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iBART: Iterative Bayesian Additive Regression Trees DescriptorSelection Method

A statistical method based on Bayesian Additive Regression Trees with Global Standard Error Permutation Test (BART-G.SE) for descriptor selection and symbolic regression. It finds the symbolic formula of the regression function y=f(x) as described in Ye, Senftle, and Li (2023) <doi:10.48550/arXiv.2110.10195>.

Version:1.0.0
Depends:R (≥ 4.0.0)
Imports:bartMachine (≥ 1.2.6),glmnet (≥ 4.1-1),foreach, stats
Suggests:knitr,rmarkdown,ggplot2,ggpubr
Published:2023-11-14
DOI:10.32614/CRAN.package.iBART
Author:Shengbin YeORCID iD [aut, cre, cph], Meng Li [aut]
Maintainer:Shengbin Ye <sy53 at rice.edu>
BugReports:https://github.com/mattsheng/iBART/issues
License:GPL (≥ 3)
URL:https://github.com/mattsheng/iBART
NeedsCompilation:no
SystemRequirements:Java (>= 8.0)
Materials:README,NEWS
CRAN checks:iBART results

Documentation:

Reference manual:iBART.html ,iBART.pdf
Vignettes:Single-Atom Catalysis Data Analysis (source,R code)
Complex Model Simulation (source,R code)

Downloads:

Package source: iBART_1.0.0.tar.gz
Windows binaries: r-devel:iBART_1.0.0.zip, r-release:iBART_1.0.0.zip, r-oldrel:iBART_1.0.0.zip
macOS binaries: r-release (arm64):iBART_1.0.0.tgz, r-oldrel (arm64):iBART_1.0.0.tgz, r-release (x86_64):iBART_1.0.0.tgz, r-oldrel (x86_64):iBART_1.0.0.tgz

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=iBARTto link to this page.


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