If you are after the lognormal distribution, I would recommend you use the lognormal functions from R itself. Check them out with
?dlnorm David Scott On Wed, 14 Nov 2007, Scionforbai wrote: > If what you want is a lognormal distribution of n values you can use > the following transformations: > > lognorm1 <- M*exp((rnorm(n)*sigma)-sigma^2/2.) > > which gives a lognormal distribution such that: > mean(lognorm1)=M ; > var(lognorm1)=M^2*(exp(sigma^2)-1); > Changing the sigma (standard deviation) you always obtain the same > arithmetic mean. > > Or, alternatively, > > lognorm2 <- exp(m + sigma * rnorm(n)) > such that: > exp(mean(log(lognorm2))=exp(m) [geometric mean] > mean(lognorm2)=exp(m + sigma^2/2); > var(lognorm2)=exp(2*m + sigma^2)*(exp(sigma^2/2)-1) > In this case, for different sigma values is the geometric mean to stay > constant, not the arithmetic. > > Did it answer your question? > > ______________________________________________ > 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. > _________________________________________________________________ David Scott Department of Statistics, Tamaki Campus The University of Auckland, PB 92019 Auckland 1142, NEW ZEALAND Phone: +64 9 373 7599 ext 86830 Fax: +64 9 373 7000 Email: [EMAIL PROTECTED] Graduate Officer, Department of Statistics Director of Consulting, Department of Statistics ______________________________________________ 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.
