1. As this is not really appropriate for R, I suggest replies be private. 2. You might try posting on various statistical forums, e.g. on http://stats.stackexchange.com/
-- Cheers, Bert On Wed, Aug 24, 2011 at 12:15 PM, Arnaud Mosnier <a.mosn...@gmail.com> wrote: > Hi, > > In order to find the best models I use AIC, more specifically I calculate > Akaike weights then Evidence Ratio (ER) and consider that models with a ER < > 2 are equally likely. > But the same problem remain each time I do that. I selected the best models > from a set of them, but I don't know if those models are efficient to > predict (or at least represent) my data. > I can have selected the best element(s) of the list of the worst models. > > Do you find it is correct to calculate R2 or pseudo-R2 for the best "set of > models" in order to have an idea of the representativeness of those models > and use this value to select the more efficient model ? > > I would be glad to hear your opinions about this ! > > Thanks, > > Arnaud > > [[alternative HTML version deleted]] > > ______________________________________________ > 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.