The functional form is given in chapter 4 of my book:
Wood S.N. (2006) Generalized Additive Models: An Introduction with R.
Chapman and Hall/CRC Press. (reserve your copy now for christmas)
... but note that by default mgcv reparameterises so that the
identifiability constraints on the smoo
Anke,
mgcv:predict.gam certainly didn't produce `something like a
negative log-likelihood of occurrence', but is it possible that one of
your maps is on the probability scale and the other on the linear
predictor scale?
If you used predict.glm(model1,type="response"), but
predict.gam(model2
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