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bartcs  

Bayesian Additive Regression Trees for Confounder Selection
View on CRAN: Click here


Download and install bartcs package within the R console
Install from CRAN:
install.packages("bartcs")

Install from Github:
library("remotes")
install_github("cran/bartcs")

Install by package version:
library("remotes")
install_version("bartcs", "1.3.0")



Attach the package and use:
library("bartcs")
Maintained by
Yeonghoon Yoo
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-07-19
Latest Update: 2025-04-08
Description:
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) .
How to cite:
Yeonghoon Yoo (2022). bartcs: Bayesian Additive Regression Trees for Confounder Selection. R package version 1.3.0, https://cran.r-project.org/web/packages/bartcs. Accessed 03 Jul. 2026.
Previous versions and publish date:
0.1.1 (2022-07-19 16:50), 0.1.2 (2022-08-06 09:30), 1.0.0 (2023-03-09 09:50), 1.1.0 (2023-05-01 14:10), 1.2.0 (2023-05-27 17:00), 1.2.1 (2024-01-24 15:02), 1.2.2 (2024-05-01 15:00)
Other packages that cited bartcs R package
View bartcs citation profile
Other R packages that bartcs depends, imports, suggests or enhances
Complete documentation for bartcs
Functions, R codes and Examples using the bartcs R package
Some associated functions: bart . bartcs-package . count_omp_thread . gelman_rubin . ihdp . plot.bartcs . summary.bartcs . 
Some associated R codes: RcppExports.R . bart.R . bartcs-package.R . gelman_rubin.R . ihdp.R . mbart.R . pip_plot.R . plot.R . print.R . sbart.R . separate_bart.R . single_bart.R . summary.R . trace_plot.R . utils.R .  Full bartcs package functions and examples
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