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BartMixVs  

Variable Selection Using Bayesian Additive Regression Trees
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("BartMixVs", "1.0.0")



Attach the package and use:
library("BartMixVs")
Maintained by
Chuji Luo
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-05-05
Latest Update: 2022-05-05
Description:
Bayesian additive regression trees (BART) provides flexible non-parametric modeling of mixed-type predictors for continuous and binary responses. This package is built upon CRAN R package 'BART', version 2.7 (). It implements the three proposed variable selection approaches in the paper: Luo, C and Daniels, M. J. (2021), "Variable Selection Using Bayesian Additive Regression Trees." , and other three existing BART-based variable selection approaches.
How to cite:
Chuji Luo (2022). BartMixVs: Variable Selection Using Bayesian Additive Regression Trees. R package version 1.0.0, https://cran.r-project.org/web/packages/BartMixVs. Accessed 23 Apr. 2025.
Previous versions and publish date:
1.0.0 (2022-05-05 07:50)
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