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
DebiasInfer_0.2.1.zip(r-4.7-any)DebiasInfer_0.2.1.zip(r-4.6-any)DebiasInfer_0.2.1.zip(r-4.5-any)
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✨
DESCRIPTION
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:

1.00 score 479 downloads 5 exports 83 dependencies

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

TargetResultTimeFilesSyslog
linux-develOK171
source / vignettesOK209
linux-releaseOK217
macos-releaseOK158
macos-oldrelOK233
windows-develOK113
windows-releaseOK118
windows-oldrelOK133
wasm-releaseOK122

Exports:DebiasProgDebiasProgCVDualCDDualObjSoftThres

Dependencies:backportscaretcheckmateclarabelclasscliclockcodetoolscpp11CVXRdata.tablediagramdigestdplyre1071farverforeachfuturefuture.applygenericsggplot2globalsgluegmpgowergtablehardhathighsipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixModelMetricsnlmennetnumDerivosqpparallellypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6RColorBrewerRcppRcppEigenrecipesreshape2rlangrpartS7scalesscsshapeslamsparsevctrsSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr