[Presuming you mean monotone; many matrices are already monotonous.]
General solutions to this problem are discussed in
@ARTICLE{Friendly:02:corrgram,
author = {M. Friendly},
title = {Corrgrams: Exploratory displays for correlation matrices},
journal = {The American Statistician},
year = {2002},
volume = {56},
pages = {316--324},
number = {4},
url = {http://www.math.yorku.ca/SCS/Papers/corrgram.pdf},
}
and implemented (in SAS)
http://www.math.yorku.ca/SCS/sasmac/corrgram.html
Rather than just the first principal component, it is usually better
to order the variables by the angles between the first 2 PC,
corresponding to their order around a 2D biplot, using
sort(atan(V2/V1))
-Michael
[EMAIL PROTECTED] wrote:
> Spencer Graves a écrit :
>
>
>> I agree it would be great to sort the variables in a correlation
>>matrix to make it easier to read and see patterns. I don't know any
>>functions for doing that. If it were my problem, I might "order" the
>>variables by their first principal component. There may also be some
>>cluster analysis way to do that, but I don't know it well enough to say.
>> Hope this helps.
>> Spencer Graves
>
>
> Thanks for your answer Spencer.
>
> Here is a first result of a very simple and naive approach.
> http://7d4.com/r/
>
> Of course, there is no assumption the sorting is "optimal",
> but on this little example it helps the matrix being
> more readable.
>
> Vincent
>
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--
Michael Friendly Email: friendly AT yorku DOT ca
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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