Package: GGMridge 1.4

GGMridge: Gaussian Graphical Models Using Ridge Penalty Followed by Thresholding and Reestimation

Estimation of partial correlation matrix using ridge penalty followed by thresholding and reestimation. Under multivariate Gaussian assumption, the matrix constitutes an Gaussian graphical model (GGM).

Authors:Min Jin Ha [aut, cre], Shannon T. Holloway [ctb]

GGMridge_1.4.tar.gz
GGMridge_1.4.zip(r-4.5)GGMridge_1.4.zip(r-4.4)GGMridge_1.4.zip(r-4.3)
GGMridge_1.4.tgz(r-4.5-any)GGMridge_1.4.tgz(r-4.4-any)GGMridge_1.4.tgz(r-4.3-any)
GGMridge_1.4.tar.gz(r-4.5-noble)GGMridge_1.4.tar.gz(r-4.4-noble)
GGMridge_1.4.tgz(r-4.4-emscripten)GGMridge_1.4.tgz(r-4.3-emscripten)
GGMridge.pdf |GGMridge.html✨
GGMridge/json (API)
NEWS

# Install 'GGMridge' in R:
install.packages('GGMridge', repos = c('https://sth1402.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.89 score 2 packages 13 scripts 224 downloads 1 mentions 13 exports 2 dependencies

Last updated 1 years agofrom:c01a137a5e. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 18 2025
R-4.5-winOKMar 18 2025
R-4.5-macOKMar 18 2025
R-4.5-linuxOKMar 18 2025
R-4.4-winOKMar 18 2025
R-4.4-macOKMar 18 2025
R-4.4-linuxOKMar 18 2025
R-4.3-winOKMar 18 2025
R-4.3-macOKMar 18 2025

Exports:EM.mixturegetEfronpksStatlambda.cvlambda.pcut.cvlambda.pcut.cv1lambda.TargetDne.lambda.cvR.separate.ridgescaledMatsimulateDatastructuredEstimatetransFisher

Dependencies:MASSmvtnorm