Sorry, just got back into town. I wonder if AIC, BIC, or cross-validation scoring couldn't also be used as criteria for model selection - I've seen it mostly in the context of variable selection rather than 'form' selection but in principle might apply here?
--- Dieter Menne <[EMAIL PROTECTED]> wrote: > Andrew Clegg <andrew.clegg <at> gmail.com> writes: > > > > > ... If I want to demonstrate that a non-linear curve fits > > better than an exponential, what's the best measure for that? Given > > that neither of nls() or optim() provide R-squared. > > To supplement Karl's comment, try Douglas Bates' (author of nls) comments > on the > matter > > http://www.ens.gu.edu.au/ROBERTK/R/HELP/00B/0399.HTML > > Short summary: > * ... "the lack of automatic ANOVA, R^2 and adj. R^2 from nls is a > feature, > not a bug :-)" > * My best advice regarding R^2 statistics with nonlinear models is, as > Nancy > Reagan suggested, "Just say no." > > Dieter > > ______________________________________________ > R-help@stat.math.ethz.ch 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@stat.math.ethz.ch 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.