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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:1.2.0
Depends:R (≥ 3.6.0)
Imports:brms (≥ 2.21.0),crayon,fs,glue,matrixStats, methods, parallel, stats,withr
Suggests:bookdown, cmdstanr (≥ 0.7.0),cowplot,dplyr,fansi,ggplot2,ggthemes,knitr,magrittr,mixtur,remotes,rmarkdown,stringr,testthat (≥ 3.0.0),tidybayes,tidyr,usethis,waldo, gghalves
Published:2025-07-24
DOI:10.32614/CRAN.package.bmm
Author:Vencislav PopovORCID iD [aut, cre, cph], Gidon T. FrischkornORCID iD [aut, cph], Chenyu Li [ctb], 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://stan-dev.r-universe.dev
Citation:bmm citation info
Materials:README,NEWS
CRAN checks:bmm results

Documentation:

Reference manual:bmm.html ,bmm.pdf

Downloads:

Package source: bmm_1.2.0.tar.gz
Windows binaries: r-devel:bmm_1.2.0.zip, r-release:bmm_1.2.0.zip, r-oldrel:bmm_1.2.0.zip
macOS binaries: r-release (arm64):bmm_1.2.0.tgz, r-oldrel (arm64):bmm_1.2.0.tgz, r-release (x86_64):bmm_1.2.0.tgz, r-oldrel (x86_64):bmm_1.2.0.tgz
Old sources: bmm archive

Linking:

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