GitHub - hsbadr/bayesian: Bindings for Bayesian TidyModels (original) (raw)
Bindings for Bayesian TidyModels 
bayesian supports Bayesian modeling usingbrms/Stanwithparsnip/tidymodels.
Installation
The stable version of bayesiancan be installed fromCRAN using:
install.packages("bayesian")
The development version ofbayesian can be installed fromGitHub 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 withbayesian.
Citation
To cite bayesian
in publications, please use:
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 areprex (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.