My feeling is that heatmap is not the right thing to use on a correlation
matrix. The heatmap function expects a data matrix, and does a two-way
clustering of cases and variables. It tries to rearrange the rows and
columns so that similar colors are closer together. This obviously will not
work for a correlation matrix.
There are several different ways you might organize the rows and columns of a correlation matrix, but rearranging it to put equal correlations together sounds like one sensible idea. You'd probably want row and column labels rather than the dendrogram heatmap() puts on, but other than that, it seems like a nice idea to me.
Duncan Murdoch
My American Statistician paper, @Article{Friendly:02:corrgram, author = "M. Friendly", year = "2002", journal = TAS, volume = 56, number = 4, pages = "316--324", title = "Corrgrams: Exploratory displays for correlation matrices", url = "http://www.math.yorku.ca/SCS/Papers/corrgram.pdf";, }
defines a simple scheme for reordering a correlation matrix (or R^-1, for conditional independence) based
on angles of the first two eigenvectors. A variety
of rendering schemes is also described. There's a SAS macro at
* Doc: http://www.math.yorku.ca/SCS/sasmac/corrgram.html *
--
Michael Friendly Email: [EMAIL PROTECTED] Professor, Psychology Dept.
York University Voice: 416 736-5115 x66249 Fax: 416 736-5814
4700 Keele Street http://www.math.yorku.ca/SCS/friendly.html
Toronto, ONT M3J 1P3 CANADA
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