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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 stat.rutgers.edu>
BugReports: https://github.com/zywang0701/SIHR/issues
License: GPL-3
URL: https://zywang0701.github.io/SIHR/
NeedsCompilation: no
Citation: SIHR citation info
Materials: README
CRAN checks: SIHR results

Documentation:

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

Downloads:

Package source: SIHR_2.1.0.tar.gz
Windows binaries: r-devel: SIHR_2.1.0.zip, r-release: SIHR_2.1.0.zip, r-oldrel: SIHR_2.1.0.zip
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

Linking:

Please use the canonical form https://CRAN.R-project.org/package=SIHR to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.