First of all, Hi to everybody out there, I am knew on this list. To cut
my story short, I would like to know if there is any way to run a
nonparametric PCA.
The electrophysiological data I am working with are usually ln
or sqrt transformed to normalize distribution. However, this procedure
does no
good on the resulting PCA loadings. Similar to a PCA on a correlation
matrix, the resulting factor loadings do not any more reflect underlying
physiological characteristics and are difficult to interpret. On the
other hand, a PCA using a covariance matrix on raw (or sqrt transformed)
data reflects the underlying physiological processes quite well and is
nicely reproducable.
Taken together, normalization as well as z-transformation due to corr
(instead of cova) has a bad influence on the interpretability of the
resulting factor loadings.
I would greatly appreciate any comments.
Thanks,
Stefan
_________
Stefan Debener
Department of Psychology II
Dresden University of Technology
Germany
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