John: 1. As always, and as requested (see posting guide), a small reproducible example might help.
2. What is CLi in your model? 3. In general, AIC may not be particularly meaningful as a measure of fit quality penalized for model complexity in NON-linear models unless the different models are "nested" in very specific ways, which are model-centric. The reason is that while the log likelihood part of AIC is clearly defined (at least up to the quality of the convergence), the number of parameters is not. That is, a single parameter in the model may count as more or less than one parameter, in some sense. Indeed, this is what distinguishes nonlinear from linear models where, for example, the definition of "nested" models is mathematically unequivocal (their basis vectors define nested linear subspaces). This is not true for nonlinear models, because the manifolds in question are nonlinear. A detailed understanding and explanation of exactly what this means exceeds my understanding. Doug Bates's PhD thesis and subsequent papers (+ others, no doubt) go into this. Cheers, Bert Gunter Genentech Nonclinical Statistics On Fri, Aug 27, 2010 at 7:45 AM, John Ludlam <ludlam.j...@gmail.com> wrote: > Using the nls function I fit the following model (and some others) to my data. > mod1=nls(CLr ~ A-(A-CLi)*exp(-k*d), start = list(A=60,k=0.005)) > I would like to rank a set of models using AIC. > > I calculated AIC as > AIC(mod1) > > However, it appears to use an incorrect number of parameters (3 > instead of 2). Why is this? > > Additionally, if I calculate AIC using the residuals sum of squares instead > of the log likelihood, the AIC values, and resulting delta AICs differ between > the two approaches. What am I missing? > > RSS=231.5;K=2;N=30 > N*log(RSS/N)+2*K > > Help is appreciated, > > John > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.