Resemble allow a certain number of plots which are very useful for your works or personal papers. In this case I use the same sets than of the previous post and I plot the PCA scores, where I can see the training matrix (Xr) scores and the validation matrix (Xu) scores overlapped.
Validation set is a 35% (randomly selected) of the whole sample population obtained from a long time period.
We can see how the validation samples cover more or less the space of the training samples.
> par(mfrow=c(1,2)) > plot(local.mbl, g = "pca", pcs=c(1,2)) > plot(local.mbl, g = "pca", pcs=c(1,3))
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