Package: bartcs 1.2.2

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]

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bartcs.pdf |bartcs.html✨
bartcs/json (API)
NEWS

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

Peer review:

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:

4.48 score 3 stars 3 scripts 318 downloads 3 exports 43 dependencies

Last updated 7 months agofrom:e4d47f698e. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 13 2024
R-4.5-win-x86_64OKNov 13 2024
R-4.5-linux-x86_64OKNov 13 2024
R-4.4-win-x86_64OKNov 13 2024
R-4.4-mac-x86_64OKNov 13 2024
R-4.4-mac-aarch64OKNov 13 2024
R-4.3-win-x86_64OKNov 13 2024
R-4.3-mac-x86_64OKNov 13 2024
R-4.3-mac-aarch64OKNov 13 2024

Exports:count_omp_threadseparate_bartsingle_bart

Dependencies:clicodacolorspacedplyrfansifarvergenericsggchartsggplot2gluegtableinvgammaisobandlabelinglatticelifecyclemagrittrMASSMatrixMatrixModelsmcmcMCMCpackmgcvmunsellnlmepatchworkpillarpkgconfigquantregR6RColorBrewerRcpprlangrootSolvescalesSparseMsurvivaltibbletidyselectutf8vctrsviridisLitewithr

Introduction to bartcs

Yeonghoon Yoo

Rendered frombartcs.Rmdusingknitr::rmarkdownon Nov 13 2024.

Last update: 2023-05-26
Started: 2022-07-07