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policytree: Policy Learning via Doubly Robust Empirical Welfare Maximization over Trees

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.

Version: 1.2.3
Depends: R (≥ 3.5.0)
Imports: Rcpp, grf (≥ 2.0.0)
LinkingTo: Rcpp, BH
Suggests: testthat (≥ 3.0.4), DiagrammeR
Published: 2024-06-13
DOI: 10.32614/CRAN.package.policytree
Author: Erik Sverdrup [aut, cre], Ayush Kanodia [aut], Zhengyuan Zhou [aut], Susan Athey [aut], Stefan Wager [aut]
Maintainer: Erik Sverdrup <erik.sverdrup at monash.edu>
BugReports: https://github.com/grf-labs/policytree/issues
License: MIT + file LICENSE
URL: https://github.com/grf-labs/policytree
NeedsCompilation: yes
CRAN checks: policytree results

Documentation:

Reference manual: policytree.pdf

Downloads:

Package source: policytree_1.2.3.tar.gz
Windows binaries: r-devel: policytree_1.2.3.zip, r-release: policytree_1.2.3.zip, r-oldrel: policytree_1.2.3.zip
macOS binaries: r-release (arm64): policytree_1.2.3.tgz, r-oldrel (arm64): policytree_1.2.3.tgz, r-release (x86_64): policytree_1.2.3.tgz, r-oldrel (x86_64): policytree_1.2.3.tgz
Old sources: policytree archive

Reverse dependencies:

Reverse imports: EpiForsk, polle

Linking:

Please use the canonical form https://CRAN.R-project.org/package=policytree to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.