Differences of variogram parameters fitted by gstat and automap
I don't know much about "autofitVariogram" fuction in the "automap" package but I am pretty familiar with the "fit.variogram" function in the "gstat". One possibility for getting different parameter estimates is that the two methods are using two different objective functions for fitting the variogram. For example, I know that gstat has options for various weighted least squares solutions. I have played around with a few of the weighted least squares options and I get highly variable results for the same data, depending on which weights I use. Also, check that your exponential models are expressed the same in both programs. Hope this helps, Kerry
On 9/9/2010 7:44 AM, K Z wrote:
Dear all, I am currently fitting variograms using both the "autofitVariogram" fuction in the "automap" package and the "fit.variogram" function in the "gstat" package. I used "autofitVariogram" to fit variograms at first, and then I used estimated parameters as the input of the "fit.variogram" function. However, I found the estimated parameters are largely different. For example, the estimated parameters by the "autofitVariogram" function are $var_model model psill range kappa 1 Nug 2.47 0 0 2 Ste 1.41 2506 10 the estimated parameters by the "fit.variogram" function are: model psill range kappa 1 Nug 0.74 0 0 2 Ste 3.03 1269 10 I tried the "exponential" model structure, and got similar results. I understand I probably cannot exactly same results, but I expect I can get similar results. Any suggestion? I appreciate your response and best regards, Kai
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********************** Kerry Ritter, Ph.D. statistician Southern California Coastal Water Research Project 3535 Harbor Blvd., Suite 110 work: 714-755-3210 cell: 714-420-3346 fax: 714-755-3299 email: kerryr at sccwrp.org