Anders;
If you want to _test_ for differences, ANOVA applied to on the (typically)
first principal component scores for each object would give a fairly quick
indication of whether there was a case to answer (though scaling is an issue to
be aware of; a low-variance variable might differ strong
On Tue, 29 May 2007, Anders Malmendal wrote:
> Thanks.
> 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 oth
Thanks.
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
ap
Thanks.
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. (I
assume that I can do some averaging after applying dist, but I can not
It seems that you have already groups defined.
Discriminant analysis would probably be more appropriate for what you want.
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 wa
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
