My version of S-PLUS has
> methods("AIC")
nlme3 nlme3 nlme3 nlme3 nlme3 nlme3
"AIC.gls" "AIC.lm" "AIC.lmList" "AIC.lme" "AIC.logLik" "AIC.nls"
so I think all you need to do is to call AIC on the fitted object. I
believe that to be true for all versions with nlme3 (which was around in
S+2000) and possibly earlier.
It works essentially as Spencer describes, calling logLik.nls. (It seems
to allow for weights in the fit.)
On Wed, 3 Mar 2004, Spencer Graves wrote:
> Recall that nls assumes normal, independent errors. Thus, the
> likelihood is
>
> prod( (1/(sigma*sqrt(2*pi))*exp(-0.5*(resid[i]/sigma)^2)).
>
> Therefore, the log(likelihood) is
>
> (-0.5)*( N*log(2*pi*sigma^2) + sum(resid[i]^2)/sigma^2).
>
> You can somehow get the MLE of "sigma", plug this into this
> formula, and get the log(likelihood). The AIC is
> (-2)*(log(likelihood)+k), where k = number of parameters estimated,
> including sigma.
>
> I don't know the simplest way to get this, and I don't have time
> to play with it, but ?nls contains a pointer to ?nls.object. The latter
> says it has a component "residuals". From this, you can compute "sigma"
> = sum(residuals^2)/N, where N = total number of observations. NOTE:
> You want to use the MLE here, not (N-k) for the unbiased estimate.
>
> There is probably a much easier way to get this, but I can't think
> of it right now.
>
> hope this helps.
> spencer graves
>
> Tropmedres wrote:
>
> >Hello
> >
> >I am doing the curve fitting using the non-linear regression (nls). I am not
> >sure how to select the best model when I cannot get the AIC as in usual lm,
> >glm, gam model. I cannot use the stepAIC function from the MASS library
> >neither. For the nested models I have been using 'anova.nls with test=chisq'
> >but what about the non-nested models?
> >
> >Thank you in advance
> >
> >Wirichada
--
Brian D. Ripley, ripley@stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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