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# Policy Learning (`polle`) <img src="man/figures/logo.png" align="right" height="250" style="float:right; height:250px;"  alt="polle website" />

Package for evaluating user-specified finite stage policies and learning
optimal treatment policies via doubly robust loss functions. Policy
learning methods include doubly robust learning of the blip/conditional
average treatment effect and sequential policy tree learning. The
package also include methods for optimal subgroup analysis. See Nordland
and Holst (2022)
[doi:10.48550/arXiv.2212.02335](https://doi.org/10.48550/arXiv.2212.02335)
for documentation and references.
