#' A row-wise correlation function calculator
#'
#' \code{matCorrs} Given two matrices X (m,n), Y(m,n) this function computes (m) Pearson and Spearman correlation coefficients
#' and their significance p-values for every pair of row vectors.
#'
#' @param X First matrix
#' @param Y Second matrix. Must have the same dimensions as X
#' @keywords correlation
#' @import Hmisc
#' @export matCorrs
#' @examples
#' (X <- round(matrix (rnorm(30)*10, ncol=6),1)) + 1:10
#' (Y <- round(X + matrix (rnorm(30)*10, ncol=6),1)) - 10:1
#' (rownames(X)=rownames(Y)=letters[1:nrow(X)])
#' (m1<-matCorrs(X,Y))
#' matCorrs
#'
#'
matCorrs <- function (X, Y){
if ((nrow(X)!=nrow(Y))||(ncol(X)!=ncol(Y))) stop('matrices dimensions do not match')
corrsList<- matrix(NA, nrow=nrow(X), ncol=4)
colnames(corrsList) <- c("r (Sp)", "r (Pear)", "p (Sp)","p (Pear)")
for (i in 1:nrow(X)){
corrs<- vecCorrs(X[i,],Y[i,])
corrsList[i,] <- corrs
}
rownames(corrsList) <- rownames(X)
return(corrsList)
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.