Hi Carlos, there is no possible way you can compare both models using a classical statistical framework, be it ML, REML or otherwise. The assumptions are violated. Regarding the df, see my previous mail.
In your case, I'd resort to the AIC/BIC criteria, and if prediction is the main focus, compare the predictive power of both models using a crossvalidation approach. Wood suggests in his book also a MCMC approach for more difficult comparisons. Cheers Joris On Tue, Jun 22, 2010 at 1:31 AM, Carlo Fezzi <c.fe...@uea.ac.uk> wrote: > Hi Christos, > > thanks for your kind reply, I agree entirely with your interpreation. > > In the first model comparison, however, "anova" does seem to work > according to our interpretation, i.e. the "df" are equal in the two model. > My intuition is that the "anova" command does a fixed-effect test rather > than a random effect one. This is the results I get: > > anova(f1$lme,f2$lme) > > Model df AIC BIC logLik > f1$lme 1 5 466.6232 479.6491 -228.3116 > f2$lme 2 5 347.6293 360.6551 -168.8146 > > Hence I was not sure our interpretation was correct. > > On your second regarding mode point I totally agree about the appealing of > GAMs... howver, I am working in a specific application where the quadratic > function is the established benchmark and I think that testing against it > will show even more strongly the appeal of a gamm approach. Any idea of > which bases could work? > > Finally thansk for the tip regarding gamm4, unfortunately I need to fit a > bivariate smooth so I cannot use it. > > Best wishes, > > Carlo > > > > -- Joris Meys Statistical consultant Ghent University Faculty of Bioscience Engineering Department of Applied mathematics, biometrics and process control tel : +32 9 264 59 87 joris.m...@ugent.be ------------------------------- Disclaimer : http://helpdesk.ugent.be/e-maildisclaimer.php ______________________________________________ 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.
