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EBcoBART  

Co-Data Learning for Bayesian Additive Regression Trees
View on CRAN: Click here


Download and install EBcoBART package within the R console
Install from CRAN:
install.packages("EBcoBART")

Install from Github:
library("remotes")
install_github("cran/EBcoBART")

Install by package version:
library("remotes")
install_version("EBcoBART", "1.1.1")



Attach the package and use:
library("EBcoBART")
Maintained by
Jeroen M. Goedhart
[Scholar Profile | Author Map]
First Published: 2024-09-02
Latest Update: 2024-09-03
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:10.48550/arXiv.2311.09997> for details.
How to cite:
Jeroen M. Goedhart (2024). EBcoBART: Co-Data Learning for Bayesian Additive Regression Trees. R package version 1.1.1, https://cran.r-project.org/web/packages/EBcoBART. Accessed 20 Feb. 2025.
Previous versions and publish date:
1.0.1 (2024-09-02 23:50), 1.0.2 (2024-09-03 18:00), 1.1.0 (2024-09-26 16:30)
Other packages that cited EBcoBART R package
View EBcoBART citation profile
Other R packages that EBcoBART depends, imports, suggests or enhances
Complete documentation for EBcoBART
Functions, R codes and Examples using the EBcoBART R package
Full EBcoBART package functions and examples
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