
bayesian
supports Bayesian modeling using brms/Stan with parsnip/tidymodels.
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")
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.
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/.
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.
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