You might find the article "Computing Thousands of Test Statistics Simultaneously in R" in http://stat-computing.org/newsletter/issues/scgn-18-1.pdf helpful.
Hadley On Sun, Aug 23, 2009 at 7:55 PM, big permie<bigper...@gmail.com> wrote: > Dear R users, > > I have a matrix a and a classification vector b such that > >> str(a) > num [1:50, 1:800000] > and >> str(b) > Factor w/ 3 levels "cond1","cond2","cond3" > > I'd like to do an anova on all 800000 columns and record the F statistic for > each test; I currently do this using > > f.stat.vec <- numeric(length(a[1,]) > > for (i in 1:length(a[1,]) { > f.test.frame <- data.frame(nums = a[,i], cond = b) > aov.vox <- aov(nums ~ cond, data = f.test.frame) > f.stat <- summary(aov.vox)[[1]][1,4] > f.stat.vec[i] <- f.stat > } > > The problem is that this code takes about 70 minutes to run. > > Is there a faster way to do an anova & record the F stat for each column? > > Any help would be appreciated. > > Thanks > Heath > > [[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. > -- http://had.co.nz/ ______________________________________________ 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.