Thank you Jari for quick responce, > So how close do you need to get? > >> 0.78101^2 > [1] 0.6099766 >> 0.69142^2 > [1] 0.4780616
Yes, that one I understood from Anderson's CAP manual. >> # The only Eigenvalue related value I find is dune.cap$tot > What about dune.cap$manova$Eigenvalues? Thank you for pointing this out for me. I was referring to the R documentation where there was no mention about these objects (directly). A misunderstanding here. When using dune.cap$manova$Eigenvalues: [,1] [,2] [,3] [,4] [,5] [,6] y[, group] 8.543145 0.825438 0.6292823 1.334105e-16 -5.300794e-17 1.572394e-17 These values are identical to the Eigenvalues in Anderson's CAP manual and by ^2 I get the delta^2 values like in A&W2003? Can you tell why > sum(dune.cap$manova$Eigenvalues) [1] 9.997866 is not same as > dune.cap$tot [1] 3.850346 ? Are they measuring different axes? dune.cap2$tot for (sum of all eigenvalues of PCoA) and dune.cap2$manova$Eigenvalues for the CAP axes? Can I compute the proportion of variance explained on each axis by: > dune.cap$manova$Eigenvalues/sum(dune.cap$manova$Eigenvalues) [,1] [,2] [,3] [,4] [,5] ... y[, group] 0.8544969 0.08256142 0.06294166 ... And finally, does the dune.cap$manova give me the similar p as in the A&W2003? Thank you for answering to my (for you trivial) questions. -Kari On Tue, Jun 7, 2011 at 2:54 PM, Jari Oksanen <jari.oksa...@oulu.fi> wrote: > On 7/06/11 06:48 AM, "Kari Lintulaakso" <kari.lintulaa...@gmail.com> wrote: > >> Dear list, >> >> I'm trying to follow the CAP analysis described in Anderson and Willis >> 2003: Canonical Analysis of Principal Coordinates: A Useful Method of >> Constrained Ordination for Ecology >> For this I'm using CAPdiscrim (instead of capscale) as it seems to >> follow the original description. >> I'm using a data set with n different biomes. Each biome has several >> sites and each site has species counts listed. >> >> I use the dune data set to describe my questions which are in the comments. >> >> require(BiodiversityR) >> require(vegan) >> data(dune) >> data(dune.env) >> # Transform variables >> dune.trs <- decostand(dune,"log") >> >> # Calculate dissimilarities between each pair of observations, Bray-Curtis >> dune.bray <- vegdist(dune.trs, method = "bray") >> >> # Canonical Analysis of Principal Coordinates (CAP): >> # This is done for Management which acts like class data >> dune.cap <- CAPdiscrim(dune.bray ~ Management, dune.env >> ,dist="bray",axes=4,m=0,permutations=9) >> >> # In Anderson and Willis 2003, page 518: >> # "... The canonical analysis (CAP) yielded two canonical axes, >> # with squared canonical correlations of delta1^2 = 0.610 and delta1^2 >> = 0.478..." >> # >> # It seems that those values come from Eigenvalues (Correlations) of >> 0.78101 and 0.69142 >> http://www.stat.auckland.ac.nz/~mja/prog/CAP_UserNotes.pdf >> # QUESTION 1: How do I get similar values using CAPdiscrim? > So how close do you need to get? > >> 0.78101^2 > [1] 0.6099766 >> 0.69142^2 > [1] 0.4780616 > > Which are identical in three decimal places to those values that A&W > reported (and they reported squared values). > >> # The only Eigenvalue related value I find is dune.cap$tot > What about dune.cap$manova$Eigenvalues? > > Cheers, Jari Oksanen > > -- Kari Lintulaakso, M.Sc.(Biosciences) Doctoral student Paleontology and Paleoecology Department of Geosciences and Geography University of Helsinki * Mobile: +358 50 40 33391 * Office: +358 9 191 50842 * Email: kari.lintulaa...@helsinki.fi * Post: Department of Geology, Gustaf Hällströmin katu 2a (P.O Box 64), 00014 University of Helsinki * Web page: http://blogs.helsinki.fi/lintulaa/ _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology