Re: applying cor.test to a (m, n) matrix

Thanks Kenn. I will add your solution to my ever growing colection of functions ;-))
 
Monica

Date: Fri, 9 May 2008 18:35:30 +0300From: lebatsnok@...: pisicandru@...: Re: [R] applying cor.test to a (m, n) matrixCC: r-help@...'ve used the following function (I wrote it some time ago so I don't remember any more why I needed it, but I checked and it still works).  I don't think you can get rid of for loops altogether: if you look at the code of apply, you'll see some there too.The argument STATS specifies those components of a function's output you want to extract (if the component you're asking for has length >1 then you'll get the first item). To extract ci's you will need an intermediate function:cor.test2 <- function(...) {    foo<-cor.test(...)    ci<-foo$conf.int    foo$ci1<-ci[1]    foo$ci2<-ci[2]    foo}Then rrapply(my.data, FUN=cor.test2, STATS=c("estimate", "p.value", "ci1", "ci2")) should do what you want.rrapply <-function(x, FUN=t.test, STATS=c("statistic", "p.value"), ...){   # use FUN=cor.test, STATS=c("estimate", "p.val!
 ue") for matrix of correlations and p-values   K <- ncol(x)   RESU <- list()   my.fun <- FUN       fuf<-my.fun(x[,2],x[,1], ...)       if(!is.list(fuf)) {             STATS <- "A"             my.fun <- function(x,y,...) list(A=FUN(x,y,...))             }   neimz <- colnames(x)   for(i in 1:length(STATS)) {         fof <- STATS[i]         RESU[[fof]] <- matrix(NA, ncol=K, nrow=K)         colnames(RESU[[fof]]) <- neimz         rownames(RESU[[fof]]) <- neimz         names(RESU)[i] <- fof         }   for(i in 2:K) for(j in 1:(i-1)) {        foo<-my.fun(x[,i],x[,j], ...)          for(h in 1:length(STATS)) {               fof <- STATS[h]               RESU[[fof]][i,j]<- foo[[fof]]               }   }  if(is.list(fuf)) RESU else RESU$A}

On Fri, May 9, 2008 at 10:12 AM, Dimitris Rizopoulos <dimitris.rizopoulos@...> wrote:
have a look also at function rcor.test() from package ltm.Best,Dimitris----Dimitris RizopoulosBiostatistical CentreSchool of Public HealthCatholic University of LeuvenAddress: Kapucijnenvoer 35, Leuven, BelgiumTel: +32/(0)16/336899Fax: +32/(0)16/337015Web: http://med.kuleuven.be/biostat/   http://www.student.kuleuven.be/~m0390867/dimitris.htm----- Original Message ----- From: "Monica Pisica" <pisicandru@...>To: <r-help@...>Sent: Thursday, May 08, 2008 9:05 PMSubject: [R] applying cor.test to a (m, n) matrix



Hi everybody,I would like to apply cor.test to a matrix with m rows and n columns and get the results in a list of matrices , one matrix for p.val, one for the statistic, one for the correlation and 2 for upper and lower confidence intervals, something analog with cor() applied to a matrix.I have done my own function to get a matrix of p.values and i suppose i can build similar functions for all the others. But i have used for loops and i wonder if there is any way to actually use one of the functions from the "apply" family to do this in a quicker way.Here is my little function:cor.pval <- function(x, method = c("pearson", "kendal", "spearman"), digit=8) {n <- dim(x)[2]pval <- matrix(paste(rep("c", n*n), seq(1,n*n), sep = ""), n, n, byrow = T)for (i in 1:n) {for (j in 1:n){pval[i, j] <- cor.test(x[,i], x[,j], method = method)$p.value                                }                 }pval <- matrix(round(as.numeric(pval),digit), n, n, byrow = T)rownames(pval) <- colnames(x)c!
 olnames(pval) <- colnames(x)return(pval)}Thanks for any input,Monica_________________________________________________________________esh_messenger_052008______________________________________________R-help@... mailing listhttps://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.Disclaimer: http://www.kuleuven.be/cwis/email_disclaimer.htm 


______________________________________________R-help@... mailing listhttps://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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