GitHub - hsbadr/bayesian: Bindings for Bayesian TidyModels (original) (raw)

• README
• Code of conduct
• License
• MIT license

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.