Re: [Rd] Is there an implementation of loess with more than 3 parametric ...

From: Dr. D. P. Kreil (Boku) <>
Date: Fri, 24 Jun 2011 17:03:33 +0200

ink1">Dear John,

> I suggest that you look at the abilities of the mgcv package.
> There are notes of mine at
> that may help you get started.

Thank you very much for the suggestion and the link to your write-up, it was indeed very helpful!

I have experimented with this library for a while now and am really happy about its flexibility. For my immediate applied problem, I will now go with a gam fit ("z~te(x,y)+fa-1").

I note, however, that this is much, much slower than loess, and is thus limited to smaller numbers of data points. (I could not fit the full model to 50,000 data points in a reasonable time.) I am therefore wondering if you knew of a way of also fixing the implementation of loess in R?

>From the error message (recompile with larger d2MAX) it seems that the
underlying Fortran library was perfectly happy to fit a larger number of parametric variables. So is there a way one could remove the restriction to 4 parameters in the R interface/compilation? I have not found an obvious place where d2MAX is defined or configured, I suspect it might be hard-coded...

With best regards,
David. mailing list Received on Fri 24 Jun 2011 - 16:52:32 GMT

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