Or since that messes up the values: u <- unique(t(apply(DF, 1, function(x) as.numeric(factor(x, levels = unique(x)))))) DF[rownames(u), ]
On 10/19/06, Gabor Grothendieck <[EMAIL PROTECTED]> wrote: > If DF is a data frame containing the rows then: > > unique(t(apply(DF, 1, function(x) as.numeric(factor(x, levels = unique(x)))))) > > > On 10/19/06, Tony Long <[EMAIL PROTECTED]> wrote: > > All: > > > > I have a matrix, X, with a LARGE number of rows. Consider the > > following three rows of that matrix: > > > > 1 1 1 1 2 2 3 3 > > 1 1 1 1 3 3 2 2 > > 3 3 2 2 1 1 1 1 > > > > I wish to fit many one-way ANOVAs to some response variable using > > each row as a set of factors. For example, for each row above I will > > do something like anova(lm(Y~as.factor(X[1,]))). My problem is that > > in the above example, I do not want to fit models for both rows 1 and > > 2 as they are essentially duplicates in terms of the ANOVA model. > > Clearly row 3, although it has the same number of 1's, 2's, and 3's, > > is a different model. > > > > Is there some computationally efficient way to remove such "factor > > duplicates" from my large matrix? I have been banging my head > > against the wall all morning. > > > > Thanks!! > > > > Tony > > -- > > ########################### > > > > Tony Long > > > > Ecology and Evolutionary Biology > > Steinhaus Hall > > University of California at Irvine > > Irvine, CA > > 92697-2525 > > > > Tel: (949) 824-2562 (office) > > Tel: (949) 824-5994 (lab) > > Fax: (949) 824-2181 > > > > email: [EMAIL PROTECTED] > > http://hjmuller.bio.uci.edu/~labhome/ > > > > ______________________________________________ > > R-help@stat.math.ethz.ch 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@stat.math.ethz.ch 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.