Hi, I hope someone knows the answer to this or has a real good reference about
it (I am using Legendre & Legendre, Numerical Ecology, 1998).... My data is a
data.frame with locations as rows and vegetation assemblages / species as
columns. I've done a PCA, a correspondance analysis (CA) and a detrended
correspondance analysis (DCA) using contributed packages to R (R is the open
source for S-PLUS at http://cran.r-project.org/). As far as i understand what
i've done .... the relationships between vegetation categories and locations
should be similar in all 3 analysis, although the 'arch' in locations / sites
seen in the CA plot should be flatten out by the DCA - which it is!. My problem
is that the locations / sites are flipped in the DCA plot versus PCA or CA
plots (locations with positive coordinates now have negative coordinates in DCA
versus CA or PCA), although the vegetation categories keep same relationships
between them in all three plots - which is expected. If some code is required i
can provide it but i didn't want to clutter the message too much. But i am
providing the resulting plots in case they will make my problem clearer. PCA
plot: ftp://stpfiles.er.usgs.gov/Monica/R_Data/pca_veg_lidarclass_phase2.pdfCA
plot: ftp://stpfiles.er.usgs.gov/Monica/R_Data/corresp_anal_phase2.pdfDCA plot:
ftp://stpfiles.er.usgs.gov/Monica/R_Data/detrend_corresp_anal_phase2.pdfDCA how
i would expect it:
ftp://stpfiles.er.usgs.gov/Monica/R_Data/detrend_corresp_anal_phase2_a.pdf
Also, i am aware that eigenvectors (scores) have asigned randomly their sign,
but magnitude is respected, as well as spatial relationships, so maybe this
"flipp" is normal ..... but i would liek to know your oppinions,
Thanks, Monica
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