Hello,
we have a large data set of water quality data and want to identify
influence variables or *why* different groups of data are different (in
an explorative sense).
We consider to use biplots, however there are only the common
PCA-Biplots available in R (biplot.princomp).
We consider to use transformations (log-type, x^a, Box-Cox), but are
seeking for alternatives.
Are there experiences or comments about using something like a
* PCA with rank-transformed data,
* other transformations, or does anybody have
* R-code to produce a biplot with MDS-like methods
* or a suggestion for a "global alternative" method?
Thank you in advance!
Thomas Petzoldt
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