Re: [Gretl-devel] simulation speed

On 23-12-2009, at 20:34, Berend Hasselman wrote: The R script of my previous post was much too long and had a mistake in adding a row to the data.frame (mixing character and numeric data in a vector). I have also added the quantile value to the table to check (column result). The result for the corrected script is (still using R.app 32-bit) RNGmethod ctype result user system elapsed 1 Inversion loop 0.05180068 1.681 0.006 1.687 2 Inversion iteration 0.05211462 1.648 0.206 1.853 3 Kinderman-Ramage loop 0.05228179 1.105 0.061 1.166 4 Kinderman-Ramage iteration 0.05176681 1.027 0.001 1.028 5 Box-Muller loop 0.05224984 1.513 0.018 1.531 6 Box-Muller iteration 0.05208642 1.417 0.005 1.423 7 Ahrens-Dieter loop 0.05237948 1.076 0.021 1.097 8 Ahrens-Dieter iteration 0.05192184 0.993 0.000 0.993 The Ahrens-Dieter method is still the quickest. Berend <R-code> resdata <- data.frame(RNGmethod="",ctype="", result=0, user=0, system=0, elapsed=0,stringsAsFactors=FALSE,row.names=NULL) nlen <- 1000 iterations <- 10000 averages <- numeric(iterations) whichp <- 0.95 for( Rmethod in c("Inversion","Kinderman-Ramage", "Box-Muller", "Ahrens-Dieter") ) { RNGkind(normal.kind=Rmethod) t <- system.time( { for(k in 1:iterations) { v <- rnorm(nlen); averages[k] <- mean(v) } result <- quantile(averages,probs=c(whichp)) }) resdata <- rbind(resdata, list(RNGmethod=Rmethod, ctype="loop", result=result, user=t[1],system=t[2],elapsed=t[3])) t <- system.time({ averages2 <- colMeans(matrix(data=rnorm(nlen*iterations), nrow=nlen, ncol=iterations)) result <- quantile(averages2,probs=c(whichp)) }) resdata <- rbind(resdata, list(RNGmethod=Rmethod, ctype="iteration", result=result, user=t[1],system=t[2],elapsed=t[3])) } # delete dummy first row resdata <- resdata[2:nrow(resdata),] row.names(resdata) <- NULL resdata </R-code>