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

Ben Bolker bbolker at gmail.com
Mon Jun 27 17:19:55 CEST 2011


Dr. D. P. Kreil (Boku <David.Kreil <at> boku.ac.at> writes:

> 
> 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...
> 

  If you go looking for d2MAX in the R code (i.e. download the entire
source or get a copy of the SVN tree) you will proceed as follows:

 find . -name "*.c" -exec grep -l d2MAX {} \;


takes you to ./src/library/stats/src/loessc.c

Looking therein finds:

 case 105:MSG("k>d2MAX in ehg136.  Need to recompile with increased dimensions.")

  grep 105 *.f finds loessf.f

within which we find two lines (1240 and 1361)

      if(k .gt. 15)   call ehg182(105)

Searching for "15" then finds a *lot* of places where "15" is 
hardcoded in the file.

 To modify the file you could either blindly change all the hard-coded
"15" dimensions to something larger and hope that it worked (i.e., use
a good test suite to make sure you didn't screw something up) or dig
through the code and understand it in detail to know what should
be changed ...



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