mvBayes

An R implementation of the multivariate Bayesian regression (mvBayes) framework. Decomposes a multivariate/functional response using a user-specified orthogonal basis decomposition, and then models each basis component independently using an arbitrary user-specified (univariate) Bayesian regression model. Includes prediction and plotting methods. (Francom et al., 2025 DOI:10.1137/24M164409)

Examples

• Friedman Example - An extension of the “Friedman function” to functional response. The Bayesian regression model here is BASS (Bayesian Adaptive Smoothing Splines, see https://github.com/lanl/BASS)

### Installation

v0.1.0 is on CRAN and can be installed as

install.packages("mvBayes")`

For a more up to date, but may not be stable version from git repository.

1. Download zip or tar.gz of package or clone repository
2. Install into R (> 4.3.0)

library(devtools)
install_github("sandialabs/mvBayesR")

References

Author: Gavin Q. Collins and J. Derek Tucker Sandia National Laboratories