bmm-package: Easy and Accesible Bayesian Measurement Models Using 'brms'

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

Easy and Accesible Bayesian Measurement Models Using 'brms'

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 (2025) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.3758/s13428-025-02643-0")}.

Author(s)

Maintainer: Vencislav Popov [e-mail] (ORCID) [copyright holder]

Authors:

• Gidon T. Frischkorn [e-mail] (ORCID) [copyright holder]

Other contributors:

• Chenyu Li [contributor]

• Paul-Christian Bürkner [e-mail] (Creator of 'brms', code portions of which are used in 'bmm'.) [copyright holder]

See Also

Useful links:

• https://github.com/venpopov/bmm

• https://venpopov.com/bmm/

• Report bugs at https://github.com/venpopov/bmm/issues

bmm documentation built on June 5, 2026, 9:07 a.m.