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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.

Functions (5)

BootTable

Summary table for a bootstrapped Joint Graphical Lasso model

EstimateGroupNetwork

Estimate Joint Graphical Lasso model on data collected on observations from different groups.

GroupBootPlot

Create a plot of bootstrapped confidence intervals for all edges of a Joint Graphical Lasso model.

GroupNetworkBoot

Compute bootstrap networks for a Joint Graphical Lasso model on data collected on observations from different groups.

covNoBessel

Covariance matrix without Bessel's correction

EstimateGroupNetwork

Perform the Joint Graphical Lasso and Selects Tuning Parameters

v0.3.1

GPL (>= 2)

Authors

Giulio Costantini, Nils Kappelmann, Sacha Epskamp

Initial release

EstimateGroupNetwork

Functions (5)

EstimateGroupNetwork

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