Package: DebiasInfer 0.2

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) <arxiv:2309.06429>.

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

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DebiasInfer.pdf |DebiasInfer.html✨
DebiasInfer/json (API)

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

Peer review:

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

On CRAN:

1.00 score 166 downloads 5 exports 85 dependencies

Last updated 1 years agofrom:41108ed379. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 02 2024
R-4.5-winOKNov 02 2024
R-4.5-linuxOKNov 02 2024
R-4.4-winOKNov 02 2024
R-4.4-macOKNov 02 2024
R-4.3-winOKNov 02 2024
R-4.3-macOKNov 02 2024

Exports:DebiasProgDebiasProgCVDualCDDualObjSoftThres

Dependencies:bitbit64caretclarabelclasscliclockcodetoolscolorspacecpp11CVXRdata.tablediagramdigestdplyre1071ECOSolveRfansifarverforeachfuturefuture.applygenericsggplot2globalsgluegmpgowergtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmgcvModelMetricsmunsellnlmennetnumDerivosqpparallellypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6RColorBrewerRcppRcppEigenrecipesreshape2rlangRmpfrrpartscalesscsshapeSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr