[R] two basic question regarding model selection in GAM

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Qusetion #1
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Model selection in GAM can be done by using:
1. step.gam {gam} : A directional stepwise search
2. gam {mgcv} : Smoothness estimation using GCV or UBRE/AIC criterion

Suppose my model starts with a additive model (linear part + spline part).
Using gam() {mgcv} i got estimated degrees of freedom(edf) for the smoothing
splines. Now I want to use the functional form of my model taking estimated
degrees of freedoms in step.gam() {gam} to search a better model.

You know mgcv masks over gam. So i can not use gam after using mgcv. Is
there any way to stop mgcv.

Qusetion #2
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Suppose i have three models:
M1. GAM with thin plate regression spline(TPRS)
M2. GAM with cubic regression spline(CRS)
M3. GAM with some TPRS and CRS

To choose best model among the three, can i use their GCV/AIC/UBRE
criterion?
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