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EstimateGroupNetwork: Perform the Joint Graphical Lasso and Selects Tuning Parameters

Can be used to simultaneously estimate networks (Gaussian Graphical Models) in data from different groups or classes via Joint Graphical Lasso. Tuning parameters are selected via information criteria (AIC / BIC / extended BIC) or cross validation.

Version: 0.3.1
Imports: parallel, igraph, qgraph, dplyr, ggplot2, stats
Suggests: mvtnorm, JGL, psych
Published: 2021-02-10
DOI: 10.32614/CRAN.package.EstimateGroupNetwork
Author: Giulio Costantini, Nils Kappelmann, Sacha Epskamp
Maintainer: Giulio Costantini <giulio.costantini at unimib.it>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: EstimateGroupNetwork citation info
Materials: NEWS
In views: Psychometrics
CRAN checks: EstimateGroupNetwork results

Documentation:

Reference manual: EstimateGroupNetwork.pdf

Downloads:

Package source: EstimateGroupNetwork_0.3.1.tar.gz
Windows binaries: r-devel: EstimateGroupNetwork_0.3.1.zip, r-release: EstimateGroupNetwork_0.3.1.zip, r-oldrel: EstimateGroupNetwork_0.3.1.zip
macOS binaries: r-release (arm64): EstimateGroupNetwork_0.3.1.tgz, r-oldrel (arm64): EstimateGroupNetwork_0.3.1.tgz, r-release (x86_64): EstimateGroupNetwork_0.3.1.tgz, r-oldrel (x86_64): EstimateGroupNetwork_0.3.1.tgz
Old sources: EstimateGroupNetwork archive

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.