On Sat, 5 Aug 2006, Andreas Beyerlein wrote: > Dear all, > > I want to compare some different models for a dataset by QQ plots and > AIC. I get the following AICs: > > - linear model: 19759.66 > - GAMLSS model: 18702.7 > - linear model with lognormal response: -7862.182 > > The QQ plots show that the lognormal model fits better than the linear > model, but still much worse than the GAMLSS. So, in my opinion, the AIC > of the lognormal model should be between the AICs of the both other > models. What happens here?
> Btw: For the lognormal model, I transformed the response variable by > log(). Apart from that, I used the same formula as for the linear model. So you got the AIC for the logged data, which is not comparable to the others. You need to convert to a likelihood and hence AIC for the original data. (I think anyone using AIC needs to know how to do that, as it is part of the basic understanding of what a likelihood is. It is also part of the derivation of the estimation of the Box-Cox transformation, something which you might well want to consider here.) -- 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 ______________________________________________ R-help@stat.math.ethz.ch 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.