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 beca
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 1
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 th
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)
x3<-rpois(50
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