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RidgeLRGLH: Ridge-Regularized Largest Root Tests for General Linear Hypotheses

Tests general linear hypotheses in high-dimensional multivariate regression using a ridge-regularized largest root statistic. Estimates the population spectral distribution by linear programming and computes Tracy-Widom centering and scaling constants. Supports fixed, Bayesian, and minimax regularization choices. Implements the methods of Li (2025) <doi:10.48550/arXiv.2504.15510>.

Version: 0.1.0
Depends: R (≥ 4.1.0)
Imports: lpSolve, RMTstat, stats
Published: 2026-10-28
DOI: 10.32614/CRAN.package.RidgeLRGLH
Author: Haoran Li [aut, cre]
Maintainer: Haoran Li <hzl0152 at auburn.edu>
License: MIT + file LICENSE
NeedsCompilation: no
Citation: RidgeLRGLH citation info
Materials: README, NEWS
CRAN checks: RidgeLRGLH results

Documentation:

Reference manual: RidgeLRGLH.html , RidgeLRGLH.pdf
Vignettes: RidgeLRGLH: Testing General Linear Hypotheses (source, R code)

Downloads:

Package source: RidgeLRGLH_0.1.0.tar.gz
Windows binaries: r-devel: RidgeLRGLH_0.1.0.zip, r-release: RidgeLRGLH_0.1.0.zip, r-oldrel: not available
macOS binaries: r-release (arm64): RidgeLRGLH_0.1.0.tgz, r-oldrel (arm64): RidgeLRGLH_0.1.0.tgz, r-release (x86_64): RidgeLRGLH_0.1.0.tgz, r-oldrel (x86_64): RidgeLRGLH_0.1.0.tgz

Linking:

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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.