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) .


Reference manual

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install.packages("fastpolicytree")

1.0 by James Cussens, a year ago


https://github.com/jcussens/tailoring


Browse source code at https://github.com/cran/fastpolicytree


Authors: James Cussens [aut, cre] (ORCID: , Julia Hatamyar [ctb] , Vishalie Shah [ctb] , University of Bristol [cph] , MRC [fnd]


Documentation:   PDF Manual  


GPL (>= 3) license


Imports Rcpp

Suggests policytree

Linking to Rcpp


See at CRAN