Package: policytree
Title: Policy Learning via Doubly Robust Empirical Welfare Maximization
        over Trees
Version: 1.1.0
Authors@R: c(
    person("Erik", "Sverdrup", role = c("aut", "cre"), email = "erikcs@stanford.edu"),
    person("Ayush", "Kanodia", role = "aut"),
    person("Zhengyuan", "Zhou", role = "aut"),
    person("Susan", "Athey", role = "aut"),
    person("Stefan", "Wager", role = "aut")
    )
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
Suggests: testthat (>= 2.1.0), DiagrammeR
RoxygenNote: 7.1.1
LinkingTo: Rcpp, BH
Imports: Rcpp, grf (>= 2.0.0)
URL: https://github.com/grf-labs/policytree
BugReports: https://github.com/grf-labs/policytree/issues
NeedsCompilation: yes
Packaged: 2021-06-24 05:59:52 UTC; erik
Author: Erik Sverdrup [aut, cre],
  Ayush Kanodia [aut],
  Zhengyuan Zhou [aut],
  Susan Athey [aut],
  Stefan Wager [aut]
Maintainer: Erik Sverdrup <erikcs@stanford.edu>
Repository: CRAN
Date/Publication: 2021-06-24 06:40:02 UTC
