[R] GAM with constraints

[lubaroz]

Simon Wood-4 wrote:
> 
> Are you interested in equality constraints or inequality constraints?
> 
No, I am interested in 2 kinds of inequality constraints: 
1) monotonic splines
2) positive coefficients of the variables, which are not splines.
It seems that pcls should be able to deal with both of them, if smoothing
parameters are given, should it not?


Simon Wood-4 wrote:
> 
> `pcls' is really useful for the inequality constraint case (e.g. when you
> want 
> shape preserving smooths). For fixed smoothing parameters you can embed
> this 
> in an IRLS loop for gam fitting also, but convergence can be tricky, and 
> smoothing parameter selection not so straightforward.
> 
The question here is how one can obtain smoothing parameters, given
inequality constraints. I've read your article "Monotonic smoothing splines
fitted by cross-validation", where you explain how the penalties are
calculated. Is there a routine in R that can do it? 

I want to build a GAM regression with constraints using performance
iteration, which updates the penalties taking the constraints in account. Do
you think this would improve the model compared to one where penalties are
generated without constraints, and then the coefficients are calculated
using pcls() with all the constraints?

  Luba
P.S. Thank you for your detailed answer.
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