XBART

XBART: Accelerated Bayesian Additive Regression Trees

XBART is a stochastic hill climbing algorithm which provide fast inference of BART posterior. Simulation studies shows that XBART XBART is comparable in computation time and more accurate at function estimation than both random forest and gradient boosting.

The beta version is posted on my website, will be upload to CRAN and pip soon. You are welcome to test the code. Bug reports are valuable and highly appreciated.

1. Installing the pacakge

Install R package

Download R package XBART_0.1.tar.gz.
The pacakge relies on Rcpp and RcppArmadillo.
install.packages("XBART_0.1.tar.gz")
C++ 11 compiler is required, please install Rtools (Windows) or Xcode and Command Line Tools (Mac).

Install python package

pip install XBART or pip3 install XBART.

2. Sample code

R script and python script.

Contact

  • Address

    The University of Chicago
    Booth School of Business
    5807 S Woodlawn Ave
    Chicago, IL 60637, USA
  • Email

    jingyu.he@chicagobooth.edu