BaseLambdaValue

CalcDegrees

CheckClassLoss

ClassNum2Indic

draw.edges

get.label.index.list

Gplot.edge

Gplot.graphics

Gplot.network

Gplot.vertex

Gplot.vertex.label

grey.palette

IC.Estep

IC.Mstep

isolate.vertices

light.palette

lnFLaplace

Mplot.env

SimConnectivity

SimGaussianVector

SimPrecMat

SpectralClustering

sub.param

ticks.space

weighted.median

internal

simone-internal

The SIMoNe algorithm iteratively combines edge estimation
        and node classification on the basis of a mixture model for
        edge weight distributions. Edges inference may be managed via
        two alternative methods: GLasso and Meinhausan-Buhlman's
        approach. Node Classification is managed by MixNet, a mixture
        model for random graphs.

simone-internal: 'simone' internal functions

Description

Arguments

Details