Thanks a lot dear Philip. I will try this. all the best
Pierre Le 22/03/2019 à 17:07, Dixon, Philip M [STAT] a écrit :
Pierre, I don't know a function that does this, but it is extremely easy to code. Dist objects are vectors containing the 1st stage pairwise dissimilarities. Call those dist1, dist2, dist3, ... So alldist <- cbind(dist1=dist1, dist2=dist2, ...) will assemble the matrix of dissimilarities with useful column names. stage2 <- as.dist(1-cor(alldist)) will compute the matrix of correlations, convert from similarity (the correlation) to distance (1-correlation) and convert to a distance object. Then just run your favorite MDS on stage2. Note: sometimes folks prefer sqrt(1-cor) as the "correlation distance", instead of 1-cor. I don't know which Clarke prefers. Best, Philip Dixon _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
_______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
