[R] How to avoid overfitting in gam(mgcv)

[Ariyo Kanno]

I appreciate your quick reply.
I am using the model of the following structure :

fit <- gam(y~x1+s(x2))

,where y, x1, and x2 are quantitative variables.
So the response distribution is assumed to be gaussian(default).

Now I understand that the data size was too small.
Thank you.

Best Wishes,

Ariyo

2007/10/3, Simon Wood <s.wood at bath.ac.uk>:
> What sort of model structure are you using? In particular what is the response
> distribution? For poisson and binomial then overfitting can be a sign of
> overdispersion and quasipoisson or quasibinomial may be better. Also I would
> not expect to get useful smoothing parameter estimates from 10 data!
>
> best,
> Simon
>
> On Wednesday 03 October 2007 06:55, $B?@LnM- at 8(B wrote:
> > Dear listers,
> >
> > I'm using gam(from mgcv) for semi-parametric regression on small and
> > noisy datasets(10 to 200
> > observations), and facing a problem of overfitting.
> >
> > According to the book(Simon N. Wood / Generalized Additive Models: An
> > Introduction with R), it is
> > suggested to avoid overfitting by inflating the effective degrees of
> > freedom in GCV evaluation with
> > increased "gamma" value(e.g. 1.4). But in my case, it didn't make a
> > significant change in the
> > results.
> >
> > The only way I've found to suppress overfitting is to set the basis
> > dimension "k" at very low values
> > (3 to 5). However, I don't think this is reasonable because knots
> > selection will then be an
> > important issue.
> >
> > Is there any other means to avoid overfitting when alalyzing small
> > datasets?
> >
> > Thank you for your help in advance,
> > Ariyo Kanno
> >
> > --
> > Ariyo Kanno
> > 1st-year doctor's degree student at
> > Institute of Environmental Studies,
> > The University of Tokyo
> >
> > ______________________________________________
> > R-help at 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.
>
> --
> > Simon Wood, Mathematical Sciences, University of Bath, Bath, BA2 7AY UK
> > +44 1225 386603  www.maths.bath.ac.uk/~sw283
>
> ______________________________________________
> R-help at 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.
>