gclust.centralgraph {sna} | R Documentation

## 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`.

### 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.

### Value

An array containing the stack of central graph adjacency matrices

### Note

### Author(s)

Carter T. Butts buttsc@uci.edu

### 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

    #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,,])

[Package sna version 1.1 Index]