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. ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel