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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "policytree" in publications use:'
type: software
license: MIT
title: 'policytree: Policy Learning via Doubly Robust Empirical Welfare Maximization
  over Trees'
version: 1.2.4
doi: 10.32614/CRAN.package.policytree
abstract: 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.
authors:
- family-names: Sverdrup
  given-names: Erik
  email: erik.sverdrup@monash.edu
- family-names: Kanodia
  given-names: Ayush
- family-names: Zhou
  given-names: Zhengyuan
- family-names: Athey
  given-names: Susan
- family-names: Wager
  given-names: Stefan
repository: https://anumbat.r-universe.dev
repository-code: https://github.com/grf-labs/policytree
commit: c797df452340ed0f714c3bfbcbdf79810e7e251d
url: https://github.com/grf-labs/policytree
date-released: '2026-02-18'
contact:
- family-names: Sverdrup
  given-names: Erik
  email: erik.sverdrup@monash.edu