bmm: Easy and Accessible Bayesian Measurement Models Using 'brms'

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 ORCID iD [aut, cre, cph], Gidon T. Frischkorn ORCID iD [aut, cph], Paul-Christian B├╝rkner [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

Documentation:

Reference manual: bmm.pdf

Downloads:

Package source: bmm_1.0.1.tar.gz
Windows binaries: r-devel: bmm_1.0.1.zip, r-release: bmm_1.0.1.zip, r-oldrel: bmm_1.0.1.zip
macOS binaries: r-release (arm64): bmm_1.0.1.tgz, r-oldrel (arm64): bmm_1.0.1.tgz, r-release (x86_64): bmm_1.0.1.tgz, r-oldrel (x86_64): bmm_1.0.1.tgz

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