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

[Eliot McIntire]

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

-- 
Eliot McIntire
NSERC Post Doctoral Fellow
Department of Ecosystems and Conservation Science
College of Forestry and Conservation
University of Montana, Missoula, MT 59812
406-243-5239
fax: 406-243-4557
emcintire at forestry.umt.edu