Is there an implementation of loess with more than 3 parametric ...

Dear John,

I suggest that you look at the abilities of the mgcv package.
There are notes of mine at

http://www.maths.anu.edu.au/%7Ejohnm/r-book/xtras/autosmooth.pdf

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.