Dear Gundala, Try this:
# Data set DF=read.table(textConnection("300.35 200.25 104.30 22.00 31.12 89.99 444.50 22.10 43.00 22.10 200.55 66.77"),header=FALSE,sep="") # Variances VAR=apply(DF,1,var) # Order pos=order(VAR) # Print VAR and pos VAR pos # ordered VAR VAR[pos] # top-2 highest VAR VAR[pos][3:4] HTH, Jorge On Thu, Jun 19, 2008 at 10:59 AM, Gundala Viswanath <[EMAIL PROTECTED]> wrote: > Hi, > > I have the following dataset (simplified for example). > > __DATA__ > 300.35 200.25 104.30 > 22.00 31.12 89.99 > 444.50 22.10 43.00 > 22.10 200.55 66.77 > > Now from that I wish to do the following: > > 1. Compute variance of each row > 2. Pick top-2 row with highest variance > 3. Store those selected rows for further processing > > To achieve this, I tried to: a) read the table and compute > variance for each row, b) append variance with its original > row in a vector, c) store a vector into multidimentional array (matrix), > d) sort that array. But I am stuck at the step (b). > > Can anybody suggest what's the best way to achieve > my aim above? > > This is the sample code I have so far (not working). > > __BEGIN__ > > #data <- read.table("testdata.txt") > > > # Is this a right way to initialize? > all.arr = NULL > > for (gi in 1:nofrow) { > gex <- as.vector(data.matrix(data[gi,],rownames.force=FALSE)) > > #compute variance > gexvar <- var(gex) > > # join variance with its original vector > nvec <- c(gexvar,gex) > > # I'm stuck here.....This doesn't seem to work > all.arr <- data.frame(nvec) > } > > print(all.arr) > __END__ > -- > Gundala Viswanath > Jakarta - Indonesia > > ______________________________________________ > 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. > [[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.