rMixSBM: Simulate a collection of networks of a mixture of stochastic...

In graphclust: Hierarchical Graph Clustering for a Collection of Networks

Simulate a collection of networks of a mixture of stochastic block models

Description

Simulate a collection of networks of a mixture of stochastic block models

Usage

rMixSBM(vec_n, thetaMixSBM, directed = TRUE)

Arguments

vec_n	vector with number of vertices
thetaMixSBM	K-list for a mixture with K components. Each field is a list with the stochastic block model parameter ($pi and $gamma) and a cluster proportion ($prop)
directed	directed networks (TRUE by default) or undirected (FALSE)

Value

list with a list of adjacency matrices ($listGraphs), a list of node labels ($listLatentZ) and a vector with the graph clustering ($label)

Examples

theta1 <- list(prop=.2, pi=c(.5,.5), gamma=matrix((1:4)/8,2,2))
theta2 <- list(prop=.8, pi=c(.5,.5), gamma=matrix(4:1/8,2,2))
thetaMixSBM <- list(NULL)
thetaMixSBM[[1]] <- theta1
thetaMixSBM[[2]] <- theta2
obs <- rMixSBM(vec_n=rep(10,3), thetaMixSBM)

graphclust documentation built on June 7, 2023, 5:18 p.m.