Nicolas --
 
Most of the statistical software systems have Clustering Algorithms with
a variety of objective functions.  It is certainly reasonable to use a several approaches
to help identify "OUTLIERS" or "INFLUENTIAL" observations.  The identification AND definition of an "OUTLIER" or "INFLUENTIAL" observations should be  the responsibility of the researcher who KNOWS the context of the analysis.
 
Also, regression models can be used to provide information to help the researcher
identify "OUTLIERS" or "INFLUENTIAL" observations. 
 
One approach is to LEAVE EACH OBSERVATION OUT OF THE ANALYSIS and
"test the hypothesis that the observed Y value for each of the "left-out" observations
is equal to the PREDICTED value from the other N-1 observations." The output of these
N hypotheses can be helpful.
 
The Classification Society of North America has a web site at
http://www.pitt.edu/~csna/  that might be helpful in your search about
Clustering.  A good contact is the Secretary/Treasurer of CSNA:

Stanley L. Sclove
Department of Information and Decision Sciences M/C 294
College of Business Administration
University of Illinois at Chicago
601 S. Morgan Street
Chicago, IL 60607-7124
www.uic.edu/~slsclove
Have fun!!
 
--Joe
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----- Original Message -----
From: Nicolas MEYER <[EMAIL PROTECTED]>
To: <[EMAIL PROTECTED]>
Sent: Sunday, March 12, 2000 4:52 AM
Subject: Cluster and outliers

| Hi everybody !!
|
| I'm desperately looking for books or papers on possible links beetwen
| cluster analysis and outliers, cluster being of course used to detect
| outlier(s).
| Does anybody knows anything about this ?
| Thank's !!
|
| Nicolas MEYER
| Interne en Sant� Publique
| CHU Strasbourg-FRANCE
|
|
|
|
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