polle-package: polle: Policy Learning

In polle: Policy Learning

polle: Policy Learning

Description

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) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.48550/arXiv.2212.02335")} for documentation and references.

Author(s)

Maintainer: Andreas Nordland [e-mail]

Authors:

• Klaus Holst [e-mail] (ORCID)

See Also

Useful links:

• Report bugs at https://github.com/AndreasNordland/polle/issues

polle documentation built on Dec. 1, 2025, 5:08 p.m.