> -----Mensaje original----- > De: Kjetil Halvorsen [mailto:kjetilbrinchmannhalvor...@gmail.com] > Enviado el: jueves, 17 de marzo de 2011 16:19 > Para: Rubén Roa > CC: Alexx Hardt; r-help@r-project.org > Asunto: Re: [R] R² for non-linear model > > see inline. > > On Thu, Mar 17, 2011 at 4:58 AM, Rubén Roa <r...@azti.es> wrote: > > Hi Alexx, > > > > I don't see any problem in comparing models based on > different distributions for the same data using the AIC, as > long as they have a different number of parameters and all > the constants are included. > > For example, you can compare distribution mixture models > with different number of components using the AIC. > > This is one example: > > Roa-Ureta. 2010. A Likelihood-Based Model of Fish Growth > With Multiple Length Frequency Data. Journal of Biological, > Agricultural and Environmental Statistics 15:416-429. > > Here is another example: > > www.education.umd.edu/EDMS/fac/Dayton/PCIC_JMASM.pdf > > Prof. Dayton writes above that one advantage of AIC over > hypothesis testing is: > > "(d) Considerations related to underlying distributions > for random > > variables can be incorporated into the > decision-making process > > rather than being treated as an assumption whose robustness > must be > > considered (e.g., models based on normal densities > and on log-normal densities can be compared)." > > My reading of this is that AIC can be used to compare models > with densities relative to the same dominating measure. > > Kjetil
I think this is correct. It is probably not wise to use the AIC to compare distribution models based on the counting measure with distribution models based on the Lebesgue measure! ____________________________________________________________________________________ Dr. Rubén Roa-Ureta AZTI - Tecnalia / Marine Research Unit Txatxarramendi Ugartea z/g 48395 Sukarrieta (Bizkaia) SPAIN ______________________________________________ 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.