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.
