R: Hierarchical Graph Clustering for a Collection of Networks

# Hierarchical Graph Clustering for a Collection of Networks

## Documentation for package ‘graphclust’ version 1.3

- DESCRIPTION file

## Help Pages

ARI | Adjusted Rand index
degreeSort | Sort stochastic block model parameter in a unique way using its graphon
fitSBMcollection | Fit a unique stochastic block model to a collection of networks
fitSimpleSBM | Fit a stochastic block model to every network in a collection of networks.
graphClustering | Hierarchical graph clustering algorithm
graphMomentsClustering | Graph clustering method using graph moments
graphonL2norm | (squared) L2-norm of the graphons associated with two stochastic block model parameters
graphonSpectralClustering | Graph clustering using the pairwise graphon distances and spectral clustering
metagraph | Plot the metagraph of the parameter of the stochastic block model associated with one of the estimated graph clusters
moments | Computation of graph moments of a network
permutParam | Permute block labels of a stochastic block model parameter
plotDendrogram | Plot dendrogram to visualize the clustering obtained by the hierarchical clustering algorithm
rCollectSBM | Simulate a sample of networks of a stochastic block model
rMixSBM | Simulate a collection of networks of a mixture of stochastic block models
rsbm | Simulate a network of a stochastic block model
sampleDPA | generation of a network of the directed preferential attachment (DPA) model
sampleDPAMixture | Generation of a mixture of directed preferential attachment (DPA) models
sbmNorm | (squared) norm between two stochastic block models