From: hck <hans-christian.krumholz_at_uni-ulm.de>

Date: Thu, 28 Apr 2011 10:27:35 -0700 (PDT)

Date: Thu, 28 Apr 2011 10:27:35 -0700 (PDT)

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_at_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.Received on Thu 28 Apr 2011 - 17:36:40 GMT

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