R help - Nov 2006 - gamm(): degrees of freedom of the fit

I wonder whether any of you know of an efficient way to calculate the
approximate degrees of freedom of a gamm() fit.

Calculating the smoother/projection matrix S: y -> \hat y and then its trace
by sum(eigen(S))$values is what I've been doing so far- but I was hoping
there might be a more efficient way than doing the spectral decomposition of an
NxN-matrix.

The degrees of freedom associated with the linear and smooth parts can be read
from the gam-part of the fitted gamm()-model, but not the degrees of freedom
associated with the random effects. For lmer()-models, there is hatTrace() but I
know of nothing of the sort for lme()-Objects.

Maybe somebody has some code or ideas to share?



--

On Wed, 1 Nov 2006, Fabian Scheipl wrote:
>
> Calculating the smoother/projection matrix S: y -> \hat y and then its 
> trace by sum(eigen(S))$values is what I've been doing so far- but I was
> hoping there might be a more efficient way than doing the spectral 
> decomposition of an NxN-matrix.
>
Well, there are more efficient ways to compute the trace of a matrix than 
spectral decomposition. The trace is just the sum of the diagonal 
elements: sum(diag(S))

 	-thomas