[R] optimizing speed of calculation (recursive product)

[Uwe Ligges]

Wolfgang Raffelsberger wrote:
> Dear list,
> I'm wondering how to optimize functions/processes like the one shown 
> below (which simplifies something we're trying to do with very large 
> datasets).
> In many cases I've noticed that using apply, sapply etc can help 
> speeding up processes, but in this case I don't see how I could do so.
> 
> a <- runif(10000000,0.5,1.6)
> C <- 2
> M <- 10000000
> system.time( for (i in 1:(M-1)) {C <- C* c(a[i],a[i+1])} )


Well, in principal you could say:

a <- runif(10000000,0.5,1.6)
C <- 2
M <- 10000000
system.time(C <- C * c(prod(a[-M]), prod(a[-1])))

but this is all completely inaccurate from a numerical point of view - 
and you probably end up with c(0, 0) which is the quickest way to 
calculate those numbers in similar accurate way.

Uwe Ligges


> 
> By the way, I'm using R-2.7.2 on Win XP and/or Fedora Linux.
> 
> Thank's in advance for any hints,
> Wolfgang Raffelsberger
> 
> . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
> Wolfgang Raffelsberger, PhD
> Laboratoire de BioInformatique et Génomique Intégratives
> CNRS UMR7104, IGBMC 1 rue Laurent Fries,  67404 Illkirch  Strasbourg,  
> France
> 
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