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" <j...@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-boun...@r-project.org] on behalf of Doran, Harold >[hdo...@air.org] >Sent: November 8, 2016 10:57 AM >To: r-help@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@r-project.org mailing list -- To UNSUBSCRIBE and more, see >https://stat.ethz.ch/mailman/listinfo/r-help >PLEASE do read the posting guide >http://www.R-project.org/posting-guide.html >and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.