Package: polle 1.6.0
polle: Policy Learning
Package for learning and evaluating (subgroup) policies via doubly robust loss functions. Policy learning methods include doubly robust blip/conditional average treatment effect learning and sequential policy tree learning. Methods for (subgroup) policy evaluation include doubly robust cross-fitting and online estimation/sequential validation. See Nordland and Holst (2022) <doi:10.48550/arXiv.2212.02335> for documentation and references.
Authors:
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polle.pdf |polle.html✨
polle/json (API)
NEWS
# Install 'polle' in R: |
install.packages('polle', repos = c('https://andreasnordland.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/andreasnordland/polle/issues
Last updated 1 days agofrom:c0e3194fba. Checks:6 OK, 3 NOTE. Indexed: yes.
Target | Result | Latest binary |
---|---|---|
Doc / Vignettes | OK | Mar 28 2025 |
R-4.5-win | NOTE | Mar 28 2025 |
R-4.5-mac | NOTE | Mar 28 2025 |
R-4.5-linux | NOTE | Mar 28 2025 |
R-4.4-win | OK | Mar 28 2025 |
R-4.4-mac | OK | Mar 28 2025 |
R-4.4-linux | OK | Mar 28 2025 |
R-4.3-win | OK | Mar 28 2025 |
R-4.3-mac | OK | Mar 28 2025 |
Exports:Allconditionalcontrol_blipcontrol_drqlcontrol_earlcontrol_owlcontrol_ptlcontrol_rwlcopy_policy_dataestimatefit_g_functionsg_empirg_glmg_glmnetg_rfg_slg_xgboostget_action_setget_actionsget_g_functionsget_historyget_history_namesget_idget_id_stageget_Kget_nget_policyget_policy_actionsget_policy_functionsget_policy_objectget_q_functionsget_stage_action_setsget_utilityICpartialpolicy_datapolicy_defpolicy_evalpolicy_eval_onlinepolicy_learnq_glmq_glmnetq_rfq_slq_xgboostsim_multi_stagesim_single_stagesim_single_stage_multi_actionssim_two_stagesim_two_stage_multi_actionssubset_id
Dependencies:BHbitopscaToolsclicodetoolscvAUCdata.tabledfoptimDiceKrigingdigestDynTxRegimeforeachfuturefuture.applygamglobalsgplotsgrfgtoolsiteratorskernlabKernSmoothlatticelavalistenvlmtestMatrixmetsmodelObjmvtnormnloptrnnlsnumDerivoptimxparallellypolicytreepracmaprogressrR6RcppRcppArmadilloRcppEigenrgenoudrlangROCRsandwichSQUAREMSuperLearnersurvivaltargetedtimeregzoo
Estimating and Evaluating the Optimal Subgroup
Rendered fromoptimal_subgroup.Rmd
usingknitr::rmarkdown
on Mar 28 2025.Last update: 2024-07-29
Started: 2024-07-11
policy_data
Rendered frompolicy_data.Rmd
usingknitr::rmarkdown
on Mar 28 2025.Last update: 2024-04-23
Started: 2024-04-23
policy_eval
Rendered frompolicy_eval.Rmd
usingknitr::rmarkdown
on Mar 28 2025.Last update: 2024-07-26
Started: 2024-04-23
policy_learn
Rendered frompolicy_learn.Rmd
usingknitr::rmarkdown
on Mar 28 2025.Last update: 2024-04-23
Started: 2024-04-23