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flexBART  

A More Flexible BART Model
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("flexBART", "2.0.3")



Attach the package and use:
library("flexBART")
Maintained by
Sameer K. Deshpande
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-02-12
Latest Update: 2026-02-12
Description:
Implements a faster and more expressive version of Bayesian Additive Regression Trees that, at a high level, approximates unknown functions as a weighted sum of binary regression tree ensembles. Supports fitting (generalized) linear varying coefficient models that posits a linear relationship between the inverse link and some covariates but allows that relationship to change as a function of other covariates. Additionally supports fitting heteroscedastic BART models, in which both the mean and log-variance are approximated with separate regression tree ensembles. A formula interface allows for different splitting variables to be used in each ensemble. For more details see Deshpande (2025) <doi:10.1080/10618600.2024.2431072> and Deshpande et al. (2024) <doi:10.1214/24-BA1470>.
How to cite:
Sameer K. Deshpande (2026). flexBART: A More Flexible BART Model. R package version 2.0.3, https://cran.r-project.org/web/packages/flexBART. Accessed 26 Jun. 2026.
Previous versions and publish date:
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Complete documentation for flexBART
Functions, R codes and Examples using the flexBART R package
Full flexBART package functions and examples
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