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: | 1.3.0 |
| 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: | 2025-04-08 |
| DOI: | 10.32614/CRAN.package.bartcs |
| Author: | Yeonghoon Yoo [aut, cre] |
| Maintainer: | Yeonghoon Yoo <yooyh.stat at gmail.com> |
| BugReports: | https://github.com/yooyh/bartcs/issues |
| License: | GPL (≥ 3) |
| URL: | https://github.com/yooyh/bartcs |
| NeedsCompilation: | yes |
| Citation: | bartcs citation info |
| Materials: | README,NEWS |
| In views: | Bayesian |
| CRAN checks: | bartcs results |
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