# RE: [R] Pearson corelation and p-value for matrix

From: Liaw, Andy <andy_liaw_at_merck.com>
Date: Sat 16 Apr 2005 - 12:51:18 EST

We can be a bit sneaky and `borrow' code from cor.test.default:

cor.pval <- function(x, alternative="two-sided", ...) {

corMat <- cor(x, ...)
n <- nrow(x)
df <- n - 2
STATISTIC <- sqrt(df) * corMat / sqrt(1 - corMat^2)     p <- pt(STATISTIC, df)
p <- if (alternative == "less") {

p
} else if (alternative == "greater") {

1 - p
} else 2 * pmin(p, 1 - p)
p
}

The test:

> system.time(c1 <- cor.pvals(X), gcFirst=TRUE)
[1] 13.19 0.01 13.58 NA NA
> system.time(c2 <- cor.pvalues(X), gcFirst=TRUE)
[1] 6.22 0.00 6.42 NA NA
> system.time(c3 <- cor.pval(X), gcFirst=TRUE)
[1] 0.07 0.00 0.07 NA NA

Cheers,
Andy

> From: John Fox
>
> 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
> 905-525-9140x23604
> http://socserv.mcmaster.ca/jfox
> --------------------------------
>
> > -----Original Message-----
> > From: Marc Schwartz [mailto:MSchwartz@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@stat.math.ethz.ch
> > > > [mailto:r-help-bounces@stat.math.ethz.ch] On Behalf Of
> Dren Scott
> > > > Sent: Friday, April 15, 2005 4:33 PM
> > > > To: r-help@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
> >
> >
>
> ______________________________________________
> R-help@stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help