[R] for loop optimization help

[David Winsemius]

On Aug 26, 2012, at 5:06 PM, Jinsong Zhao wrote:

> Hi there,
>
> In my code, there is a for loop like the following:
>
>   pmatrix <- matrix(NA, nrow = 99, ncol = 10000)
>   qmatrix <- matrix(NA, nrow = 99, ncol = 3)
>   paf <- seq(0.01, 0.99, 0.01)
>   for (i in 1:10000) {
>       p.r.1 <- rnorm(1000, 1, 0.5)
>       p.r.2 <- rnorm(1000, 2, 1.5)
>       p.r.3 <- rnorm(1000, 3, 1)
>       pmatrix[,i] <- quantile(c(p.r.1, p.r.2, p.r.3), paf)
>   }
>   for (i in 1:99) {
>      qmatrix[i,] <- quantile(pmatrix[i,], c(0.05, 0.5, 0.95))
>   }
>
> Because of the number of loop is very large, e.g., 10000 here, the  
> code is very slow.

I would think that picking the seq(0.01, 0.99, 0.01) items in the  
first case and the 500th, 5000th and the 9500th in the second case,   
rather than asking for what `quantile` would calculate,  would surely  
be more "statistical", in the sense of choose order statistics anyway.  
Likely much faster.

-- 
David.

>
> Is it possible to optimize the code?
>
> Any suggestion will be greatly appreciated.
>
> Regards,
> Jinsong
>
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David Winsemius, MD
Alameda, CA, USA