Package: polle
Title: Policy Learning
Version: 1.4
Authors@R: c(person(given = "Andreas",
                    family = "Nordland",
                    role = c("aut", "cre"),
                    email = "andreasnordland@gmail.com"),
             person(given = "Klaus",
                    family = "Holst",
                    role = c("aut"),
                    email = "klaus@holst.it",
                    comment = c(ORCID="0000-0002-1364-6789"))
             )
Description: Framework for evaluating user-specified finite stage policies and learning realistic policies via doubly robust loss functions. Policy learning methods include doubly robust Q-learning, sequential policy tree learning, and outcome weighted learning. See Nordland and Holst (2022) <doi:10.48550/arXiv.2212.02335> for documentation and references.
License: Apache License (>= 2)
Encoding: UTF-8
Depends: R (>= 4.0), SuperLearner
Imports: data.table (>= 1.14.5), lava (>= 1.7.0), future.apply,
        progressr, methods, policytree (>= 1.2.0), survival, targeted
        (>= 0.4), DynTxRegime
Suggests: DTRlearn2, glmnet (>= 4.1-6), mgcv, xgboost, knitr, ranger,
        rmarkdown, testthat (>= 3.0), ggplot2
RoxygenNote: 7.3.1
BugReports: https://github.com/AndreasNordland/polle/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-04-25 10:09:12 UTC; oano
Author: Andreas Nordland [aut, cre],
  Klaus Holst [aut] (<https://orcid.org/0000-0002-1364-6789>)
Maintainer: Andreas Nordland <andreasnordland@gmail.com>
Repository: CRAN
Date/Publication: 2024-04-25 10:30:02 UTC
Built: R 4.2.3; ; 2024-04-25 12:47:22 UTC; unix
