Let me take a stab at the cross-validation part first:

Deutch and Journel (GSLib 1998) suggest examining cross-validated residuals
keeping in mind that kriging estimates should be symmetric around zero with
minimal spread, globally and conditionally unbiased, homoscedastic, and
spatially-independent.  I would hesitate on quantitatively evaluating a
model strictly on one error statistic (see Isaaks and Srivastava 1989).

As for the choice of your model, it depends on what makes sense for what you
are studying.  If you have a pure nugget effect (no detectable range) but
you think there truly is a dependent effect then you might conclude that the
spatial dependence is occurring at a resolution below the minimum lag
distance. I've seen some folks recommend shortening the x-axis of the
variogram to about 1/6 the total lag distance and concentrate on modeling
the short lags well.

Variowin:  I've been using the numerical output file (.var) and importing it
into excel to plot the "data" variograms.  Just remember that the values
aren't "standardized" in that file, so for example if you want to plot the
covariance in the form of a variogram you have to subtract the covariance
from the global sample variance, etc.  As for the model parameters, the
range, nugget, and sill are given in the Model program.  You can plug those
values directly into the equation for the spherical model for plotting in
another program.

Hope this helps.

*************************************************
Sara Kustron
Boston University Department of Geography
675 Commonwealth Avenue Rm 445
Boston, MA 02215

[EMAIL PROTECTED]
office: (617) 353-8341
**************************************************




----- Original Message -----
From: "Juliann Aukema" <[EMAIL PROTECTED]>
To: <[EMAIL PROTECTED]>
Sent: Monday, April 09, 2001 5:22 PM
Subject: AI-GEOSTATS: Variowin equations and cross-validation


> Hi,
>
> Variowin/equation questions:
>
>      I have fitted models using variowin and am now trying to plot them in
> other graphics programs. Vario2D produces a file that I can use to plot
the
> experimental variograms, but in the modeling I get an equation like:
> gamma(h) = 14.2 + 6.399 Sph. 169.66(h)
> I am wondering how to turn the exponential, spherical or power into some
> sort of equation that another program can plot. Can anyone point me in the
> direction of these equations  (other than the manual, which  is out of
> print)?
> While I'm asking, the sill reported in variowin is always about half of
> what the sill appears to be from looking at it graphically. What is the
> reason for this difference?
>
> Cross-validation:
>
>       Any hints for using cross-validation to compare models?  What does
it
> mean if the average error and the square root of the average squared
> normalized error are of both models are similar and close to 0 or 1
> respectively?
>      Specifically,  I fitted models using Variowin (the file is too large
> for Geoeas) and I found a pure nugget model in the same way.  Variowin
> gives a goodness of fit measure, and the fitted model was in all cases
> "better" than the pure nugget model. When I did the cross validation in
> Geoeas,  the models seemed pretty good (for example, with values raning
> from 0-54, average error = -0.093, and the standard deviation of the
Zscore
> was 1.16. The estimated values were somewhat underestimated, only ranging
> from 0-17). However, the pure nugget effect seemed to be pretty good also
> and not terribly different from the model (in this example, av. error =
> 1.665, which is further from 0, but sd of zscore = 1.027, which is closer
> to 1. The estimates ranged from 0-14).  Several models I looked at didn't
> seem to have huge differences between the fitted model and a pure nugget
> model.
>        So, does this mean that  there is not a clear spatial effect here?
> That there may be a weak spatial effect? That there is definitely not a
> spatial effect? Is there some way to test for significance of  difference
> between the models?. . .
>
> Thank you.
>
> Juliann Aukema
> [EMAIL PROTECTED]
>
>
>
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