Package: DebiasInfer 0.2.1

DebiasInfer: Efficient Inference on High-Dimensional Linear Model with Missing Outcomes

A statistically and computationally efficient debiasing method for conducting valid inference on the high-dimensional linear regression function with missing outcomes. The reference paper is Zhang, Giessing, and Chen (2023) <doi:10.48550/arXiv.2309.06429>.

Authors:Yikun Zhang [aut, cre], Alexander Giessing [aut], Yen-Chi Chen [aut]

DebiasInfer_0.2.1.tar.gz
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DebiasInfer_0.2.1.tgz(r-4.6-any)DebiasInfer_0.2.1.tgz(r-4.5-any)
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manual.pdf |manual.html✨
card.svg |card.png
DebiasInfer/json (API)

# Install 'DebiasInfer' in R:
install.packages('DebiasInfer', repos = c('https://zhangyk8.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/zhangyk8/debias-infer/issues

On CRAN:

Conda:

2.14 score 14k downloads 5 exports 83 dependencies

Last updated from:2cda05a420. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK179
source / vignettesOK200
linux-release-x86_64OK204
macos-release-arm64OK297
macos-oldrel-arm64OK244
windows-develOK172
windows-releaseOK115
windows-oldrelOK115
wasm-releaseOK139

Exports:DebiasProgDebiasProgCVDualCDDualObjSoftThres

Dependencies:backportscaretcheckmateclarabelclasscliclockcodetoolscpp11CVXRdata.tablediagramdigestdplyre1071farverforeachfuturefuture.applygenericsggplot2globalsgluegmpgowergtablehardhathighsipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixModelMetricsnlmennetnumDerivosqpparallellypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6RColorBrewerRcppRcppEigenrecipesreshape2rlangrpartS7scalesscsshapeslamsparsevctrsSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr