Hi

I would think this could occur only in a special case where a mixture
model approach can be used. The data would need to be from three different
multivariate normal distributions, each with the same covariance matrix.
If you do a web search on 'mixture models' you will come up with the
information you need.

I don't know of and can't imagine any type of hierarchical or scaling
approach that could be used.


Bill
---

William D. Shannon, Ph.D.

Assistant Professor of Biostatistics in Medicine
Division of General Medical Sciences and Biostatistics

Washington University School of Medicine
Campus Box 8005, 660 S. Euclid
St. Louis, MO   63110

Phone: 314-454-8356
Fax: 314-454-5113
e-mail: [log in to unmask]
web page: http://ilya.wustl.edu/~shannon


On Wed, 23 Oct 2002, Marinucci, Max (MB Ergo) wrote:

> Dear all
>
>
> I would like to know if there is some clustering provedure which does the
> following.Given a data set with n observations on k variables with
> correlations matrix R (k x k) I would like to obtain 3 cluster of
> approximatively equal size n1=n2=n3 that satisfy the following condition.
>
>
> The correlations matrix of each of the three subgroups should be as close as
> possible each other and with respect to the pooled correlation matrix, That
> is R1=R2=R3=R
>
>
> Do you have any suggestions or ideas on how to proceed to obtain such
> partitions?
>
>
> Thanx a lot
>
>
> Massimiliano Marinucci
>
>
> Phd candidate
>
>
> Universidad Complutense Madrid
>
>
>
>
>
>
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