[R] hierarhical cluster analysis of groups of vectors
Prof Brian Ripley
ripley at stats.ox.ac.uk
Tue May 29 14:56:48 CEST 2007
On Tue, 29 May 2007, Anders Malmendal wrote:
> The vectors are produced by PLS-discriminant analysis between groups and
> the vectors within a group are simply different measurements of the same
> thing. What I need is a measure of how the different groups cluster
> (relative to each other). (I assume that I can do some averaging after
> applying dist, but I can not find the information on how to do it.)
I don't think anyone can tell you that: it is a matter of judgement.
What you need is a dissimilarity on your groups.
Assuming your vectors are numeric (you didn't say) you could use
Mahalanobis distance between the centroids, with within-group covariance
as the variance matrix. Often that works well, but not always, and you
might prefer Euclidean distance between centroids, or minimum Euclidean or
Mahalanobis distance ....
> Best regards
> Rafael Duarte wrote:
>> It seems that you have already groups defined.
>> Discriminant analysis would probably be more appropriate for what you
>> Best regards,
>> Rafael Duarte
>> Anders Malmendal wrote:
>>> I want to do hierarchical cluster analysis to compare 10 groups of
>>> vectors with five vectors in each group (i.e. I want to make a
>>> dendogram showing the clustering of the different groups). I've
>>> looked into using dist and hclust, but cannot see how to compare the
>>> different groups instead of the individual vectors. I am thankful for
>>> any help.
>>> R-help at stat.math.ethz.ch mailing list
>>> PLEASE do read the posting guide
>>> and provide commented, minimal, self-contained, reproducible code.
Brian D. Ripley, ripley at stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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