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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "bmm" in publications use:'
type: software
license: GPL-2.0-only
title: 'bmm: Easy and Accessible Bayesian Measurement Models Using ''brms'''
version: 1.0.0
doi: 10.31234/osf.io/umt57
identifiers:
- type: doi
  value: 10.32614/CRAN.package.bmm
abstract: 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.
authors:
- family-names: Popov
  given-names: Vencislav
  email: vencislav.popov@gmail.com
  orcid: https://orcid.org/0000-0002-8073-4199
- family-names: Frischkorn
  given-names: Gidon T.
  email: gidon.frischkorn@psychologie.uzh.ch
  orcid: https://orcid.org/0000-0002-5055-9764
preferred-citation:
  type: article
  title: 'A tutorial for estimating mixture models for visual working memory tasks
    in brms: Introducing the Bayesian Measurement Modeling (bmm) package for R'
  authors:
  - family-names: Frischkorn
    given-names: Gidon T.
    email: gidon.frischkorn@psychologie.uzh.ch
    orcid: https://orcid.org/0000-0002-5055-9764
  - family-names: Popov
    given-names: Vencislav
    email: vencislav.popov@gmail.com
    orcid: https://orcid.org/0000-0002-8073-4199
  journal: PsyArXiv
  year: '2023'
  doi: 10.31234/osf.io/umt57
repository: https://popov-lab.r-universe.dev
repository-code: https://github.com/venpopov/bmm
commit: 8ada976031db6f46deea8e1f52e68046e8aae8a6
url: https://venpopov.github.io/bmm/
contact:
- family-names: Popov
  given-names: Vencislav
  email: vencislav.popov@gmail.com
  orcid: https://orcid.org/0000-0002-8073-4199