Package: bartMachine Type: Package Title: Bayesian Additive Regression Trees Version: 1.4.3 Date: 2026-09-01 Maintainer: Adam Kapelner Authors@R: c(person(given = "Adam", family = "Kapelner", role = c("aut", "cre", "cph"), email = "kapelner@qc.cuny.edu", comment = c(ORCID = "0000-0001-5985-6792")), person(given = "Justin", family = "Bleich", role = c("aut", "cph"))) Description: Fits Bayesian additive regression trees (BART), a Bayesian nonparametric machine-learning method, for regression and classification. Provides posterior inference, credible and prediction intervals, variable selection, interaction analysis, partial-dependence plots, cross-validation, and optional graphics processing unit (GPU) acceleration through TornadoVM. License: MIT + file LICENSE Encoding: UTF-8 Depends: R (>= 2.14.0) Imports: bartMachineJARs (>= 1.2.3), rJava, randomForest, missForest, stats, ggplot2, grid, checkmate, matrixStats, grDevices Suggests: testthat (>= 3.0.0), withr SystemRequirements: Java (>= 21.0), TornadoVM (if you want GPU optimization) URL: https://kapelner.github.io/bartMachine/, https://kapelner.r-universe.dev/bartMachine, https://github.com/kapelner/bartMachine BugReports: https://github.com/kapelner/bartMachine/issues X-schema.org-keywords: Bayesian additive regression trees, BART, Bayesian machine learning, Bayesian nonparametrics, machine learning, ensemble learning, decision trees, regression, classification, posterior inference, MCMC, variable selection, uncertainty quantification, interpretable machine learning, partial dependence, cross-validation, GPU acceleration RoxygenNote: 7.3.3 Config/testthat/edition: 3 Config/pak/sysreqs: make default-jdk Repository: https://kapelner.r-universe.dev Date/Publication: 2026-09-03 13:11:19 UTC RemoteUrl: https://github.com/kapelner/bartMachine RemoteRef: HEAD RemoteSha: ca90cdd752e574cf2302d30a05f947e2f12a8469 RemoteSubdir: bartMachine NeedsCompilation: no Packaged: 2026-10-15 10:36:05 UTC; root Author: Adam Kapelner [aut, cre, cph] (ORCID: ), Justin Bleich [aut, cph]