Package: banditsCI 1.0.0

Molly Offer-Westort

banditsCI: Bandit-Based Experiments and Policy Evaluation

Frequentist inference on adaptively generated data. The methods implemented are based on Zhan et al. (2021) <doi:10.48550/arXiv.2106.02029> and Hadad et al. (2021) <doi:10.48550/arXiv.1911.02768>. For illustration, several functions for simulating non-contextual and contextual adaptive experiments using Thompson sampling are also supplied.

Authors:Molly Offer-Westort [aut, cre, cph], Yinghui Zhou [aut], Ruohan Zhan [aut]

banditsCI_1.0.0.tar.gz
banditsCI_1.0.0.tar.gz(r-4.5-noble)banditsCI_1.0.0.tar.gz(r-4.4-noble)
banditsCI_1.0.0.tgz(r-4.4-emscripten)banditsCI_1.0.0.tgz(r-4.3-emscripten)
banditsCI.pdf |banditsCI.html
banditsCI/json (API)
NEWS

# Install 'banditsCI' in R:
install.packages('banditsCI', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/uchicago-pol-methods/banditsci/issues

Pkgdown:https://uchicago-pol-methods.github.io

2.70 score 9 scripts 24 exports 14 dependencies

Last updated 8 days agofrom:51e70e2368. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 29 2024
R-4.5-linuxOKNov 29 2024

Exports:.check_A.check_first_batch.check_shapeaw_estimateaw_scoresaw_varcalculate_balwtscalculate_continuous_X_statisticsdraw_thompsonestimategenerate_bandit_dataifelse_clipimpose_floorLinTSModeloutput_estimatesplot_cumulative_assignmentridge_initridge_muhat_lfo_pairidge_updaterun_experimentsimple_tree_datastick_breakingtwopoint_stable_var_ratioupdate_thompson

Dependencies:codetoolsforeachglmnetiteratorslatticeMASSMatrixmvtnormrbibutilsRcppRcppEigenRdpackshapesurvival

Confidence interval vignette.

Rendered frombanditsCI.Rmdusingknitr::rmarkdownon Nov 29 2024.

Last update: 2024-11-29
Started: 2024-11-29