[Rd] Is there an implementation of loess with more than 3 parametric ...
Dr. D. P. Kreil (Boku)
David.Kreil at boku.ac.at
Fri Jun 24 17:03:33 CEST 2011
> 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,
More information about the R-devel