Dear All, Im working with data science and one of my favorites is PCA - Principal Component Analysis. Gnumerics is really great in many ways, but the present PCA has some weaknesses. I found the R library "mixOmics" which has a great PCA (and also PLS). This supports (among other things) :
* missing values * all matrix forms * scaling/centering * NIPALS and SVD Suggestion : Can the present PCA be replaced with the one in R "mixOmics" ? If this is of interest/possible, I would gladly help with suggestions around implementation etc. Thanks for a Great software Martin
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