Dear All,

I remember but could not find references showing the relationship
between the Mahalanobis distance and principal component analysis.  I
appreciate if anybody explain or give references.

Also, I'm wondering what is the right way of clustering observations
when variables are highly collinear?
1) Run PCA and use all of principal components for cluster analysis
2) Use the Mahalanobis distance.  

By the way, why the Mahalanobis distance is not included in books for
cluster analysis and also major softwares such as SAS, SPSS or
Minitab?  I usually work on data where many variables are collinear
and have to include those variables.  My inexperienced thought in
cluster analysis is that it would be better to use the Mahalanobis
distance if variables are collinear but most softwares do not include
it.

I appreciate any helps.  
Sangdon Lee, Ph.D,
GM Tech Center, MI, USA.
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