bayesian supports Bayesian modeling using brms/Stan with parsnip/tidymodels.
Installation
The stable version of bayesian can be installed from CRAN using:
install.packages("bayesian")The development version of bayesian can be installed from GitHub using:
install.packages("pak")
pak::pkg_install("hsbadr/bayesian")Example
library(bayesian)
bayesian_mod <-
  bayesian() |>
  set_engine("brms") |>
  fit(
    rating ~ treat + period + carry + (1 | subject),
    data = inhaler
  )
summary(bayesian_mod$fit)For more details, get started with bayesian.
Citation
To cite bayesian in publications, please use:
citation("bayesian")Hamada S. Badr and Paul C. Bürkner (2024): bayesian: Bindings for Bayesian TidyModels, Comprehensive R Archive Network (CRAN). URL: https://hsbadr.github.io/bayesian/.
Contributing
This project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
- For questions and discussions about tidymodels packages, modeling, and machine learning, please post on RStudio Community. 
- If you think you have encountered a bug, please submit an issue. 
- Either way, learn how to create and share a reprex (a minimal, reproducible example), to clearly communicate about your code. 
- Check out further details on contributing guidelines for tidymodels packages and how to get help. 
