A Python 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.
To install the most up to date version on github
pip install -e .
please see requirements for a list of packages mvBayes
depends on
- 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/pyBASS)
Author: Gavin Q. Collins and J. Derek Tucker Sandia National Laboratories