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.
- Version1.1.0
- R versionunknown
- LicenseGPL (≥ 3)
- Needs compilation?No
- Last release09/26/2024
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Team
Jeroen M. Goedhart
Vincent Dorie
Show author detailsRolesContributorMark A. van de Wiel
Show author detailsRolesAuthorThomas Klausch
Show author detailsRolesAuthorHanarth Fonds
Show author detailsRolesfnd
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- Imports5 packages