`gam' in package `mgcv' will let you supply any smoothing parameter you want (via argument `sp') and will get the fit and corresponding GCV score for you (`gcv.ubre' in the `gam' object). The CV score you'd have to calculate yourself, but `influence.gam' will extract the necessary H_ii. See the examples in ?smooth.construct for how to use the truncated polynomial basis with mgcv:gam.
On Tuesday 31 March 2009 15:22, Nora Velvet wrote: > I received an assignment that I have to do in R, but I'm absolutely not > very good at it. > The task is the following: > http://www.nabble.com/file/p22804957/question8.jpg > > To do this, we also get the following pieces of code (not in correct > order): http://www.nabble.com/file/p22804957/hints.jpg > > I'm terrible at this and I'm completely stuck. The model I chose can be > found in here: > myknots6 = c(20,24,34) > p.spline8 = spm(accel ~ > f(times,basis="trunc.poly",degree=2,knots=myknots6)) > > Can someone please help me with this task? I'm kind of desperate. > > Thank you! -- > Simon Wood, Mathematical Sciences, University of Bath, Bath, BA2 7AY UK > +44 1225 386603 www.maths.bath.ac.uk/~sw283 ______________________________________________ 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.
