[R] 3-dimensional looping Q.

[Peter Wolf]

You can compute cor by hand without loops but the code is not much 
faster (dim(slp)[1]==3):

<<*>>=
set.seed(13)
n<-3
y<-1:n
slp<-array(rnorm(n*73*144),c(3,73,144))
n.1<-length(y)-1

print(system.time({
rData <- array(0,c(73,144))   # array to store results
   for (i in 1:73) {
        for (j in 1:144) {
              rData[i,j] <- cor(slp[,i,j],y)
        }
    }
}))

print(system.time({
n.1<-length(y)-1
mean.slp<-apply(slp,c(2,3),mean)
mean.y<-mean(y); sy<-var(y)^0.5
sqslp<-apply(slp*slp,c(2,3),sum)/n.1-mean.slp^2*n/n.1
sslpy<-apply(slp*y,c(2,3),sum)/n.1-mean.slp*mean.y*n/n.1
rslpy<-sslpy/(sqslp^0.5*sy)
}))

print(all(round(100*rslpy)==round(100*rData)))

@
output-start
[1] 1.49 0.00 1.49 0.00 0.00
[1] 0.92 0.00 0.92 0.00 0.00
[1] TRUE
output-end

Peter Wolf


Uwe Ligges wrote:

> Maurice McHugh wrote:
>
>> Hello everyone-
>>
>> I have a 3-d array with the 1st dimension being monthly mean data that
>> I would like to correlate with some time series index, for example, 
>> and save the coefficients in an array.
>>
>> The code I am currently running is....
>>
>>
>>    rData <- array(0,c(73,144))   # array to store results
>>    for (i in 1:73) {
>>         for (j in 1:144) {
>>               rData[i,j] <- cor(slp[,i,j],y)
>>         }
>>     }
>>
>>     Rather than running this analysis embedded with two outer loops, 
>> are =
>>     there any more efficient ways of doing this?
>>     Many thanks!
>
>
>
> Don't know whether it's more efficient:
> You can try to apply() the function rcorr() in package "Hmisc" to your 
> problem...
>
> Uwe Ligges
>
>
>
>
>>    
>> Maurice
>>
>> Maurice McHugh
>> Department of Geography and Anthropology
>> Louisiana State University
>> Baton Rouge, LA
>>     [[alternative HTML version deleted]]
>>
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>
>
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