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
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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 290 downloads 1 mentions 13 exports 2 dependencies

Last updated 1 years agofrom:c01a137a5e. Checks:8 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 16 2025
R-4.5-winOKFeb 16 2025
R-4.5-macOKFeb 16 2025
R-4.5-linuxOKFeb 16 2025
R-4.4-winOKFeb 16 2025
R-4.4-macOKFeb 16 2025
R-4.3-winOKFeb 16 2025
R-4.3-macOKFeb 16 2025

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

Dependencies:MASSmvtnorm