[R] fitting of all possible models

[hadley wickham]

Hi Lukas,

You may find my meifly package helpful.  It provides functions to
generate ensembles of models (eg. fitall) and then extract all the
coefficients, residuals etc (coef, summary, residual etc).  The main
point of the package is to visualise all these models, and I second
Frank's comment that merely selecting the best model will be perilous.

Unfortunately, the package is not on CRAN yet, but if you are
interested, contact me off list with your OS and I can email you the
package, and accompanying paper.

Regards,

Hadley

On 2/27/07, Indermaur Lukas <Lukas.Indermaur at eawag.ch> wrote:
> 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: lukas.indermaur at eawag.ch
> www.lukasindermaur.ch
>
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