Hi, I am not sure why AUC should be better than, say, AICc - second order Akaike criterion and AIC weights (comfortably calculated by AICcModavg package) or Nagelkerke's R2 in this case. Would anybody be so kind and explain this for me? I just want to make warning: do not put strong (or any) emphasis to p-values of partial tests.
Best, Martin Ludovico Frate píše v Čt 20. 02. 2014 v 14:19 +0100: > Hi all,I am trying to built a species distribution model with count data > (Species Richness) using a GLM. My independent variable are computed at > multiple-scales. In order to select which is the best scale for my model, I > first calculate a bivariate model for each of the predictor for each scale. > So, I know that one possible way to select the best predictor is the use of > the AUC, but I don't know if is possible to use the AUC for count data. I > have read about presence/absence data (for example in the package DISMO, > function evaluate) but never for count data! Any suggestions?Thank you! > > > > Ludovico > Frate > > PhD student (University of Molise - Italy) > Environmetrics Lab > http://www.distat.unimol.it/STAT/environmetrica/organico/collaboratori/ludovico-frate-1 > Department of Biosciences and Territory - DiBT > Universit del Molise. > Contrada Fonte > Lappone, > 86090 - Pesche (IS) > ITALIA. > Cel: ++39 > 3333767557 > Fax: ++39 (0874) 404123 > E-mail ludovico.fr...@unimol.it > ludovicofr...@hotmail.it > > [[alternative HTML version deleted]] > > _______________________________________________ > R-sig-ecology mailing list > R-sig-ecology@r-project.org > https://stat.ethz.ch/mailman/listinfo/r-sig-ecology _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology