[R] Weighted association map

[Gabor Grothendieck]

Actually the discretization does not appear to be needed.  This
works just as well:

set.seed(123)
kor <- cor(iris[1:4])
gplot(sign(kor), edge.lwd = 10*kor, displaylabels = TRUE, label = rownames(kor))

On 9/8/06, Gabor Grothendieck <ggrothendieck at gmail.com> wrote:
> Try the sna package.  Below we calculate the
> correlation matrix, kor, of the numeric cols of builtin iris
> dataset.  Zap negative ones and discretize rest to
> get lwd width matrix, lwd, used for edge widths.  From
> that create the adjacency matrix, sign(lwd), and plot it
> using indicated layout mode.  Seems like three of
> the variables are correlated and Sepal.Width is uncorrelated
> or negatively correlated to those. Try playing around with
> gplot args to create variations.
>
> library(sna)
> set.seed(123) # layout uses random numbers
> kor <- cor(iris[1:4])
> lwd <- replace(kor, TRUE, 10 * round(pmax(0, kor), 1))
> gplot(sign(lwd), edge.lwd = lwd, displaylabels = TRUE, label = rownames(kor))
>
> On 9/8/06, kone <attenka at utu.fi> wrote:
> > Could somebody program this kind of plot type to R, if none exists,
> > based on mds or correlation tables or some more suitable method? What
> > do you think about idea? Does it work? None similar or better exists?
> >
> > http://weightedassociationmap.blogspot.com/
> >
> >
> > Atte Tenkanen
> > University of Turku, Finland
> >
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>