Package: rdlearn 0.1.1

Kentaro Kawato

rdlearn: Safe Policy Learning under Regression Discontinuity Design with Multiple Cutoffs

Implements safe policy learning under regression discontinuity designs with multiple cutoffs, based on Zhang et al. (2022) <doi:10.48550/arXiv.2208.13323>. The learned cutoffs are guaranteed to perform no worse than the existing cutoffs in terms of overall outcomes. The 'rdlearn' package also includes features for visualizing the learned cutoffs relative to the baseline and conducting sensitivity analyses.

Authors:Kentaro Kawato [cre, cph], Yi Zhang [aut], Soichiro Yamauchi [aut], Eli Ben-Michael [aut], Kosuke Imai [aut]

rdlearn_0.1.1.tar.gz
rdlearn_0.1.1.tar.gz(r-4.5-noble)rdlearn_0.1.1.tar.gz(r-4.4-noble)
rdlearn_0.1.1.tgz(r-4.4-emscripten)rdlearn_0.1.1.tgz(r-4.3-emscripten)
rdlearn.pdf |rdlearn.html
rdlearn/json (API)
NEWS

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

Bug tracker:https://github.com/kkawato/rdlearn/issues

Datasets:

2.70 score 5 exports 36 dependencies

Last updated 23 days agofrom:b601454582. Checks:2 OK. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKJan 29 2025
R-4.5-linuxOKJan 29 2025

Exports:plotrdestimaterdlearnsenssummary

Dependencies:clicolorspacedplyrfansifarvergenericsggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmennetnprobustpillarpkgconfigR6RColorBrewerRcppRcppArmadillordrobustrlangscalestibbletidyselectutf8vctrsviridisLitewithr

Replication by rdlearn

Rendered fromreplication.Rmdusingknitr::rmarkdownon Jan 29 2025.

Last update: 2025-01-29
Started: 2025-01-29