EBcoBART: Co-Data Learning for Bayesian Additive Regression Trees
Estimate prior variable weights for Bayesian Additive Regression Trees (BART). These weights correspond to the probabilities of the variables being selected in the splitting rules of the sum-of-trees. Weights are estimated using empirical Bayes and external information on the explanatory variables (co-data). BART models are fitted using the 'dbarts' 'R' package. See Goedhart and others (2023) <doi:10.48550/arXiv.2311.09997> for details.
| Version: | 1.1.0 |
| Depends: | R (≥ 2.10) |
| Imports: | dbarts, loo, posterior, univariateML, extraDistr, graphics |
| Published: | 2024-09-26 |
| DOI: | 10.32614/CRAN.package.EBcoBART |
| Author: | Jeroen M. Goedhart
 [aut, cre,
cph],
Thomas Klausch [aut],
Mark A. van de Wiel [aut],
Vincent Dorie [ctb] (Author of 'dbarts' 'R' package and auxiliary
function getDepth),
Hanarth Fonds [fnd] |
| Maintainer: | Jeroen M. Goedhart <jeroengoed at gmail.com> |
| License: | GPL (≥ 3) |
| URL: | https://github.com/JeroenGoedhart/EBcoBART |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | EBcoBART results |
Documentation:
| Reference manual: | EBcoBART.pdf |
Downloads:
| Package source: | EBcoBART_1.1.0.tar.gz |
| Windows binaries: | r-devel: EBcoBART_1.1.0.zip, r-release: EBcoBART_1.1.0.zip, r-oldrel: EBcoBART_1.1.0.zip |
| macOS binaries: | r-release (arm64): EBcoBART_1.1.0.tgz, r-oldrel (arm64): EBcoBART_1.1.0.tgz, r-release (x86_64): EBcoBART_1.1.0.tgz, r-oldrel (x86_64): EBcoBART_1.1.0.tgz |
| Old sources: | EBcoBART archive |
Linking:
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