`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