doi:10.5281/zenodo.4426836>. 'tidymodels' is a collection of packages for machine learning; see Kuhn and Wickham (2020) <https://www.tidymodels.org>). The technical details of 'brms' and 'Stan' are described in Bürkner (2017) <doi:10.18637/jss.v080.i01>, Bürkner (2018) <doi:10.32614/RJ-2018-017>, and Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>.">

bayesian: Bindings for Bayesian TidyModels (original) (raw)

Fit Bayesian models using 'brms'/'Stan' with 'parsnip'/'tidymodels' via 'bayesian' <doi:10.5281/zenodo.4426836>. 'tidymodels' is a collection of packages for machine learning; see Kuhn and Wickham (2020) <https://www.tidymodels.org>). The technical details of 'brms' and 'Stan' are described in Bürkner (2017) <doi:10.18637/jss.v080.i01>, Bürkner (2018) <doi:10.32614/RJ-2018-017>, and Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>.

Version: 1.0.1
Depends: brms (≥ 2.21.0), parsnip (≥ 1.2.1), R (≥ 4.1.0)
Imports: dplyr, purrr, rlang, stats, tibble, utils
Suggests: covr, devtools, future, knitr, recipes, rmarkdown, roxygen2, rstan, spelling, testthat, workflows
Published: 2024-04-28
DOI: 10.32614/CRAN.package.bayesian
Author: Hamada S. Badr ORCID iD [aut, cre], Paul-Christian Bürkner [aut]
Maintainer: Hamada S. Badr
BugReports: https://github.com/hsbadr/bayesian/issues
License: MIT + file
URL: https://hsbadr.github.io/bayesian/,https://github.com/hsbadr/bayesian
NeedsCompilation: no
Language: en-US
Citation: bayesian citation info
Materials: README NEWS
In views: Bayesian
CRAN checks: bayesian results

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