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:10.1002/sim.70004> for details.
| Version: | 1.1.2 | 
| Depends: | R (≥ 2.10) | 
| Imports: | dbarts, loo, posterior, univariateML, extraDistr, graphics | 
| Published: | 2025-08-20 | 
| DOI: | 10.32614/CRAN.package.EBcoBART | 
| Author: | Jeroen M. Goedhart | 
| Maintainer: | Jeroen M. Goedhart <jeroengoed at gmail.com> | 
| License: | GPL (≥ 3) | 
| URL: | https://github.com/JeroenGoedhart/EBcoBART | 
| NeedsCompilation: | no | 
| Citation: | EBcoBART citation info | 
| Materials: | README, NEWS | 
| CRAN checks: | EBcoBART results | 
| Reference manual: | EBcoBART.html , EBcoBART.pdf | 
| Package source: | EBcoBART_1.1.2.tar.gz | 
| Windows binaries: | r-devel: EBcoBART_1.1.2.zip, r-release: EBcoBART_1.1.2.zip, r-oldrel: EBcoBART_1.1.2.zip | 
| macOS binaries: | r-release (arm64): EBcoBART_1.1.2.tgz, r-oldrel (arm64): EBcoBART_1.1.2.tgz, r-release (x86_64): EBcoBART_1.1.2.tgz, r-oldrel (x86_64): EBcoBART_1.1.2.tgz | 
| Old sources: | EBcoBART archive | 
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