R: Plot Various Graph Statistics Over a Network MDS

gdist.plotstats {sna} | R Documentation

## Plot Various Graph Statistics Over a Network MDS

### Description

Plots a two-dimensional metric MDS of `d`, with the corresponding values of `meas` indicated at each point. Various options are available for controlling how `meas` is to be displayed.

### Usage

    gdist.plotstats(d, meas, siz.lim=c(0, 0.15), rescale="quantile",
        display.scale="radius", display.type="circleray", cex=0.5, pch=1,
        labels=NULL, pos=1, labels.cex=1, legend=NULL, legend.xy=NULL,
        legend.cex=1, ...)

### Arguments

`d` | A matrix containing the inter-graph distances
`meas` | An nxm matrix containing the graph-level measures; each row must correspond to a graph, and each column must correspond to an index
`siz.lim` | The minimum and maximum sizes (respectively) of the plotted symbols, given as fractions of the total plotting range
`rescale` | One of “quantile” for ordinal scaling, “affine” for max-min scaling, and “normalize” for rescaling by maximum value; these determine the scaling rule to be used in sizing the plotting symbols
`display.scale` | One of “area” or “radius”; this controls the attribute of the plotting symbol which is rescaled by the value of `meas`
`display.type` | One of “circle”, “ray”, “circleray”, “poly”, or “polyray”; this determines the type of plotting symbol used (circles, rays, polygons, or come combination of these)
`cex` | Character expansion coefficient
`pch` | Point types for the base plotting symbol (not the expanded symbols which are used to indicate `meas` values)
`labels` | Point labels, if desired
`pos` | Relative position of labels (see `par`)
`labels.cex` | Character expansion factor for labels
`legend` | Add a legend?
`legend.xy` | x,y coordinates for legend
`legend.cex` | Character expansion factor for legend
`...` | Additional arguments to `plot`

### Details

`gdist.plotstats` works by performing an MDS (using `cmdscale`) on `d`, and then using the values in `meas` to determine the shape of the points at each MDS coordinate. Typically, these shapes involve rays of varying color and length indicating `meas` magnitude, with circles and polygons of the appropriate radius and/or error being options as well. Various options are available (described above) to govern the details of the data display; some tinkering may be needed in order to produce an aesthetically pleasing visualization.

The primary use of `gdist.plotstats` is to explore broad relationships between graph properties and inter-graph distances. This routine complements others in the `gdist` and `gclust` family of interstructural visualization tools.

### Value

None

### Note

This routine does not actually depend on the data's being graphic in origin, and can be used with any distance matrix/measure matrix combination.

### 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

`gdist.plotdiff`, `gclust.boxstats`, `gclust.centralgraph`

### Examples

    #Generate random graphs with varying density
    g<-rgraph(10,20,tprob=runif(20,0,1))

    #Get Hamming distances between graphs
    g.h<-hdist(g)

    #Plot the association of distance, density, and reciprocity
    gdist.plotstats(g.h,cbind(gden(g),grecip(g)))

[Package sna version 2.4 Index]