centralgraph {sna} | R Documentation

## Find the Central Graph of a Labeled Graph Stack

### Description

Returns the central graph of a set of labeled graphs, i.e. that graph in which i->j iff i->j in >=50% of the graphs within the set. If `normalize==TRUE`, then the value of the i,jth edge is given as the proportion of graphs in which i->j.

### Usage

    centralgraph(dat, normalize=FALSE)

### Arguments

`dat` | one or more input graphs.
`normalize` | boolean indicating whether the results should be normalized. The result of this is the "mean matrix". By default, `normalize==FALSE`.

### Details

The central graph of a set of graphs S is that graph C which minimizes the sum of Hamming distances between C and G in S. As such, it turns out (for the dichotomous case, at least), to be analogous to both the mean and median for sets of graphs. The central graph is useful in a variety of contexts; see the references below for more details.

### Value

A matrix containing the central graph (or mean matrix)

### Note

0.5 is used as the cutoff value regardless of whether or not the data is dichotomous (as is tacitly assumed). The routine is unaffected by data type when `normalize==TRUE`.

### Author(s)

Carter T. Butts buttsc@uci.edu

### References

Banks, D.L., and Carley, K.M. (1994). ``Metric Inference for Social Networks.'' Journal of Classification, 11(1), 121-49.

### See Also

`hdist`

### Examples

    #Generate some random graphs
    dat<-rgraph(10,5)
    #Find the central graph
    cg<-centralgraph(dat)
    #Plot the central graph
    gplot(cg)
    #Now, look at the mean matrix
    cg<-centralgraph(dat,normalize=TRUE)
    print(cg)

[Package sna version 1.1 Index]