R help - Jan 2012 - snow - bootstrapped correlation ranking

I wonder if someone could help me adjusting the following code to parallelized
snow code:

#Creating a data set (not needed to be parallel)
n<-100
p<-100
x<-matrix(rnorm(n*p),p)
y<-rnorm(n)
# Bootstrapping
nboot<-1000
alpha<-0.05
rhoboot <- array(0, dim=c(p,nboot))
bootranks <- array(0, dim=c(p,nboot))
bootsamples <- array( floor(runif(n*nboot)*n+1), dim=c(n,nboot))
for (i in 1:nboot){
rhoboot[,i] <- cor(y[bootsamples[,i]],x[bootsamples[,i],])
bootranks[,i] <- p+1rank(abs(rhoboot[,i]))
}
# Summarise results
rankhigh = apply(bootranks, 1, quantile, probs=alpha/2)
ranklow = apply(bootranks, 1, quantile, probs=1-alpha/2)


Patrik Waldmann

	[[alternative HTML version deleted]]

This might be of help:
http://viksalgorithms.blogspot.com/2012/01/parallel-r-loops-for-windows-and-linux.html

Michael

On Thu, Jan 19, 2012 at 4:21 PM, Patrik Waldmann
<patrik.waldmann at boku.ac.at> wrote:
> I wonder if someone could help me adjusting the following code to
parallelized snow code:
>
> #Creating a data set (not needed to be parallel)
> n<-100
> p<-100
> x<-matrix(rnorm(n*p),p)
> y<-rnorm(n)
> # Bootstrapping
> nboot<-1000
> alpha<-0.05
> rhoboot <- array(0, dim=c(p,nboot))
> bootranks <- array(0, dim=c(p,nboot))
> bootsamples <- array( floor(runif(n*nboot)*n+1), dim=c(n,nboot))
> for (i in 1:nboot){
> rhoboot[,i] <- cor(y[bootsamples[,i]],x[bootsamples[,i],])
> bootranks[,i] <- p+1rank(abs(rhoboot[,i]))
> }
> # Summarise results
> rankhigh = apply(bootranks, 1, quantile, probs=alpha/2)
> ranklow = apply(bootranks, 1, quantile, probs=1-alpha/2)
>
>
> Patrik Waldmann
>
> ? ? ? ?[[alternative HTML version deleted]]
>
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