BartMixVs: Variable Selection Using Bayesian Additive Regression Trees

Bayesian additive regression trees (BART) provides flexible non-parametric modeling of mixed-type predictors for continuous and binary responses. This package is built upon CRAN R package 'BART', version 2.7 (<>). It implements the three proposed variable selection approaches in the paper: Luo, C and Daniels, M. J. (2021), "Variable Selection Using Bayesian Additive Regression Trees." <arXiv:2112.13998>, and other three existing BART-based variable selection approaches.

Version: 1.0.0
Depends: R (≥ 2.10), nlme, nnet
Imports: Rcpp (≥ 1.0.6), loo, mvtnorm
LinkingTo: Rcpp
Published: 2022-05-05
Author: Chuji Luo [aut, cre], Michael J. Daniels [aut], Robert McCulloch [ctb], Rodney Sparapani [ctb]
Maintainer: Chuji Luo <cjluo at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: README
CRAN checks: BartMixVs results


Reference manual: BartMixVs.pdf


Package source: BartMixVs_1.0.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): BartMixVs_1.0.0.tgz, r-oldrel (arm64): BartMixVs_1.0.0.tgz, r-release (x86_64): BartMixVs_1.0.0.tgz, r-oldrel (x86_64): BartMixVs_1.0.0.tgz


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