Package: bartcs 1.3.0

Yeonghoon Yoo

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>.

Authors:Yeonghoon Yoo [aut, cre]

bartcs_1.3.0.tar.gz
bartcs_1.3.0.tar.gz(r-4.7-arm64)bartcs_1.3.0.tar.gz(r-4.7-x86_64)bartcs_1.3.0.tar.gz(r-4.6-arm64)bartcs_1.3.0.tar.gz(r-4.6-x86_64)
bartcs_1.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
bartcs/json (API)
NEWS

# Install 'bartcs' in R:
install.packages('bartcs', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/yooyh/bartcs/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • ihdp - Infant Health and Development Program Data

On CRAN:

Conda:

cppopenmp

2.70 score 5 scripts 314 downloads 4 exports 41 dependencies

Last updated from:7127bc934a. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK154
linux-devel-x86_64OK148
source / vignettesOK230
linux-release-arm64OK142
linux-release-x86_64OK147
wasm-releaseOK179

Exports:count_omp_threadseparate_bartsingle_bartsynthetic_data

Dependencies:clicodacolorspacecpp11dplyrfarvergenericsggchartsggplot2gluegtableinvgammaisobandlabelinglatticelifecyclemagrittrMASSMatrixMatrixModelsmcmcMCMCpackpatchworkpillarpkgconfigquantregR6RColorBrewerRcpprlangrootSolveS7scalesSparseMsurvivaltibbletidyselectutf8vctrsviridisLitewithr

Introduction to bartcs

Rendered frombartcs.Rmdusingknitr::rmarkdownon Jun 10 2026.

Last update: 2025-04-08
Started: 2022-07-19