Package: polle
Title: Policy Learning
Version: 1.0
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 restricted Q-learning, sequential policy tree learning and outcome weighted learning. See Nordland and Holst (2022) for documentation and references.
License: Apache License (>= 2)
Encoding: UTF-8
Imports: data.table (>= 1.14.5), future.apply, lava (>= 1.7.0),
        methods, policytree (>= 1.2.0), SuperLearner, survival,
        targeted, DynTxRegime
Suggests: DTRlearn2, glmnet, mgcv, knitr, ranger, rmarkdown, testthat
        (>= 3.0)
Depends: R (>= 4.0)
RoxygenNote: 7.2.1
URL: https://arxiv.org/abs/2212.02335
BugReports: https://github.com/AndreasNordland/polle/issues
NeedsCompilation: no
Packaged: 2022-12-06 13:47:47 UTC; andreasnordland
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: 2022-12-06 17:30:02 UTC
