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: | 1.5 |
| Depends: | R (≥ 2.10), survival |
| Imports: | Rcpp (≥ 0.12.3), parallel, tools |
| LinkingTo: | Rcpp |
| Suggests: | knitr, rmarkdown, sbart, MASS |
| Published: | 2018-02-08 |
| Author: | Robert McCulloch [aut], Rodney Sparapani [aut, cre], Robert Gramacy [aut], Charles Spanbauer [aut], Matthew Pratola [aut], Jean-Sebastien Roy [ctb], Makoto Matsumoto [ctb], Takuji Nishimura [ctb], Bill Venables [ctb], Brian Ripley [ctb] |
| Maintainer: | Rodney Sparapani <rsparapa at mcw.edu> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | yes |
| SystemRequirements: | C++11 |
| Materials: | NEWS |
| In views: | MachineLearning |
| CRAN checks: | BART results |
| Reference manual: | BART.pdf |
| Vignettes: |
wbart, BART for Numeric Outcomes Binary and categorical outcomes with BART Efficient computing with BART Time-to-event outcomes with BART |
| Package source: | BART_1.5.tar.gz |
| Windows binaries: | r-devel: BART_1.5.zip, r-release: BART_1.5.zip, r-oldrel: BART_1.5.zip |
| OS X El Capitan binaries: | r-release: BART_1.5.tgz |
| OS X Mavericks binaries: | r-oldrel: BART_1.3.tgz |
| Old sources: | BART archive |
Please use the canonical form https://CRAN.R-project.org/package=BART to link to this page.