All smooths in a GAM are `centred' in order to ensure model
identifiability. This means that a smooth, s, is estimated subject to the
constraint that \sum_i s(x_i)=0, where, x_i, are the covariate values.
So you can't transform back to the response scale just by applying the
inverse link, even
Sorry if this is an obvious question...
I'm estimating a simple binomial generalized additive model using the
gam function in the package mgcv. The model makes sense given my data,
and the predicted values also make sense given what I know about the
data.
However, I'm having trouble
