func.uinit

n.comp

Method used for initialization
init={'cl.init','r.means','random','kmeans','kmeans.hc','hc'}

init

Initial cluster assignments;
need to be provided if init='cl.init' (otherwise this param is ignored)

my.cl

Number of random starts in kmeans; default=1

nstart.kmeans

Maximal number of iteration in kmeans; default=10

iter.max.kmeans

modelname.hc

internal

Package nethet is an implementation of statistical solid
    methodology enabling the analysis of network heterogeneity from
    high-dimensional data. It combines several implementations of recent
    statistical innovations useful for estimation and comparison of networks in
    a heterogeneous, high-dimensional setting. In particular, we provide code
    for formal two-sample testing in Gaussian graphical models (differential
    network and GGM-GSA; Stadler and Mukherjee, 2013, 2014) and make a novel
    network-based clustering algorithm available (mixed graphical lasso,
    Stadler and Mukherjee, 2013).

func.uinit: Initialization of MixGLasso

Description

Usage

Arguments

Value