Hi Carlos, > I want to see the similarity between them, and to be able to extract the > differences between them.
You need to explain a bit more. Are you looking for number of elements in common? How are your data set up? (eg species as columns and sites as rows) One way to get number of joint presences is this (although there are certainly more elegant ways), assuming that columns are species > m1 <- matrix(c(1,0,0,0,1,0,1,1,1,1,1,1), 3,4) > m2 <- matrix(c(1,0,1,0,1,0,0,1,0,1,0,1), 3,4) > apply((m1 + m2), 1, function(x)sum(x == 2)) [1] 2 2 1 > I tried with the function cor2m() [package=edodist] but it didn't worked > and my matrices are much bigger than the ones from the example. "Didn't work"? That's a bit vague, but anyway this won't help, since cor2m is intended for use with a matrix of environmental variables as the second matrix, and not for binary data (the first matrix can be binary). I doubt that correlations are really the measure you want anyway - if they are, then you can use simply cor(m1, m2) Sarah -- Sarah Goslee http://www.functionaldiversity.org ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
