Bayesian Additive Regression Trees Using Particle Gibbs Sampler
and Gibbs/Metropolis-Hastings Sampler
Description
The Particle Gibbs sampler and Gibbs/Metropolis-Hastings sampler were implemented
to fit Bayesian additive regression tree model. Construction of the model (training) and prediction
for a new data set (testing) can be separated. Our reference papers are:
Lakshminarayanan B, Roy D, Teh Y W. Particle Gibbs for Bayesian additive regression trees[C],
Artificial Intelligence and Statistics. 2015: 553-561,
and Chipman, H., George, E., and McCulloch R. (2010) Bayesian Additive Regression Trees. The Annals of Applied Statistics, 4,1, 266-298, .