From David.Kreil at boku.ac.at  Fri Jun 24 17:03:33 2011
From: David.Kreil at boku.ac.at (Dr. D. P. Kreil (Boku))
Date: Fri, 24 Jun 2011 17:03:33 +0200
Subject: [Rd] Is there an implementation of loess with more than 3
	parametric ...
In-Reply-To: <9C83044E-C107-4F77-AD1D-4042A679C54B@anu.edu.au>
References: <9C83044E-C107-4F77-AD1D-4042A679C54B@anu.edu.au>
Message-ID: <BANLkTikBYNqH5uhf4CzDOcPyQpKTYZZQDA@mail.gmail.com>

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.



[Rd] Is there an implementation of loess with more than 3 parametric ...
Dr. D. P. Kreil (Boku