Package: GGMridge 1.5

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], Shannon T. Holloway [ctb, cre]

GGMridge_1.5.tar.gz
GGMridge_1.5.zip(r-4.7-any)GGMridge_1.5.zip(r-4.6-any)GGMridge_1.5.zip(r-4.5-any)
GGMridge_1.5.tgz(r-4.6-any)GGMridge_1.5.tgz(r-4.5-any)
GGMridge_1.5.tar.gz(r-4.7-any)GGMridge_1.5.tar.gz(r-4.6-any)
GGMridge_1.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
GGMridge/json (API)

# 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.

1.98 score 2 packages 16 scripts 434 downloads 1 mentions 13 exports 2 dependencies

Last updated from:41204b6c7b. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK116
source / vignettesOK140
linux-releaseOK114
macos-releaseOK109
macos-oldrelOK105
windows-develOK74
windows-releaseOK62
windows-oldrelOK73
wasm-releaseOK88

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

Dependencies:MASSmvtnorm