bartcs: Bayesian Additive Regression Trees for Confounder Selection

Fit Bayesian Regression Additive Trees (BART) models to select true confounders from a large set of potential confounders and to estimate average treatment effect. For more information, see Kim et al. (2023) <doi:10.1111/biom.13833>.

Version: 1.2.2
Depends: R (≥ 3.4.0)
Imports: coda (≥ 0.4.0), ggcharts, ggplot2, invgamma, MCMCpack, Rcpp, rlang, rootSolve, stats
LinkingTo: Rcpp
Suggests: knitr, microbenchmark, rmarkdown
Published: 2024-05-01
DOI: 10.32614/CRAN.package.bartcs
Author: Yeonghoon Yoo [aut, cre]
Maintainer: Yeonghoon Yoo <yooyh.stat at>
License: GPL (≥ 3)
NeedsCompilation: yes
Citation: bartcs citation info
Materials: README NEWS
In views: Bayesian
CRAN checks: bartcs results


Reference manual: bartcs.pdf
Vignettes: Introduction to bartcs


Package source: bartcs_1.2.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): bartcs_1.2.2.tgz, r-oldrel (arm64): bartcs_1.2.2.tgz, r-release (x86_64): bartcs_1.2.2.tgz, r-oldrel (x86_64): bartcs_1.2.2.tgz
Old sources: bartcs archive


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