ML_IMPL

R, python, C code for implementing MCMC and other simulations.

How to use

It is just script, not R package. You can load script by 'source' function. But it will mess up your environment. I recommend this way.

BCART <- new.env()
source("./Bayes_CART.R", local=BCART)

model0 <- BCART$lapBCART(Y~., "exposure", example.data, method = "zip")

Citations

For 'Bayes_GLM.R'

Scott A. Baldwin, Michael J. Larson,
An introduction to using Bayesian linear regression with clinical data,
Behaviour Research and Therapy, Volume 98, 2017, Pages 58-75

For 'Bayes_CART.R'

Normal regression and classification

Chipman, H. A., George, E. I., & McCulloch, R. E. (1998).
Bayesian CART Model Search.
Journal of the American Statistical Association, 93(443), 935–948.

Poisson, NegBinomial, ZIP

Yaojun Zhang, Lanpeng Ji, Georgios Aivaliotis, Charles Taylor,
Bayesian CART models for insurance claims frequency,
Insurance: Mathematics and Economics, Volume 114, 2024, Pages 108-131.

For 'RJMCMC'

Andrieu, C., de Freitas, N., Doucet, A. et al. An Introduction to MCMC for Machine Learning.
Machine Learning 50, 5–43 (2003). https://doi.org/10.1023/A:1020281327116

For 'BART'

Hugh A. Chipman. Edward I. George. Robert E. McCulloch. "BART: Bayesian additive regression trees."
Ann. Appl. Stat. 4 (1) 266 - 298, March 2010. https://doi.org/10.1214/09-AOAS285

For 'xbart'

Jingyu He, Saar Yalov, P. Richard Hahn. "XBART: Accelerated Bayesian Additive Regression Trees."
arXiv:1810.02215 https://arxiv.org/abs/1810.02215v3