Daren Tan
2008-Nov-25 12:14 UTC
[R] compute pearson correlation p-values for all combinations of columns of 2 matrices
How can I compute the pearson correlation p-values for all combinations of columns of 2 matrices ?> m <- matrix(rnorm(20), nrow=4, dimnames=list(LETTERS[1:4], letters[1:5])) > m1 <- matrix(rnorm(20), nrow=4, dimnames=list(LETTERS[1:4], letters[1:5])) > cor(m,m1)a b c d e a -0.67533294 -0.2516151 -0.3780815 0.55816011 -0.16526501 b 0.41729336 0.1078082 0.6671405 -0.81381931 -0.20240428 c -0.01058068 -0.5069489 0.7723080 -0.79558376 -0.32441411 d 0.98691269 0.8147252 -0.2853724 0.05879335 0.63893235 e 0.59140305 0.6746471 0.2835064 -0.47762034 -0.06372043
David Winsemius
2008-Nov-25 14:50 UTC
[R] compute pearson correlation p-values for all combinations of columns of 2 matrices
Didn't this question get asked and answered within a week or two? Daren Tan, .... meet John Baron's help search page: http://search.r-project.org/ ( .... and it apparently gets repeatedly asked and answered over the years.) -- David Winsemius On Nov 25, 2008, at 7:14 AM, Daren Tan wrote:> > How can I compute the pearson correlation p-values for all > combinations of columns of 2 matrices ? > > >> m <- matrix(rnorm(20), nrow=4, dimnames=list(LETTERS[1:4], >> letters[1:5])) >> m1 <- matrix(rnorm(20), nrow=4, dimnames=list(LETTERS[1:4], >> letters[1:5])) >> cor(m,m1) > a b c d e > a -0.67533294 -0.2516151 -0.3780815 0.55816011 -0.16526501 > b 0.41729336 0.1078082 0.6671405 -0.81381931 -0.20240428 > c -0.01058068 -0.5069489 0.7723080 -0.79558376 -0.32441411 > d 0.98691269 0.8147252 -0.2853724 0.05879335 0.63893235 > e 0.59140305 0.6746471 0.2835064 -0.47762034 -0.06372043 > > ______________________________________________ > R-help at 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.