Package: DRDRtest 0.1

DRDRtest: A Nonparametric Doubly Robust Test for Continuous Treatment Effect

Implement the statistical test proposed in Weng et al. (2021) to test whether the average treatment effect curve is constant and whether a discrete covariate is a significant effect modifier.

Authors:Guangwei Weng [aut, cre]

DRDRtest_0.1.tar.gz
DRDRtest_0.1.zip(r-4.7)DRDRtest_0.1.zip(r-4.6)DRDRtest_0.1.zip(r-4.5)
DRDRtest_0.1.tgz(r-4.6-any)DRDRtest_0.1.tgz(r-4.5-any)
DRDRtest_0.1.tar.gz(r-4.7-any)DRDRtest_0.1.tar.gz(r-4.6-any)
DRDRtest_0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
DRDRtest/json (API)

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

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 57 downloads 6 exports 14 dependencies

Last updated from:2c26c56b78. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK132
source / vignettesOK117
linux-release-x86_64OK100
macos-release-arm64OK130
macos-oldrel-arm64OK178
windows-develOK102
windows-releaseOK57
windows-oldrelOK122
wasm-releaseOK104

Exports:drdrtestdrdrtest_emdrdrtest_em.basedrdrtest_em.superlearnerdrdrtest.basedrdrtest.superlearner

Dependencies:bitopscaToolscodetoolscvAUCdata.tableforeachgamgplotsgtoolsiteratorsKernSmoothnnlsROCRSuperLearner