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bartMachine: Bayesian Additive Regression Trees

An advanced implementation of Bayesian Additive Regression Trees with expanded features for data analysis and visualization.

Version: 1.3.4.1
Depends: R (≥ 2.14.0), rJava (≥ 0.9-8), bartMachineJARs (≥ 1.2.1), randomForest, missForest
Imports: graphics, grDevices, stats
Published: 2023-07-06
DOI: 10.32614/CRAN.package.bartMachine
Author: Adam Kapelner and Justin Bleich (R package)
Maintainer: Adam Kapelner <kapelner at qc.cuny.edu>
License: GPL-3
Copyright: see file COPYRIGHTS
NeedsCompilation: no
SystemRequirements: Java (>= 8.0)
Citation: bartMachine citation info
Materials: ChangeLog
In views: Bayesian, MachineLearning
CRAN checks: bartMachine results

Documentation:

Reference manual: bartMachine.pdf
Vignettes: bartMachine

Downloads:

Package source: bartMachine_1.3.4.1.tar.gz
Windows binaries: r-devel: bartMachine_1.3.4.1.zip, r-release: bartMachine_1.3.4.1.zip, r-oldrel: bartMachine_1.3.4.1.zip
macOS binaries: r-release (arm64): bartMachine_1.3.4.1.tgz, r-oldrel (arm64): bartMachine_1.3.4.1.tgz, r-release (x86_64): bartMachine_1.3.4.1.tgz, r-oldrel (x86_64): bartMachine_1.3.4.1.tgz
Old sources: bartMachine archive

Reverse dependencies:

Reverse imports: bartMan, EnsembleBase, iBART
Reverse suggests: BayesTreePrior, condvis2, evalITR, flowml, MachineShop, SuperLearner, superMICE, vivid
Reverse enhances: tidytreatment

Linking:

Please use the canonical form https://CRAN.R-project.org/package=bartMachine to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.