wsBART: Weighted Soft Bayesian Additive Trees

Description

• To incorporate weights into softBART used for heteroskedastic model.
• To embed the softBART into a larger model without auto-updating variance parameters.
• Add more flexibilities in MCMC.

Installation

To install the package, if you are a mac OSX user, you should install the gfortran library from here first, otherwise, you simply install as follows:

library(devtools)
install_github("yizenglistat/wsBART")

Usage

Assume that Y_i= f(x) + ε_i with ε_i follows a normal distribution with mean 0 and variance σ²/w_i, for i=1,...,N. Here w^1/2's are our weight vector in the package.

Note you could still recover the original SoftBart functionality without feeding the weights into it or set the weights to be ones.