Spearman would be easier since you just convert the data to ranks and use the Pearson correlation:
> set.seed(42) > x <- data.frame(matrix(sample(1:9, 20, replace=TRUE), 10, 2)) > x X1 X2 1 9 5 2 9 7 3 3 9 4 8 3 5 6 5 6 5 9 7 7 9 8 2 2 9 6 5 10 7 6 > cor(x) X1 X2 X1 1.00000000 0.01897427 X2 0.01897427 1.00000000 > cor(x, method="spearman") X1 X2 X1 1.00000000 -0.03135181 X2 -0.03135181 1.00000000 > cor(sapply(x, rank)) X1 X2 X1 1.00000000 -0.03135181 X2 -0.03135181 1.00000000 ---------------------------------------------- David L Carlson Associate Professor of Anthropology Texas A&M University College Station, TX 77843-4352 > -----Original Message----- > From: r-help-boun...@r-project.org [mailto:r-help-bounces@r- > project.org] On Behalf Of BOURGADE Eric > Sent: Thursday, February 28, 2013 3:50 AM > To: r-help@r-project.org > Subject: [R] PCA with spearman and kendall correlations > > Hello, > > I would like to do a PCA with dudi.pca or PCA, but also with the use of > Spearman or Kendall correlations > Is it possible ? > Otherwise, how can I do, according to you ? > > Thanking you in advance > > Eric Bourgade > RTE > France > > > > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org 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. ______________________________________________ R-help@r-project.org 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.