The key is to assign space in advance -- e.g., compare:
> N <- 20000
>
> res <- NULL
> system.time( for(i in 1:N) res <- c(res, sample(10)) )
[1] 28.62 8.91 37.79 0.00 0.00
>
> res <- vector("list",N)
> system.time( for(i in 1:N) res[[i]] <- sample(10) )
[1] 0.45 0.00 0.44 0.00 0.00
>
> res <- matrix(0.0, N,10)
> system.time( for(i in 1:N) res[i,] <- sample(10) )
[1] 0.47 0.01 0.47 0.00 0.00
>
Gardar
At 01:46 PM 9/28/2004 +0200, Nael Al Anaswah wrote:
Hi there,
I am running Monte Carlo Simulations in R using ordinary "while (condition)" loops. Since the number of iterations is something like 100.000 and within each iteration a given subsample is extended sequentially it takes hours to run the simulation.
Does anyone know if there is either a way to avoid using loops in Monte Carlo Simulations or how to include possible faster "c++" commands in R code?
many thanks in advance.
Nael Al-Anaswah
----------------------------------------------------- Nael Al-Anaswah Department of Econometrics University of Muenster Germany
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