iBART: Iterative Bayesian Additive Regression Trees Descriptor Selection 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 Ye  [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.pdf |
| Vignettes: |
Single-Atom Catalysis Data Analysis Complex Model Simulation |
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 |
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