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.