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https://github.com/hsbadr/bayesian

Bindings for Bayesian TidyModels
https://github.com/hsbadr/bayesian

bayesian brms stan tidymodels

Last synced: 6 days ago
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Bindings for Bayesian TidyModels

Host: GitHub
URL: https://github.com/hsbadr/bayesian
Owner: hsbadr
License: other
Created: 2021-01-06T20:13:10.000Z (about 4 years ago)
Default Branch: main
Last Pushed: 2024-12-30T12:14:46.000Z (19 days ago)
Last Synced: 2025-01-05T10:06:27.398Z (13 days ago)
Topics: bayesian, brms, stan, tidymodels
Language: R
Homepage: https://hsbadr.github.io/bayesian/
Size: 6.67 MB
Stars: 44
Watchers: 5
Forks: 3
Open Issues: 5
Metadata Files:
- Readme: README.Rmd
- Changelog: NEWS.md
- Contributing: .github/CONTRIBUTING.md
- License: LICENSE
- Code of conduct: .github/CODE_OF_CONDUCT.md
- Citation: CITATION.cff
- Support: .github/SUPPORT.md

Awesome Lists containing this project

README

        ---

output: github_document

---

```{r, include = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

  fig.path = "man/figures/README-",

  out.width = "100%"

)

```

# Bindings for Bayesian TidyModels [](https://hsbadr.github.io/bayesian/)

[![Lifecycle: Stable](https://img.shields.io/badge/Lifecycle-Stable-green.svg)](https://lifecycle.r-lib.org/articles/stages.html)

[![Codecov Test Coverage](https://codecov.io/gh/hsbadr/bayesian/branch/main/graph/badge.svg)](https://app.codecov.io/gh/hsbadr/bayesian?branch=main)

[![Last commit](https://img.shields.io/github/last-commit/hsbadr/bayesian)](https://github.com/hsbadr/bayesian/commits/main)

[![Commits since release](https://img.shields.io/github/commits-since/hsbadr/bayesian/latest.svg?color=green)](https://github.com/hsbadr/bayesian/commit/main)

[![R](https://github.com/hsbadr/bayesian/workflows/R/badge.svg)](https://github.com/hsbadr/bayesian/actions)

[![CRAN Status](https://www.r-pkg.org/badges/version/bayesian)](https://CRAN.R-project.org/package=bayesian)

[![CRAN Downloads](https://cranlogs.r-pkg.org/badges/grand-total/bayesian)](https://cran.r-project.org/package=bayesian)

[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://github.com/hsbadr/bayesian/blob/main/LICENSE.md)

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.4426836.svg)](https://zenodo.org/doi/10.5281/zenodo.4426836)

[**`bayesian`**](https://hsbadr.github.io/bayesian/) supports Bayesian modeling using [`brms`](https://paul-buerkner.github.io/brms/)/[`Stan`](https://mc-stan.org/)

with [`parsnip`](https://parsnip.tidymodels.org/)/[`tidymodels`](https://www.tidymodels.org/).

## Installation

The stable version of [`bayesian`](https://hsbadr.github.io/bayesian/) can be installed from [CRAN](https://CRAN.R-project.org/package=bayesian) using:

``` r

install.packages("bayesian")

```

The development version of [`bayesian`](https://hsbadr.github.io/bayesian/) can be installed from [GitHub](https://github.com/hsbadr/bayesian) using:

``` r

install.packages("pak")

pak::pkg_install("hsbadr/bayesian")

```

## Example

``` r

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`](https://hsbadr.github.io/bayesian/articles/GetStarted.html).

## Citation

To cite `bayesian` in publications, please use:

```r

citation("bayesian")

```

> Hamada S. Badr and Paul C. Bürkner (2024):

bayesian: Bindings for Bayesian TidyModels,

[_Comprehensive R Archive Network (CRAN)_](https://cran.r-project.org/package=bayesian).

URL: [https://hsbadr.github.io/bayesian/](https://hsbadr.github.io/bayesian/).

## Contributing

This project is released with a [Contributor Code of Conduct](https://contributor-covenant.org/version/2/0/CODE_OF_CONDUCT.html). 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](https://forum.posit.co/).

- If you think you have encountered a bug, please [submit an issue](https://github.com/hsbadr/bayesian/issues).

- Either way, learn how to create and share a [reprex](https://reprex.tidyverse.org) (a minimal, reproducible example), to clearly communicate about your code.

- Check out further details on [contributing guidelines for tidymodels packages](https://www.tidymodels.org/contribute/) and [how to get help](https://www.tidymodels.org/help/).