SIHR: Statistical Inference in High Dimensional Regression

The goal of SIHR is to provide inference procedures in the high-dimensional generalized linear regression setting for: (1) linear functionals <doi:10.48550/arXiv.1904.12891> <doi:10.48550/arXiv.2012.07133>, (2) conditional average treatment effects, (3) quadratic functionals <doi:10.48550/arXiv.1909.01503>, (4) inner product, (5) distance.

Version: 2.1.0
Imports: CVXR, glmnet, stats
Suggests: knitr, rmarkdown, R.rsp
Published: 2024-04-24
Author: Zhenyu Wang [aut], Prabrisha Rakshit [aut], Tony Cai [aut], Zijian Guo [aut, cre]
Maintainer: Zijian Guo <zijguo at>
License: GPL-3
NeedsCompilation: no
Citation: SIHR citation info
Materials: README
CRAN checks: SIHR results


Reference manual: SIHR.pdf
Vignettes: Quick Start to SIHR
Intro of Methods
Intro of Usage


Package source: SIHR_2.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): SIHR_2.1.0.tgz, r-oldrel (arm64): SIHR_2.1.0.tgz, r-release (x86_64): SIHR_2.1.0.tgz, r-oldrel (x86_64): SIHR_2.1.0.tgz
Old sources: SIHR archive

Reverse dependencies:

Reverse imports: MaximinInfer


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