CRE: Interpretable Discovery and Inference of Heterogeneous Treatment Effects

Provides a new method for interpretable heterogeneous treatment effects characterization in terms of decision rules via an extensive exploration of heterogeneity patterns by an ensemble-of-trees approach, enforcing high stability in the discovery. It relies on a two-stage pseudo-outcome regression, and it is supported by theoretical convergence guarantees. Bargagli-Stoffi, F. J., Cadei, R., Lee, K., & Dominici, F. (2023) Causal rule ensemble: Interpretable Discovery and Inference of Heterogeneous Treatment Effects. arXiv preprint <doi:10.48550/arXiv.2009.09036>.

Version: 0.2.6
Depends: R (≥ 3.5.0)
Imports: MASS, stats, logger, gbm, randomForest, methods, xgboost, RRF, data.table, xtable, glmnet, bartCause, stabs, stringr, SuperLearner, magrittr, ggplot2, arules
Suggests: grf, BART, gnm, covr, knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2024-04-21
Author: Naeem Khoshnevis ORCID iD [aut, cre] (FASRC), Daniela Maria Garcia ORCID iD [aut], Riccardo Cadei ORCID iD [aut], Kwonsang Lee ORCID iD [aut], Falco Joannes Bargagli Stoffi ORCID iD [aut]
Maintainer: Naeem Khoshnevis <nkhoshnevis at>
License: GPL-3
Copyright: Harvard University
NeedsCompilation: no
Language: en-US
Citation: CRE citation info
Materials: README NEWS
CRAN checks: CRE results


Reference manual: CRE.pdf
Vignettes: CRE
Testing the CRE package


Package source: CRE_0.2.6.tar.gz
Windows binaries: r-prerel:, r-release:, r-oldrel:
macOS binaries: r-prerel (arm64): CRE_0.2.6.tgz, r-release (arm64): CRE_0.2.6.tgz, r-oldrel (arm64): CRE_0.2.6.tgz, r-prerel (x86_64): CRE_0.2.6.tgz, r-release (x86_64): CRE_0.2.6.tgz
Old sources: CRE archive


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