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 / eBIC) or crossvalidation.

Version: 0.1.2
Imports: parallel, igraph, qgraph
Suggests: mvtnorm, JGL, psych
Published: 2017-03-20
Author: Giulio Costantini, Sacha Epskamp
Maintainer: Giulio Costantini <giulio.costantini at unimib.it>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: EstimateGroupNetwork results

Downloads:

Reference manual: EstimateGroupNetwork.pdf
Package source: EstimateGroupNetwork_0.1.2.tar.gz
Windows binaries: r-devel: EstimateGroupNetwork_0.1.2.zip, r-release: EstimateGroupNetwork_0.1.2.zip, r-oldrel: EstimateGroupNetwork_0.1.2.zip
OS X Mavericks binaries: r-release: EstimateGroupNetwork_0.1.2.tgz, r-oldrel: EstimateGroupNetwork_0.1.2.tgz

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