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>.

Version: 0.2
Imports: CVXR, caret, stats
Suggests: MASS, glmnet
Published: 2023-10-09
DOI: 10.32614/CRAN.package.DebiasInfer
Author: Yikun Zhang ORCID iD [aut, cre], Alexander Giessing ORCID iD [aut], Yen-Chi Chen ORCID iD [aut]
Maintainer: Yikun Zhang <yikunzhang at>
License: MIT + file LICENSE
NeedsCompilation: no
CRAN checks: DebiasInfer results


Reference manual: DebiasInfer.pdf


Package source: DebiasInfer_0.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): DebiasInfer_0.2.tgz, r-oldrel (arm64): DebiasInfer_0.2.tgz, r-release (x86_64): DebiasInfer_0.2.tgz, r-oldrel (x86_64): DebiasInfer_0.2.tgz
Old sources: DebiasInfer archive


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