policytree: Policy learning via doubly robust empirical welfare maximization over trees

R C++ Submitted 20 May 2020Published 22 June 2020
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Editor: @arfon (all papers)
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Authors

Erik Sverdrup (0000-0001-6093-1390), Ayush Kanodia, Zhengyuan Zhou, Susan Athey, Stefan Wager

Citation

Sverdrup et al., (2020). policytree: Policy learning via doubly robust empirical welfare maximization over trees. Journal of Open Source Software, 5(50), 2232, https://doi.org/10.21105/joss.02232

@article{Sverdrup2020, doi = {10.21105/joss.02232}, url = {https://doi.org/10.21105/joss.02232}, year = {2020}, publisher = {The Open Journal}, volume = {5}, number = {50}, pages = {2232}, author = {Erik Sverdrup and Ayush Kanodia and Zhengyuan Zhou and Susan Athey and Stefan Wager}, title = {policytree: Policy learning via doubly robust empirical welfare maximization over trees}, journal = {Journal of Open Source Software} }
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causal inference econometrics

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ISSN 2475-9066