
Thank you for your answer !
 
Actually I'm doing an internship about GAM for mid-term french load forecasting (at "EDF", Electricité De France). I'm working with your book and I was asked to simulate data on my own, in order to see if gam (from mgcv) gave good estimations of the functions I had used for simulation, even with explicative variables like the load of the previous day, or with correlated noise. 
 
We knew that it was possible to get the coefficients and so, at this moment of our work, we wondered if there was a way to get the actual bases in order to estimate a "distance" between our original functions and the functions estimated by gam. In the meantime, I have created a new "instrumental" data frame with many points from the definition areas of my original functions, and used predict.gam on it with link="terms". 
 
Amandine.
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