DESCRIPTION

Package: bmm
Title: Easy and Accessible Bayesian Measurement Models Using 'brms'
Version: 1.0.1.9000
Authors@R: c(
    person("Vencislav", "Popov", , "vencislav.popov@gmail.com", role = c("aut", "cre", "cph"),
           comment = c(ORCID = "0000-0002-8073-4199")),
    person("Gidon T.", "Frischkorn", , "gidon.frischkorn@psychologie.uzh.ch", role = c("aut", "cph"),
           comment = c(ORCID = "0000-0002-5055-9764")),
    person("Paul-Christian", "Bürkner", , "paul.buerkner@gmail.com", role = "cph",
           comment = "Creator of 'brms', code portions of which are used in 'bmm'.")
  )
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>.
License: GPL-2
URL: https://github.com/venpopov/bmm, https://venpopov.github.io/bmm/
BugReports: https://github.com/venpopov/bmm/issues
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
Additional_repositories: https://mc-stan.org/r-packages/
Config/testthat/edition: 3
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2