Policy Learning via Doubly Robust Empirical Welfare Maximization over Trees

Learn optimal policies via doubly robust empirical welfare maximization over trees. This package implements the multi-action doubly robust approach of Zhou, Athey and Wager (2018) in the case where we want to learn policies that belong to the class of depth k decision trees.


Reference manual

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1.1.1 by Erik Sverdrup, 7 months ago


Report a bug at https://github.com/grf-labs/policytree/issues

Browse source code at https://github.com/cran/policytree

Authors: Erik Sverdrup [aut, cre] , Ayush Kanodia [aut] , Zhengyuan Zhou [aut] , Susan Athey [aut] , Stefan Wager [aut]

Documentation:   PDF Manual  

GPL-3 license

Imports Rcpp, grf

Suggests testthat, DiagrammeR

Linking to Rcpp, BH

See at CRAN