Package: flexBART 2.0.3

Sameer K. Deshpande

flexBART: A More Flexible BART Model

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>.

Authors:Sameer K. Deshpande [aut, cre], George Perrett [aut], Ryan Yee [aut], Cecilia Balocchi [aut], Jennifer Hill [aut]

flexBART_2.0.3.tar.gz
flexBART_2.0.3.tar.gz(r-4.7-arm64)flexBART_2.0.3.tar.gz(r-4.7-x86_64)flexBART_2.0.3.tar.gz(r-4.6-arm64)flexBART_2.0.3.tar.gz(r-4.6-x86_64)
flexBART_2.0.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
flexBART/json (API)

# Install 'flexBART' in R:
install.packages('flexBART', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/skdeshpande91/flexbart/issues

Pkgdown/docs site:https://skdeshpande91.github.io

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

openblascpp

1.00 score 9 scripts 184 downloads 3 exports 11 dependencies

Last updated from:c11db3865f. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK281
linux-devel-x86_64OK274
source / vignettesOK307
linux-release-arm64OK278
linux-release-x86_64OK263
wasm-releaseOK234

Exports:flexBARTpredict.flexBARTrflexBART

Dependencies:codetoolsforeachglmnetiteratorslatticeMatrixRcppRcppArmadilloRcppEigenshapesurvival