Message-ID: <7B9A8B27-6E58-409F-BC0F-50BFDD1A60EC@comcast.net>
Date: 2011-01-05T19:22:11Z
From: David Winsemius
Subject: speed up in R apply
In-Reply-To: <AANLkTik5cjXTGA-8H0S+NozfRwKEpv0q_2bnBz6a9KAe@mail.gmail.com>
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