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deaRs, I want to build a covariance matrix out of the data from a binary file, that I can read in chunk by chunk, with each chunk containing a single observation vector X. I wonder how to do that most efficiently, avoiding the calculation of the full symmetric matrices XX'. The trivial non-optimal approach boils down to something like: Q <- matrix(rnorm(100000),ncol=200) M <-

Hi there =20 I use Gnu R sometimes at work.=20 =20 Unfortunately we use Windows and R has problems with getting the calendar week number with the first week as the one which has at least 4 days. A colleague told me that he has the same problem.=20 =20 Below you can see what I use now, for finding the right week.=20 =20 =20 Kind regards,=20 Samuel Andreas Meichtry =20 =20

Hello, I'm hoping someone with a wide experience with R may be able to see what the program is trying to tell me. I've got an array: y1=rnorm(41,0.2) y2=rnorm(41,0.2) y3=rbind(y1,y2) data11<-array(0,c(41,2,2)) data11[,1,]=y3 data11[,2,]=y3 rownames(data11)<-rownames(data11, do.NULL = FALSE, prefix = "Obs.") colnames=c("V","R")