SIHR: Statistical Inference in High Dimensional Regression

Inference procedures in the high-dimensional setting for (1) linear functionals and quadratic functionals in linear regression ('Cai et al.' (2019) <arXiv:1904.12891>, 'Guo et al.' (2019) <arXiv:1909.01503>), (2) linear functional in logistic regression ('Guo et al.' <arXiv:2012.07133>), (3) individual treatment effects in linear and logistic regression, (4) single regression coefficient in binary outcome regression.

Version: 0.2.0
Imports: CVXR, Matrix, glmnet, Rdpack, scalreg, qpdf
Suggests: knitr, rmarkdown, MASS
Published: 2021-10-07
Author: Prabrisha Rakshit [aut, cre], Tony Cai [aut], Zijian Guo [aut]
Maintainer: Prabrisha Rakshit <prabrisha.rakshit at rutgers.edu>
BugReports: https://github.com/prabrishar1/SIHR/issues
License: GPL-3
URL: https://github.com/prabrishar1/SIHR
NeedsCompilation: no
Materials: README
CRAN checks: SIHR results

Documentation:

Reference manual: SIHR.pdf
Vignettes: SIHR

Downloads:

Package source: SIHR_0.2.0.tar.gz
Windows binaries: r-devel: SIHR_0.2.0.zip, r-release: SIHR_0.2.0.zip, r-oldrel: SIHR_0.2.0.zip
macOS binaries: r-release (arm64): SIHR_0.2.0.tgz, r-oldrel (arm64): SIHR_0.2.0.tgz, r-release (x86_64): SIHR_0.2.0.tgz, r-oldrel (x86_64): SIHR_0.2.0.tgz
Old sources: SIHR archive

Reverse dependencies:

Reverse imports: hierbase, MaximinInfer

Linking:

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