gdist.plotstats | R Documentation |

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.

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, ...)

`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 |

`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 |

`labels` |
Point labels, if desired |

`pos` |
Relative position of labels (see |

`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 |

`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.

None

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.

Carter T. Butts buttsc@uci.edu

Butts, C.T., and Carley, K.M. (2001). “Multivariate Methods for Interstructural Analysis.” CASOS working paper, Carnegie Mellon University.

`gdist.plotdiff`

, `gclust.boxstats`

, `gclust.centralgraph`

#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)))

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