There is probably a better way to do this but a for loop like this should work. You would just need to change the numbers to yours and then add on the locations 
========================================================= 

scores  <- 1:5
mydata <- matrix(data=NA, nrow=5, ncol=10)

for(i in 1:10) {
mydata[,i] <- sample(scores, 5, replace=FALSE)
}

=========================================================
--- On Wed, 4/20/11, Kevin Matthews <kevin-matthews@uiowa.edu> wrote:

From: Kevin Matthews <kevin-matthews@uiowa.edu>
Subject: Re: [R] Random Relabelling
To: "John Kane" <jrkrideau@yahoo.ca>
Cc: r-help@r-project.org
Received: Wednesday, April 20, 2011, 1:22 PM

I have a map of Iowa of with 4000 locations.  At each location, I have a cancer mortality rate.  I need to test my null hypothesis; that the spatial distribution of the mortality rates is  random.  For this test, I need to establish a spatial reference distribution.  


My reference distribution will be created by some random relabelling algorithm.  The 4000 locations would remain fixed, but the observed mortality rates would be randomly redistributed.  Then, I want 1000 permutations of the same algorithm.  For each of those 1000 times, I would record the redistributed mortality rate at each location.  Then,  I would calculate the mean of the 1000 points.  The result would be a spatial reference distribution with a mean value of the random permutations at each of the 4000 locations.  



Thanks for the response,Kevin

On Wed, Apr 20, 2011 at 11:08 AM, John Kane <jrkrideau@yahoo.ca> wrote:


Can you explain this a bit more. At the moment I don't see what you are trying to achieve.   "calculate the mean of the 1000 values at each of the 4000 points" does not seem to make sense.





--- On Wed, 4/20/11, kmatthews <kevin-matthews@uiowa.edu> wrote:



> From: kmatthews <kevin-matthews@uiowa.edu>

> Subject: [R] Random Relabelling

> To: r-help@r-project.org

> Received: Wednesday, April 20, 2011, 10:04 AM

> I have 4000 observations that I need

> to randomly relabel 1000 times and then

> calculate the mean of the 1000 values at each of the 4000

> points.  Any ideas

> for where to begin?

>

> Thanks

> Kevin

>






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