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Authors
Riccardo Cadei (0000-0003-2416-8943), Naeem Khoshnevis (0000-0003-4315-1426), Kwonsang Lee (0000-0002-5823-4331), Daniela Maria Garcia (0000-0003-3226-3561), Falco J. Bargagli Stoffi (0000-0002-6131-8165)
Citation
Cadei et al., (2023). CRE: An R package for interpretable discovery and inference of heterogeneous treatment effects. Journal of Open Source Software, 8(92), 5587, https://doi.org/10.21105/joss.05587
@article{Cadei2023,
doi = {10.21105/joss.05587},
url = {https://doi.org/10.21105/joss.05587},
year = {2023},
publisher = {The Open Journal},
volume = {8},
number = {92},
pages = {5587},
author = {Riccardo Cadei and Naeem Khoshnevis and Kwonsang Lee and Daniela Maria Garcia and Falco J. Bargagli Stoffi},
title = {CRE: An R package for interpretable discovery and inference of heterogeneous treatment effects},
journal = {Journal of Open Source Software}
}
Tags
causal inference heterogeneous effect interpretability machine learning
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