I would consider using the lda() function from MASS package. The function allows for the use of a training dataset (the extant data, in your case) and the associated predict function gives you the score of all specimens (extant and fossil). In my experience, the ordination of specimens on the discriminant functions of lda and on the canonical variate axis of cva from Morpho are identical, except for arbitrary inversion of the sign of some axis, usually the first. Additionally, predict.lda already give you group membership probabilities.
As for PCA, I think that princomp and prcomp functions have a predict option that would produce scores for specimens not included in the original analysis. Best, Fabio Andrade Machado Laboratório de Evolução de Mamíferos Departamento de Genética e Biologia Evolutiva- USP [email protected] <mailto:[email protected]> ; [email protected] <mailto:[email protected]> +55 11 982631029 skype: fabio_a_machado Lattes: http://lattes.cnpq.br/3673327633303737 <http://lattes.cnpq.br/3673327633303737> Google Scholar: http://scholar.google.com/citations?hl=en&user=2l6-VrQAAAAJ <http://scholar.google.com/citations?hl=en&user=2l6-VrQAAAAJ> > Em 19/08/2015, à(s) 18:40, Blake Dickson <[email protected]> escreveu: > > 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 > <http://www.morphometrics.org/> > > To unsubscribe from this group and stop receiving emails from it, send an > email to [email protected] > <mailto:[email protected]>. -- 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 [email protected].
