AirScreen: Feature Screening via Adaptive Iterative Ridge (Air-HOLP and Air-OLS)

Implements two complementary high-dimensional feature screening methods, Adaptive Iterative Ridge High-dimensional Ordinary Least-squares Projection (Air-HOLP, suitable when the number of predictors p is greater than or equal to the sample size n) and Adaptive Iterative Ridge Ordinary Least Squares (Air-OLS, for n greater than p). Also provides helper functions to generate compound-symmetry and AR(1) correlated data, plus a unified Air() front end and a summary method. For methodological details see Joudah, Muller and Zhu (2025) <doi:10.1007/s11222-025-10599-6>.

Version: 0.1.0
Imports: stats
Suggests: testthat (≥ 3.0.0)
Published: 2025-07-31
DOI: 10.32614/CRAN.package.AirScreen
Author: Ibrahim Joudah ORCID iD [aut, cre], Samuel Muller ORCID iD [aut], Houying Zhu ORCID iD [aut]
Maintainer: Ibrahim Joudah <ibrahim.joudah at mq.edu.au>
License: MIT + file LICENSE
URL: https://github.com/Logic314/Air-HOLP
NeedsCompilation: no
Materials: README
CRAN checks: AirScreen results

Documentation:

Reference manual: AirScreen.html , AirScreen.pdf

Downloads:

Package source: AirScreen_0.1.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: AirScreen_0.1.0.zip
macOS binaries: r-release (arm64): AirScreen_0.1.0.tgz, r-oldrel (arm64): AirScreen_0.1.0.tgz, r-release (x86_64): AirScreen_0.1.0.tgz, r-oldrel (x86_64): AirScreen_0.1.0.tgz

Linking:

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