The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

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

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.
Health stats visible at Monitor.