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: 1.1.1 Depends: R (≥ 2.10) Imports: dbarts, loo, posterior, univariateML, extraDistr, graphics Published: 2025-01-14 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: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=EBcoBART to link to this page.
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