PCAs with three diferent methods and projections (Test and Val Set)

The shoot-out 2012 is composed with 155 samples for the training set (Blue color), 460 for the Test Set (Red color), and other few samples for the Validation set (Green color).

I have developed 3 different ways of Principal Components Analysis and I would like to show you the score plot of PC1 vs PC2 developed with the Training Set and the projections on that space of the Test and Validation Set.

This first plot is in the case  of using PRCOMP:

Second case is using NIPALS for the calculation of the PCAs:

and third using SVD for the calculation of the PCAs

As you can see no differences, and we can have the conclussions that the Training Set cover the variability for the samples of the Test Set and Validation Set, so we don´t have to extrapolate outside the calibration space.

I will writte a post with the code (quite long) if interested. Let me know.