search for: colstdevs

I need to calculate a large number of t statistics, and would like to do so via matrix operations. So far I have figured out a way to calculate the mean of each row of the matrix: d <- matrix(runif(100000,1,10), 1000, 10) # some test data s <- rep(1,ncol(d)) # a sum vector to use for matrix multiplication means <- (d%*%s)/ncol(d) This is at least 1 order of magnitude faster than

I've uploaded a package colSums_1.0.tar.gz to CRAN /src/contrib/Devel. It contains functions colSums, colMeans, colVars, colStdevs, rowSums, rowMeans, rowVars, and rowStdevs. These do simple, fast arithmetic on columns/rows of a matrix, or more generally across dimensions of an array, e.g. colSums(m) = apply(m, 2, sum) but faster. They should be compatible with the corresponding S-Plus functions. The core code was written b...

...ms(x^2, na.rm, dims)) N <- rowSums(!is.na(x), FALSE, dims) Nm1 <- if (unbiased) N-1 else N if (twopass) {x <- if (dims==0) x - mean(x, na.rm=na.rm) else sweep(x, 1:dims, rowMeans(x,na.rm,dims))} (rowSums(x^2, na.rm, dims) - rowSums(x, na.rm, dims)^2/N) / Nm1 } colStdevs <- function(x, ...) sqrt(colVars(x, ...)) rowStdevs <- function(x, ...) sqrt(rowVars(x, ...))

...2,tdon21) don<-guiDisplayFileDialog() import.data (DataFrame="tdon",FileName=don,FileType="EXCEL") nbcol<-length(tdon[1,]) nlc<-matrix(0,1,nbcol) for (i in 1:nbcol) {nbl1<-tdon[,i] nbl2<-nbl1[nbl1!="NA"] nbl3<-numRows(nbl2) nlc[,i]<-nbl3 ect<-colStdevs(tdon,na.rm=T,unbiased=T) h<-1.06*ect*(nlc^-0.2) cpt<-0 nlgn<-choose(nbcol,2) Results<-matrix("*",nrow=nlgn,ncol=3,dimnames=list(NULL,c("Ech.1","Ech.2","Overlap"))) for (i in 1:(nbcol-1)) {tdon1<-tdon[,i] tdon11<-tdon1[tdon1!="NA"]...

Hi people, If there is a fn "colMeans" why isn't there a "colSDs" etc Thanks, Phil. -- Philip Rhoades Pricom Pty Limited (ACN 003 252 275) GPO Box 3411 Sydney NSW 2001 Australia Mobile: +61:0411-185-652 Fax: +61:2:8923-5363 E-mail: pri at chu.com.au -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Hi, Currently, the "base" has colSums, colMeans. It seems that it would be useful to extend this to also include colMin, colMax (of course, rowMin and rowMax, as well) in order to facilitate faster computations for large vectors (compared to using apply). Has this been considered before? Please forgive me if this has already been discussed before. Thanks, Ravi Ravi Varadhan, Ph.D.