[R] Alternative to apply in base R

Doran, Harold HDoran at air.org
Tue Nov 8 21:23:04 CET 2016

It¹s a good suggestion. Multiplication in this case is over 7 columns in
the data, but the number of rows is millions. Unfortunately, the values
are negative as these are actually gauss-quad nodes used to evaluate a
multidimensional integral.

colSums is better than something like apply(dat, 2, sum); I was hoping
there was something similar to colSums/rowSums using prod().

On 11/8/16, 3:00 PM, "Fox, John" <jfox at mcmaster.ca> wrote:

>Dear Harold,
>If the actual data with which you're dealing are non-negative, you could
>log all the values, and use colSums() on the logs. That might also have
>the advantage of greater numerical accuracy than multiplying millions of
>numbers. Depending on the numbers, the products may be too large or small
>to be represented. Of course, logs won't work with your toy example,
>where rnorm() will generate values that are both negative and positive.
>I hope this helps,
> John
>John Fox, Professor
>McMaster University
>Hamilton, Ontario
>Canada L8S 4M4
>web: socserv.mcmaster.ca/jfox
>From: R-help [r-help-bounces at r-project.org] on behalf of Doran, Harold
>[HDoran at air.org]
>Sent: November 8, 2016 10:57 AM
>To: r-help at r-project.org
>Subject: [R] Alternative to apply in base R
>Without reaching out to another package in R, I wonder what the best way
>is to speed enhance the following toy example? Over the years I have
>become very comfortable with the family of apply functions and generally
>not good at finding an improvement for speed.
>This toy example is small, but my real data has many millions of rows and
>the same operations is repeated many times and so finding a less
>expensive alternative would be helpful.
>mm <- matrix(rnorm(100), ncol = 10)
>rn <- apply(mm, 1, prod)
>        [[alternative HTML version deleted]]
>R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
>PLEASE do read the posting guide
>and provide commented, minimal, self-contained, reproducible code.

More information about the R-help mailing list