Well if your matrix and vector are centered and properly scaled (and there are no missing values), then the correlations are just a crossproduct and matrix arithmetic is already fairly fast (assuming you have enough memory).
-- Gregory (Greg) L. Snow Ph.D. Statistical Data Center Intermountain Healthcare [email protected] 801.408.8111 > -----Original Message----- > From: [email protected] [mailto:r-help-boun...@r- > project.org] On Behalf Of jastar > Sent: Thursday, May 14, 2009 2:06 PM > To: [email protected] > Subject: [R] "Fast" correlation algorithm > > > Hi, > Is in R any "fast" algorithm for correlation? > What I mean is: > I have very large dataset (microarray) with 55000 rows and 100 columns. > I > want to count correlation (p-value and cor.coef) between each row of > dataset > and some vector (of course length of this vector is equal to number of > columns of dataset). > In short words: > For t-test we have: > "normal" algorithm - t.test > "fast" algorithm - rowttests > For correlation: > "normal" algorithm - cor.test > "fast" algorithm - ??? > > Thank's for help > -- > View this message in context: http://www.nabble.com/%22Fast%22- > correlation-algorithm-tp23548016p23548016.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > [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. ______________________________________________ [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.
