stochtree-package: stochtree: Stochastic Tree Ensembles (XBART and BART) for...

In stochtree: Stochastic Tree Ensembles (XBART and BART) for Supervised Learning and Causal Inference

stochtree: Stochastic Tree Ensembles (XBART and BART) for Supervised Learning and Causal Inference

Description

Flexible stochastic tree ensemble software. Robust implementations of Bayesian Additive Regression Trees (BART) Chipman, George, McCulloch (2010) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1214/09-AOAS285")} for supervised learning and Bayesian Causal Forests (BCF) Hahn, Murray, Carvalho (2020) \Sexpr[results=rd]{tools:::Rd_expr_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.

Author(s)

Maintainer: Drew Herren [e-mail] (ORCID)

Authors:

• Richard Hahn

• Jared Murray

• Carlos Carvalho

• Jingyu He

Other contributors:

• Pedro Lima [contributor]

• stochtree contributors [copyright holder]

• Eigen contributors (C++ source uses the Eigen library for matrix operations, see inst/COPYRIGHTS) [copyright holder]

• xgboost contributors (C++ tree code and related operations include or are inspired by code from the xgboost library, see inst/COPYRIGHTS) [copyright holder]

• treelite contributors (C++ tree code and related operations include or are inspired by code from the treelite library, see inst/COPYRIGHTS) [copyright holder]

• Microsoft Corporation (C++ I/O and various project structure code include or are inspired by code from the LightGBM library, which is a copyright of Microsoft, see inst/COPYRIGHTS) [copyright holder]

• Niels Lohmann (C++ source uses the JSON for Modern C++ library for JSON operations, see inst/COPYRIGHTS) [copyright holder]

• Daniel Lemire (C++ source uses the fast_double_parser library internally, see inst/COPYRIGHTS) [copyright holder]

• Victor Zverovich (C++ source uses the fmt library internally, see inst/COPYRIGHTS) [copyright holder]

See Also

Useful links:

• https://stochtree.ai/

• https://github.com/StochasticTree/stochtree

• Report bugs at https://github.com/StochasticTree/stochtree/issues

stochtree documentation built on April 4, 2025, 2:11 a.m.