Re: [R] mgcv: increasing basis dimension

That's interesting. Playing with the example, it doesn't seem to be a local minimum. I think that this happens because, although the higher rank basis contains the lower rank basis, the penalty can not simply suppress all the extra components in the higher rank basis and recover exactly what

Re: [R] mgcv: increasing basis dimension

Hi Greg, Recent mgcv versions use extended quasi-likelihood in place of the likelihood for (Laplace approx) REML with quasi families (e.g. McCullagh and Nelder, GLM book 2nd ed section 9.6): this fixes the problems with trying to use the quasi-likelihood directly with REML. best, Simon On

Re: [R] mgcv: increasing basis dimension

thanks Simon I'll upgrade R to try t2. The data I'm actually analysing requires scaled Poisson so I don't think REML is an option. thanks Greg On 14/02/12 11:22 Simon Wood wrote: That's interesting. Playing with the example, it doesn't seem to be a local minimum. I think that this happens

[R] mgcv: increasing basis dimension

hi Using a ts or tprs basis, I expected gcv to decrease when increasing the basis dimension, as I thought this would minimise gcv over a larger subspace. But gcv increased. Here's an example. thanks for any comments. greg #simulate some data set.seed(0) x1-runif(500) x2-rnorm(500)