R help - Jan 2011 - speed up in R apply

Hi,

I am doing some simulations and found a bottle neck in my R script. I made
an example:
> a = matrix(rnorm(5000000),1000000,5)
> tt  = Sys.time(); sum(a[,1]*a[,2]*a[,3]*a[,4]*a[,5]); Sys.time() - tt
[1] -1291.026
Time difference of 0.2354031 secs
>
> tt  = Sys.time(); sum(apply(a,1,prod)); Sys.time() - tt
[1] -1291.026
Time difference of 20.23150 secs

Is there a faster way of calculating sum of products (of columns, or of
rows)? And is this an expected behavior?

Thanks for your advice in advance,

Young

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On Jan 5, 2011, at 10:03 AM, Young Cho wrote:
> Hi,
>
> I am doing some simulations and found a bottle neck in my R script.  
> I made
> an example:
>
>> a = matrix(rnorm(5000000),1000000,5)
>> tt  = Sys.time(); sum(a[,1]*a[,2]*a[,3]*a[,4]*a[,5]); Sys.time() - tt
> [1] -1291.026
> Time difference of 0.2354031 secs
>>
>> tt  = Sys.time(); sum(apply(a,1,prod)); Sys.time() - tt
> [1] -1291.026
> Time difference of 20.23150 secs
>
> Is there a faster way of calculating sum of products (of columns, or  
> of
> rows)?
You should look at crossprod and tcrossprod.
> And is this an expected behavior?
Yes. For loops and *apply strategies are slower than the proper use of  
vectorized functions.
>
> Thanks for your advice in advance,
>
-- 

David Winsemius, MD
West Hartford, CT