Hello, this problem is recurrent throughout multivariate analysis, and I know of no universally satisfying solution. In spatially/phylogenetically constrained methods, the idea is that a relevant structure should exhibit both strong variance and autocorrelation. I think the simulation approaches suggested by Ted and Tom are the way to go if you seek a less descriptive approach.
Cheers Thibaut ________________________________________ From: r-sig-phylo-boun...@r-project.org [r-sig-phylo-boun...@r-project.org] on behalf of Franck Stefani [fopstef...@gmail.com] Sent: 23 August 2012 11:54 To: r-sig-phylo@r-project.org Subject: [R-sig-phylo] pPCA - global and local components Dear Theodore, Thanks for your reply but I fear I am not skilled enough in stats for considering your alternative... I have a look at the paper published by Jombart et al. (2010, Putting phylogeny into the analysis of biological traits: a methodological approach. J Theor Biol 264: 693) and it seems they have only considered the first global and/or first local components and this even if the second global or local components seemed to explain a certain amount of the total variance. Franck 2012/8/23 Theodore Garland Jr <theodore.garl...@ucr.edu> > That seems like it would be OK, at least if you think it is OK for > nonphylogenetic PCA. > An alternative is to simulate data along your phylogeny, analyze it the > same way, do it a couple thousand times, then make an empirical null > distribution of, say, the eigenvalues when the data have no correlation on > average but increased variance in the values of correlations caused by the > phylogenetic hierarchy. > This is discussed in our very old PHYLOGR package. > However, you will need to make some decisions about the "branch lengths" > to use for your individuals within species, represented by a bunch of > mini-star phylogenies. > > Cheers, > Ted > > Theodore Garland, Jr. > Professor > Department of Biology > University of California, Riverside > Riverside, CA 92521 > Office Phone: (951) 827-3524 > Facsimile: (951) 827-4286 = Dept. office (not confidential) > Email: tgarl...@ucr.edu > http://www.biology.ucr.edu/people/faculty/Garland.html > http://scholar.google.com/citations?hl=en&user=iSSbrhwAAAAJ > > Experimental Evolution: Concepts, Methods, and Applications of Selection > Experiments. 2009. > Edited by Theodore Garland, Jr. and Michael R. Rose > http://www.ucpress.edu/book.php?isbn=9780520261808 > (PDFs of chapters are available from me or from the individual authors) > > ________________________________________ > From: r-sig-phylo-boun...@r-project.org [r-sig-phylo-boun...@r-project.org] > on behalf of Franck Stefani [fopstef...@gmail.com] > Sent: Wednesday, August 22, 2012 3:50 PM > To: r-sig-phylo@r-project.org > Subject: [R-sig-phylo] pPCA - global and local components > > Hi, > > Among the graphical outputs of the pPCA, there is the scree plot showing > the global and local components. I would like to know what are the criteria > to define the number of GPC or LPC to interpret ? Can we use a broken stick > model? > > Cheers, > > Franck > > [[alternative HTML version deleted]] > > _______________________________________________ > R-sig-phylo mailing list > R-sig-phylo@r-project.org > https://stat.ethz.ch/mailman/listinfo/r-sig-phylo > [[alternative HTML version deleted]] _______________________________________________ R-sig-phylo mailing list R-sig-phylo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-phylo _______________________________________________ R-sig-phylo mailing list R-sig-phylo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-phylo
