Package: CRE 0.2.7

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>.

Authors:Naeem Khoshnevis [aut], Daniela Maria Garcia [aut], Riccardo Cadei [aut], Kwonsang Lee [aut], Falco Joannes Bargagli Stoffi [aut, cre]