Package: bartcs 1.2.2

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_1.2.2.tar.gz
bartcs_1.2.2.tar.gz(r-4.5-noble)bartcs_1.2.2.tar.gz(r-4.4-noble)
bartcs_1.2.2.tgz(r-4.4-emscripten)bartcs_1.2.2.tgz(r-4.3-emscripten)
bartcs.pdf |bartcs.html✨
bartcs/json (API)
NEWS

# Install 'bartcs' in R:
install.packages('bartcs', repos = c('https://cran.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

cppopenmp

3.00 score 324 downloads 3 exports 43 dependencies

Last updated 9 months agofrom:3c33038cc9. Checks:2 OK. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKJan 27 2025
R-4.5-linux-x86_64OKJan 27 2025

Exports:count_omp_threadseparate_bartsingle_bart

Dependencies:clicodacolorspacedplyrfansifarvergenericsggchartsggplot2gluegtableinvgammaisobandlabelinglatticelifecyclemagrittrMASSMatrixMatrixModelsmcmcMCMCpackmgcvmunsellnlmepatchworkpillarpkgconfigquantregR6RColorBrewerRcpprlangrootSolvescalesSparseMsurvivaltibbletidyselectutf8vctrsviridisLitewithr

Introduction to bartcs

Yeonghoon Yoo

Rendered frombartcs.Rmdusingknitr::rmarkdownon Jan 27 2025.

Last update: 2023-05-27
Started: 2022-07-19