[R] Pearson corelation and p-value for matrix
John Fox
jfox at mcmaster.ca
Sat Apr 16 03:36:05 CEST 2005
Dear Mark,
I think that the reflex of trying to avoid loops in R is often mistaken, and
so I decided to try to time the two approaches (on a 3GHz Windows XP
system).
I discovered, first, that there is a bug in your function -- you appear to
have indexed rows instead of columns; fixing that:
cor.pvals <- function(mat)
{
cols <- expand.grid(1:ncol(mat), 1:ncol(mat))
matrix(apply(cols, 1,
function(x) cor.test(mat[, x[1]], mat[, x[2]])$p.value),
ncol = ncol(mat))
}
My function is cor.pvalues and yours cor.pvals. This is for a data matrix
with 1000 observations on 100 variables:
> R <- diag(100)
> R[upper.tri(R)] <- R[lower.tri(R)] <- .5
> library(mvtnorm)
> X <- rmvnorm(1000, sigma=R)
> dim(X)
[1] 1000 100
>
> system.time(cor.pvalues(X))
[1] 5.53 0.00 5.53 NA NA
>
> system.time(cor.pvals(X))
[1] 12.66 0.00 12.66 NA NA
>
I frankly didn't expect the advantage of my approach to be this large, but
there it is.
Regards,
John
--------------------------------
John Fox
Department of Sociology
McMaster University
Hamilton, Ontario
Canada L8S 4M4
905-525-9140x23604
http://socserv.mcmaster.ca/jfox
--------------------------------
> -----Original Message-----
> From: Marc Schwartz [mailto:MSchwartz at MedAnalytics.com]
> Sent: Friday, April 15, 2005 7:08 PM
> To: John Fox
> Cc: 'Dren Scott'; R-Help
> Subject: RE: [R] Pearson corelation and p-value for matrix
>
> Here is what might be a slightly more efficient way to get to John's
> question:
>
> cor.pvals <- function(mat)
> {
> rows <- expand.grid(1:nrow(mat), 1:nrow(mat))
> matrix(apply(rows, 1,
> function(x) cor.test(mat[x[1], ], mat[x[2],
> ])$p.value),
> ncol = nrow(mat))
> }
>
> HTH,
>
> Marc Schwartz
>
> On Fri, 2005-04-15 at 18:26 -0400, John Fox wrote:
> > Dear Dren,
> >
> > How about the following?
> >
> > cor.pvalues <- function(X){
> > nc <- ncol(X)
> > res <- matrix(0, nc, nc)
> > for (i in 2:nc){
> > for (j in 1:(i - 1)){
> > res[i, j] <- res[j, i] <- cor.test(X[,i], X[,j])$p.value
> > }
> > }
> > res
> > }
> >
> > What one then does with all of those non-independent test
> is another
> > question, I guess.
> >
> > I hope this helps,
> > John
>
> > > -----Original Message-----
> > > From: r-help-bounces at stat.math.ethz.ch
> > > [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Dren Scott
> > > Sent: Friday, April 15, 2005 4:33 PM
> > > To: r-help at stat.math.ethz.ch
> > > Subject: [R] Pearson corelation and p-value for matrix
> > >
> > > Hi,
> > >
> > > I was trying to evaluate the pearson correlation and the p-values
> > > for an nxm matrix, where each row represents a vector.
> One way to do
> > > it would be to iterate through each row, and find its correlation
> > > value( and the p-value) with respect to the other rows. Is there
> > > some function by which I can use the matrix as input?
> Ideally, the
> > > output would be an nxn matrix, containing the p-values
> between the
> > > respective vectors.
> > >
> > > I have tried cor.test for the iterations, but couldn't find a
> > > function that would take the matrix as input.
> > >
> > > Thanks for the help.
> > >
> > > Dren
>
>
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