Flexible stochastic tree ensemble software. Robust implementations of Bayesian Additive Regression Trees (BART) (Chipman, George, McCulloch (2010) <doi:10.1214/09-AOAS285>) for supervised learning and Bayesian Causal Forests (BCF) (Hahn, Murray, Carvalho (2020) <doi:10.1214/19-BA1195>) for causal inference. Enables model serialization and parallel sampling and provides a low-level interface for custom stochastic forest samplers. Includes the grow-from-root algorithm for accelerated forest sampling (He and Hahn (2021) <doi:10.1080/01621459.2021.1942012>), a log-linear leaf model for forest-based heteroskedasticity (Murray (2020) <doi:10.1080/01621459.2020.1813587>), and the cloglog BART model of Alam and Linero (2025) <doi:10.48550/arXiv.2502.00606> for ordinal outcomes.
| Version: | 0.4.0 |
| Imports: | R6, stats |
| LinkingTo: | cpp11, BH |
| Suggests: | testthat (≥ 3.0.0) |
| Published: | 2026-03-06 |
| DOI: | 10.32614/CRAN.package.stochtree |
| Author: | Drew Herren |
| Maintainer: | Drew Herren <drewherrenopensource at gmail.com> |
| BugReports: | https://github.com/StochasticTree/stochtree/issues |
| License: | MIT + file LICENSE |
| Copyright: | Copyright details for stochtree's C++ dependencies, which
are vendored along with the core stochtree source code, are
detailed in inst/COPYRIGHTS stochtree copyright details |
| URL: | https://stochtree.ai/, https://github.com/StochasticTree/stochtree |
| NeedsCompilation: | yes |
| SystemRequirements: | C++17 |
| Materials: | README, NEWS |
| In views: | Bayesian, CausalInference, MachineLearning |
| CRAN checks: | stochtree results |
| Reference manual: | stochtree.html , stochtree.pdf |
| Package source: | stochtree_0.4.0.tar.gz |
| Windows binaries: | r-devel: stochtree_0.3.1.zip, r-release: stochtree_0.3.1.zip, r-oldrel: stochtree_0.3.1.zip |
| macOS binaries: | r-release (arm64): stochtree_0.4.0.tgz, r-oldrel (arm64): stochtree_0.4.0.tgz, r-release (x86_64): stochtree_0.3.1.tgz, r-oldrel (x86_64): stochtree_0.3.1.tgz |
| Old sources: | stochtree archive |
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