Package: policytree
Title: Policy Learning via Doubly Robust Empirical Welfare Maximization
        over Trees
Version: 1.2.4
Authors@R: c(
    person("Erik", "Sverdrup", role = c("aut", "cre"), email = "erik.sverdrup@monash.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. Given doubly robust reward estimates, this package
 finds a rule-based treatment prescription policy, where the policy takes the form of
 a shallow decision tree that is globally (or close to) optimal.
Depends: R (>= 3.5.0)
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: testthat (>= 3.0.4), DiagrammeR
RoxygenNote: 7.2.3
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: 2026-02-18 06:27:58 UTC; erikcs
Author: Erik Sverdrup [aut, cre],
  Ayush Kanodia [aut],
  Zhengyuan Zhou [aut],
  Susan Athey [aut],
  Stefan Wager [aut]
Maintainer: Erik Sverdrup <erik.sverdrup@monash.edu>
Repository: CRAN
Date/Publication: 2026-02-18 07:10:02 UTC
Built: R 4.6.0; aarch64-apple-darwin23; 2026-04-26 00:32:54 UTC; unix
Archs: policytree.so.dSYM
