[R-sig-eco] SDM-model evaluation

[Martin Weiser]

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.
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