EBcoBART
Co-Data Learning for Bayesian Additive Regression Trees
v1.1.2
·
Aug 20, 2025
·
GPL (>= 3)
Description
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.
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| r-devel-windows-x86_64 | OK |
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| r-oldrel-windows-x86_64 | OK |
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| r-release-linux-x86_64 | OK |
| r-release-macos-arm64 | OK |
| r-release-macos-x86_64 | OK |
| r-release-windows-x86_64 | OK |
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OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
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1.1.2
Mar 9, 2026