Fabio Berzaghi <fabe <at> dmu.dk> writes:
>
> hello all,
>
> I have a simple linear model with 4/5 variables that I am trying to fit.
> I would like to find the lowest AIC value with any combination of all
> the variables. I would like to implement this with a while/for loop.
> Possibly I would like to generalize this so then I can use it when I
> have many more variables. I do not want to use step AIC. At the moment I
> am doing it manually but I would like to automate the process because I
> have many species. I want to compute all possible combinations with all
> the variables and know which combination gives the lowest AIC.
> My function looks like this
>
[snip]
You should really use a data argument, i.e.
lm(tl~poly(bs0011yme,2)+poly(bt0011yme,2)+poly(ss0011sme,2)+
poly(st0011sme,2),data=subxy)
(It won't change the answers but it will make everything work
better if you want to post-process the fit, e.g updating or
predicting)
> I cannot seem to find a library that has a function that does this
> automatically.
Check out the MuMIn, AICcmodavg, and glmulti packages.
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