EBcoBART

Co-Data Learning for Bayesian Additive Regression Trees

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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.


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