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Package for learning and evaluating (subgroup) policies via doubly robust loss functions. Policy learning methods include doubly robust blip/conditional average treatment effect learning and sequential policy tree learning. Methods for (subgroup) policy evaluation include doubly robust cross-fitting and online estimation/sequential validation. See Nordland and Holst (2022) <doi:10.48550/arXiv.2212.02335> for documentation and references.
Package details |
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| Author | Andreas Nordland [aut, cre], Klaus Holst [aut] (ORCID: <https://orcid.org/0000-0002-1364-6789>) |
| Maintainer | Andreas Nordland <andreasnordland@gmail.com> |
| License | Apache License (>= 2) |
| Version | 1.6.1 |
| Package repository | View on CRAN |
| Installation |
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