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 [aut, cre], Paul-Christian Bürkner [aut] Maintainer: Hamada S. Badr <badr at jhu.edu> BugReports: https://github.com/hsbadr/bayesian/issues License: MIT + file LICENSE 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 Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=bayesian to link to this page.
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