Package: ReguGLH 0.1.0

ReguGLH: General Linear Hypothesis Tests via Spectral Shrinkage

Implements high-dimensional general linear hypothesis tests using ridge, reciprocal cubic polynomial, and user-defined analytic spectral regularizers. Provides prior-based shrinkage selection and Gaussian maximum calibration for composite tests. Implements the methods of Li, Aue and Paul (2020), "High-dimensional general linear hypothesis tests via non-linear spectral shrinkage", Bernoulli, 26(4), 2541-2571 <doi:10.3150/19-BEJ1186>.

Authors:Haoran Li [aut, cre]

ReguGLH_0.1.0.tar.gz
ReguGLH_0.1.0.zip(r-4.7-any)ReguGLH_0.1.0.zip(r-4.6-any)ReguGLH_0.1.0.zip(r-4.5-any)
ReguGLH_0.1.0.tgz(r-4.6-any)ReguGLH_0.1.0.tgz(r-4.5-any)
ReguGLH_0.1.0.tar.gz(r-4.7-any)ReguGLH_0.1.0.tar.gz(r-4.6-any)
ReguGLH_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
ReguGLH/json (API)

# Install 'ReguGLH' in R:
install.packages('ReguGLH', repos = c('https://haoranli.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/haoranli/reguglh/issues

On CRAN:

Conda:

2.70 score 3 exports 0 dependencies

Last updated from:e4e2e8c835. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK96
source / vignettesOK170
linux-releaseOK91
macos-releaseOK174
macos-oldrelOK201
windows-develOK70
windows-releaseOK62
windows-oldrelOK64
wasm-releaseOK75

Exports:cubic_gridglh_testshrinkage_moments

Dependencies: