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bmm  

Easy and Accessible Bayesian Measurement Models Using 'brms'
View on CRAN: Click here


Download and install bmm package within the R console
Install from CRAN:
install.packages("bmm")

Install from Github:
library("remotes")
install_github("cran/bmm")

Install by package version:
library("remotes")
install_version("bmm", "1.2.0")



Attach the package and use:
library("bmm")
Maintained by
Vencislav Popov
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-05-27
Latest Update: 2025-07-24
Description:
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>.
How to cite:
Vencislav Popov (2024). bmm: Easy and Accessible Bayesian Measurement Models Using 'brms'. R package version 1.2.0, https://cran.r-project.org/web/packages/bmm. Accessed 21 Aug. 2026.
Previous versions and publish date:
(2026-07-09 07:22), 1.0.1 (2024-05-27 20:10), 1.2.0 (2025-07-24 17:20), 1.3.0 (2026-03-30 13:00)
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Complete documentation for bmm
Functions, R codes and Examples using the bmm R package
Full bmm package functions and examples
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