Dear Brett,
If the problem is separating size and shape, then, fortunately, in my edited
book titled Morphometrics- Applications in Biology and Paleontology
(Springer-Verlag, 2004) you will find a chapter that is written by
Garcia-Rodriguez et al. They used the Sheared PCA analysis and could
There is a method called common PCA which seems to overcome the problem of
non-multinormality of overall sample that includes several subsamples all
with different central momenta. The source to read is:
Flury B. 1988. Common principal components and relatÅd multivariate models.
NY: Wiley. 258 p.
Just a comment on this one, from a pragmatic point of view.
It is of course true that PCA is only *guaranteed* to
produce components maximizing variance if you have
multivariate normality. The theory of PCA is based on this
assumption. But in many cases, PCA is used purely as a
visualization
