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. -- View this message in context: http://www.nabble.com/GAM-with-constraints-tf4869470.html#a13987796 Sent from the R help mailing list archive at Nabble.com. ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
