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rdlearn: Safe Policy Learning under Regression Discontinuity Design with Multiple Cutoffs
Implements safe policy learning under regression discontinuity designs with multiple cutoffs, based on Zhang et al. (2022) <doi:10.48550/arXiv.2208.13323>. The learned cutoffs are guaranteed to perform no worse than the existing cutoffs in terms of overall outcomes. The 'rdlearn' package also includes features for visualizing the learned cutoffs relative to the baseline and conducting sensitivity analyses.
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Package details |
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| Author | Kentaro Kawato [cre, cph], Yi Zhang [aut], Soichiro Yamauchi [aut], Eli Ben-Michael [aut], Kosuke Imai [aut] |
| Maintainer | Kentaro Kawato <kentaro1358nohe@gmail.com> |
| License | MIT + file LICENSE |
| Version | 0.1.1 |
| URL | https://github.com/kkawato/rdlearn |
| Package repository | View on CRAN |
| Installation |
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