I think a ratio of two normals has a Cauchy distribution, which doesn't have a variance (the singularity in the denominator), so the Central Limit theorem does not apply.
I would suggest using bootstrap resampling to make inferences. At 08:10 PM 9/11/2007, Moshe wrote: >For large samples you have asymptotic normality! > >--- Paul Smith <[EMAIL PROTECTED]> wrote: > > > Dear All, > > > > The package mratios can perform inferences for > > ratios of normal means. > > Is there some other package to do the same but with > > non-normal > > populations. Since I have got large samples, an > > asymptotic procedure > > would be fine. > > > > Thanks in advance, > > > > Paul > > > > ______________________________________________ > > 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. > > > >______________________________________________ >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. ================================================================ Robert A. LaBudde, PhD, PAS, Dpl. ACAFS e-mail: [EMAIL PROTECTED] Least Cost Formulations, Ltd. URL: http://lcfltd.com/ 824 Timberlake Drive Tel: 757-467-0954 Virginia Beach, VA 23464-3239 Fax: 757-467-2947 "Vere scire est per causas scire" ______________________________________________ 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.
