Package: policytree
Title: Policy Learning via Doubly Robust Empirical Welfare Maximization
        over Trees
Version: 1.0.1
Authors@R: c(
    person("Zhengyuan", "Zhou", role = "aut"),
    person("Susan", "Athey", role = "aut"),
    person("Stefan", "Wager", role = "aut"),
    person("Ayush", "Kanodia", role = "aut"),
    person("Erik", "Sverdrup", role = "cre", email = "erikcs@stanford.edu")
    )
Description: 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) <arXiv:1810.04778> in the case where
 we want to learn policies that belong to the class of depth k decision trees.
Depends: R (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Suggests: testthat (>= 2.1.0), DiagrammeR
RoxygenNote: 7.0.2
LinkingTo: Rcpp, BH
Imports: Rcpp, grf (>= 1.1.0)
URL: https://github.com/grf-labs/policytree
NeedsCompilation: yes
Packaged: 2020-07-13 01:20:46 UTC; erik
Author: Zhengyuan Zhou [aut],
  Susan Athey [aut],
  Stefan Wager [aut],
  Ayush Kanodia [aut],
  Erik Sverdrup [cre]
Maintainer: Erik Sverdrup <erikcs@stanford.edu>
Repository: CRAN
Date/Publication: 2020-07-13 06:30:02 UTC
