[R-sig-Geo] Fitting nested variograms to empirical variograms

[Paulo Justiniano Ribeiro Jr]

Dear Elliot

I entirely agree with Ole's comments and would just add the following:

- with geoR the only thing you can do is to overimpose to an epirical
variogram a theoretical nested variogram using lines.variomodel()
which internally calls cov.spatial()

- cov.spatial() is able to compute values of nested variogram, so you
could use it as ingredient for other computation
bearing in mind whether this is really useful and whether these things
are really estimable

best
P.J.

On Thu, 14 Oct 2004, Ole F. Christensen wrote:

> Dear Elliot
>
> I can only comment on the geoR related question, since I am unfamiliar
> with gstat.
>
> Reading the help-file for variofit, then I think it is rather clear that
> this functions assumes one variogram model [i.e. the format of the
> estimated parameters is a vector].
> So fitting nested model using that function seems not possible.
> I agree with you that the help-file for cov.spatial gives the impression
> that nested variables are allowed for that function.
> And it also is bit misleading that  the help-file for variofit  refers
> to  cov.spatial, hinting that the full functionality of cov.spatial can
> be used in variofit.
> I hope the author of the package can provide more details on this
> [therefore copy to him].
>
> I have no experience fitting nested variogram models myself, but my
> general opinion is that nested variograms aren't really useful, since
> what matters the most is
> to make a good fit of the empirical variogram near the origin. And if
> one really wants to make a very careful fit of a variogram-model to the
> data, then the likelihood function should be used rather than fitting to
> the empirical variogram.
>
> Ole
>
>
> Eliot McIntire wrote:
>
> > Hello,
> >
> > I am new to the list, but I have searched for an answer to this
> > question  in the list archives and couldn't find anything.
> >
> > Question:
> > Does anybody have experience with fitting nested variogram models in
> > R?  I  am not having success.
> >
> > Details:
> > I am trying fit a nested variogram to an empirical variogram.  I have
> > tried both gstat and geoR which appear able to do this, but I have
> > come  across these problems:
> >
> > geoR: I can only run nested variogram models using cov.spatial and
> > this is  not suitable to fit a model to an empirical variogram.  In
> > the help manual  it says that I should inherit cov.spatial in the
> > variofit function,  however, it does not seem to work.  I get:
> > Error in match.arg(cov.model, choices = c("matern", "exponential",
> > "gaussian",  :
> >         there is more than one match in match.arg
> > my code: F2.1Y.wls.exp = variofit(F2.1Y,
> > ini.cov.pars=starting.values,  fix.nugget=F,
> > nugget=starting.values.vec, cov.model=c("exp","spherical"))
> >
> > gstat: I can run nested models using
> > F2.BA1.fit = fit.variogram (F2.BA1.variogram, vgm(psill=33,"Lin",6,
> > add.to  = vgm(psill=33,"Lin",6, nugget=20) )
> >                 , print.SSE=T, fit.sills=T, fit.ranges=T )
> >
> >
> > but I never seem to get a good fit, i.e., it always fails to fit the
> > empirical variogram.
> >
> > If anyone has a solution, I also need to calculate the Residual Sums
> > of  Squares to test for the relative fit.
> >
> > Thank you,
> > Eliot
> >
>
> --
> Ole F. Christensen
> BiRC - Bioinformatics Research Center
> University of Aarhus
>
>
>
>

Paulo Justiniano Ribeiro Jr
Departamento de Estatística
Universidade Federal do Paraná
Caixa Postal 19.081
CEP 81.531-990
Curitiba, PR  -  Brasil
Tel: (+55) 41 361 3573
Fax: (+55) 41 361 3141
e-mail: paulojus at est.ufpr.br
http://www.est.ufpr.br/~paulojus

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