BART: Bayesian Additive Regression Trees

Bayesian Additive Regression Trees (BART) provide flexible nonparametric modeling of covariates for continuous, binary and time-to-event outcomes. For more information on BART, see Chipman, George and McCulloch (2010) <doi:10.1214/09-AOAS285> and Sparapani, Logan, McCulloch and Laud (2016) <doi:10.1002/sim.6893>.

Version: 1.3
Depends: R (≥ 2.10), survival
Imports: Rcpp (≥ 0.12.3), parallel, tools
LinkingTo: Rcpp
Published: 2017-09-21
Author: Robert McCulloch [aut], Rodney Sparapani [aut, cre], Robert Gramacy [aut], Matthew Pratola [aut], Jean-Sebastien Roy [ctb], Makoto Matsumoto [ctb], Takuji Nishimura [ctb]
Maintainer: Rodney Sparapani <rsparapa at mcw.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
SystemRequirements: C++11
Materials: NEWS
CRAN checks: BART results

Downloads:

Reference manual: BART.pdf
Package source: BART_1.3.tar.gz
Windows binaries: r-devel: BART_1.3.zip, r-release: BART_1.3.zip, r-oldrel: BART_1.3.zip
OS X El Capitan binaries: r-release: BART_1.3.tgz
OS X Mavericks binaries: r-oldrel: BART_1.3.tgz
Old sources: BART archive

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