R: Plot Statistics Associated with Graph Clusters

gclust.boxstats {sna} | R Documentation

## Plot Statistics Associated with Graph Clusters

### Description

`gclust.boxstats` creates side-by-side boxplots of graph statistics based on a hierarchical clustering of networks (cut into `k` sets).

### Usage

    gclust.boxstats(h, k, meas, ...)

### Arguments

`h` | an `hclust` object, presumably formed by clustering a set of structural distances.
`k` | the number of groups to evaluate.
`meas` | a vector of length equal to the number of graphs in `h`, containing a GLI to be evaluated.
`...` | additional parameters to `boxplot`.

### Details

`gclust.boxstats` simply takes the `hclust` object in `h`, applies `cutree` to form `k` groups, and then uses `boxplot` on the distribution of `meas` by group. This can be quite handy for assessing graph clusters.

### Value

None

### Note

Actually, this function will work with any `hclust` object and measure matrix; the data need not originate with social networks. For this reason, the clever may also employ this function in conjunction with `sedist` or `equiv.clust` to plot NLIs against clusters of positions within a graph.

### 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

`gclust.centralgraph`, `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 display boxplots of density by cluster for a two cluster solution
    gclust.boxstats(g.c,2,gden(g))

[Package sna version 2.4 Index]