Hi,
Fitting all possible models (GLM) with 10 predictors will result in loads of
(2^10 - 1) models. I want to do that in order to get the importance of
variables (having an unbalanced variable design) by summing the up the
AIC-weights of models including the same variable, for every variable
separately. It's time consuming and annoying to define all possible models by
hand.
Is there a command, or easy solution to let R define the set of all possible
models itself? I defined models in the following way to process them with a
batch job:
# e.g. model 1
preference<- formula(Y~Lwd + N + Sex + YY)
# e.g. model 2
preference_heterogeneity<- formula(Y~Ri + Lwd + N + Sex + YY)
etc.
etc.
I appreciate any hint
Cheers
Lukas
°°°
Lukas Indermaur, PhD student
eawag / Swiss Federal Institute of Aquatic Science and Technology
ECO - Department of Aquatic Ecology
Überlandstrasse 133
CH-8600 Dübendorf
Switzerland
Phone: +41 (0) 71 220 38 25
Fax : +41 (0) 44 823 53 15
Email: [EMAIL PROTECTED]
www.lukasindermaur.ch
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