Hallo everybody, I'm wondering whether it might be possible to speed up the following code:
Error<-rnorm(10000000, mean=0, sd=0.05) estimate<-(log(1.1)-Error) DCF_korrigiert<-(1/(exp(1/(exp(0.5*(-estimate)^2/(0.05^2))*sqrt(2*pi/(0.05^2))*(1-pnorm(0,((-estimate)/(0.05^2)),sqrt(1/(0.05^2))))))-1)) D<-100000 Delta_ln<-rep(0,D) for(i in 1:D) Delta_ln[i]<-(log(mean(sample(DCF_korrigiert,1000000,replace=TRUE))/(1/0.10))) The calculation of the for-loop takes several hours even on a very quick machine (4GHz, 8 GB RAM Windows 2008 Server 64bit). Has anybody an idea, how to improve the for-line? Thanks for helping me. Hans -- View this message in context: http://r.789695.n4.nabble.com/Speed-up-code-with-for-loop-tp3481680p3481680.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list 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.
