On Mon, 31 Jan 2005, Carsten Steinhoff wrote:
maybe that my Question is a "beginner"-Question, but up to now, my research didn't bring any useful result.
I'm trying to fit a distribution (e.g. lognormal) to a given set of data (ML-Estimation). I KNOW about my data that there is a truncation for all data below a well known threshold. Is there an R-solution for an ML-estimation for this kind of data-problem? As far as I've seen the "fitdistr" in package "MASS" doesn't solve this problem.
I can intrepret that two ways. If you have a truncated lognormal distribution on say (-a, Inf), fitdistr will do this: you just need to give it the density of the truncated distribution.
If the observations are rather censored (they are smaller than something, but the value is not otherwise known), for a lognormal you can use survreg with reversed time.
Function mle() in package stats4 is useful for general MLE problems.
-- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595
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