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.