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refundBayes: Bayesian Regression with Functional Data

Bayesian regression with functional data, including regression with scalar, survival, or functional outcomes. The package allows regression with scalar and functional predictors. Methods are described in Jiang et al. (2025) "Tutorial on Bayesian Functional Regression Using Stan" <doi:10.1002/sim.70265>.

Version: 0.5.1
Depends: R (≥ 3.6.0)
Imports: brms, dplyr, ggplot2 (≥ 2.0.0), mgcv, refund, rstan (≥ 2.29.0), splines2, stats
Suggests: knitr, rmarkdown
Published: 2026-04-07
DOI: 10.32614/CRAN.package.refundBayes
Author: Ziren Jiang [aut, cre], Erjia Cui [aut], Ciprian Crainiceanu [ctb]
Maintainer: Ziren Jiang <jian0746 at umn.edu>
BugReports: https://github.com/ZirenJiang/refundBayes/issues
License: GPL-2
URL: https://zirenjiang.github.io/refundBayes/, https://github.com/ZirenJiang/refundBayes
NeedsCompilation: no
Materials: README
CRAN checks: refundBayes results

Documentation:

Reference manual: refundBayes.html , refundBayes.pdf
Vignettes: Bayesian Functional Cox Regression (source, R code)
Bayesian Function-on-Scalar Regression (source, R code)
Bayesian Scalar-on-Function Regression (source, R code)

Downloads:

Package source: refundBayes_0.5.1.tar.gz
Windows binaries: r-release: refundBayes_0.5.1.zip, r-oldrel: refundBayes_0.5.1.zip
macOS binaries: r-release (arm64): refundBayes_0.5.1.tgz, r-oldrel (arm64): refundBayes_0.5.1.tgz, r-release (x86_64): refundBayes_0.5.1.tgz, r-oldrel (x86_64): refundBayes_0.5.1.tgz
Old sources: refundBayes archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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