Nothing
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>.
Getting started
Browse package contents
Package details |
|
|---|---|
| Author | James Cussens [aut, cre] (ORCID: <https://orcid.org/0000-0002-1363-2336>), Julia Hatamyar [ctb], Vishalie Shah [ctb], University of Bristol [cph], MRC [fnd] |
| Maintainer | James Cussens <james.cussens@bristol.ac.uk> |
| License | GPL (>= 3) |
| Version | 1.0 |
| URL | https://github.com/jcussens/tailoring |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the fastpolicytree package in your browser
Any scripts or data that you put into this service are public.
