Thanks all you wizards for your suggestions and help. The lda() and predict.lda() functions in MASS did the trick and gave me the same results (yay).
Cheers, Blake On Wednesday, August 19, 2015 at 5:40:34 PM UTC-4, Blake Dickson wrote: > > Hey Morphmetricians, > > So I have a question regarding calculating PC scores and CV scores > post-hoc: > > I have a GMM dataset of extant and fossil species which I want to plot > using PCA and CVA. I want to calculate the extant species first, then use > the eigenvectors from this the plot the scores for the fossil taxa. > > I have done this successfully for the PCA in R by centering the whole > dataset, then calculating the covariance matrix and eigenvectors for the > extant species only. I then calculate the PC scores for the fossil taxa > using these eigenvalues. > > I am not certain whether the same tactic for the CVA is valid. I have > tried it: performing the CVA (using the Morpho package) on the extant > dataset with associated groupings, then correcting the fossil coordinates > by the mean of this CVA and calculating the CV scores for the fossil taxa > using the canonical variates (CV) matrix. This gives me a result, with > plot-able CV scores for the fossil taxa, but I want to be certain the > method is valid. > > In addition, assuming that what I have done with the CVA is correct; how > would I best go about testing the likelihood of group membership for these > fossil taxa? > > Cheers all, > > Blake Dickson > -- MORPHMET may be accessed via its webpage at http://www.morphometrics.org To unsubscribe from this group and stop receiving emails from it, send an email to morphmet+unsubscr...@morphometrics.org.
