easy and Accessible Bayesian Measurement Models Using 'brms' (original) (raw)
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 |
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