fastpolicytree: Constructs Policy Trees from Covariate and Reward Data
Constructs optimal policy trees which provide a rule-based treatment prescription policy. Input is covariate and reward data, where, typically, the rewards will be doubly robust reward estimates. This package aims to construct optimal policy trees more quickly than the existing 'policytree' package and is intended to be used alongside that package. For more details see Cussens, Hatamyar, Shah and Kreif (2025) <doi:10.48550/arXiv.2506.15435>.
| Version: | 1.0 |
| Imports: | Rcpp (≥ 1.0.7) |
| LinkingTo: | Rcpp |
| Suggests: | policytree |
| Published: | 2025-06-24 |
| DOI: | 10.32614/CRAN.package.fastpolicytree |
| Author: | James Cussens 
[aut, cre],
Julia Hatamyar [ctb],
Vishalie Shah [ctb],
University of Bristol [cph],
MRC [fnd] |
| Maintainer: | James Cussens <james.cussens at bristol.ac.uk> |
| License: | GPL (≥ 3) |
| URL: | https://github.com/jcussens/tailoring |
| NeedsCompilation: | yes |
| CRAN checks: | fastpolicytree results |
Documentation:
| Reference manual: | fastpolicytree.pdf |
Downloads:
| Package source: | fastpolicytree_1.0.tar.gz |
| Windows binaries: | r-devel: not available, r-release: fastpolicytree_1.0.zip, r-oldrel: fastpolicytree_1.0.zip |
| macOS binaries: | r-release (arm64): fastpolicytree_1.0.tgz, r-oldrel (arm64): fastpolicytree_1.0.tgz, r-release (x86_64): fastpolicytree_1.0.tgz, r-oldrel (x86_64): fastpolicytree_1.0.tgz |
Linking:
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