sna (version 2.4)

gclust.centralgraph: Get Central Graphs Associated with Graph Clusters

Description

Calculates central graphs associated with particular graph clusters (as indicated by the k partition of h).

Usage

gclust.centralgraph(h, k, dat, ...)

Arguments

h

an hclust object, based on a graph stack in dat.

k

the number of groups to evaluate.

dat

one or more graphs (on which the clustering was performed).

…

additional arguments to centralgraph.

Value

An array containing the stack of central graph adjacency matrices

Details

gclust.centralgraph uses cutree to cut the hierarchical clustering in h into k groups. centralgraph is then called on each cluster, and the results are returned as a graph stack. This is a useful tool for interpreting clusters of (labeled) graphs, with the resulting central graphs being subsequently analyzed using standard SNA methods.

References

Butts, C.T., and Carley, K.M. (2001). ``Multivariate Methods for Interstructural Analysis.'' CASOS working paper, Carnegie Mellon University.

See Also

hclust, centralgraph, gclust.boxstats, gdist.plotdiff, gdist.plotstats

Examples

# NOT RUN {
#Create some random graphs
g<-rgraph(10,20,tprob=c(rbeta(10,15,2),rbeta(10,2,15)))

#Find the Hamming distances between them
g.h<-hdist(g)

#Cluster the graphs via their Hamming distances
g.c<-hclust(as.dist(g.h))

#Now find central graphs by cluster for a two cluster solution
g.cg<-gclust.centralgraph(g.c,2,g)

#Plot the central graphs
gplot(g.cg[1,,])
gplot(g.cg[2,,])
# }