436RE: AI-GEOSTATS: Declustering
- Nov 16, 2001
> I am slightly confused:The semi-variogram is calculated on the difference
> ... if sampling is clustered preferentially in
> e.g. > higher values
> areas, would this not bias the semi-variogram for
> the first few lags?...at
> least if, as it can happen, the variance is related
> to the mean.
between the two sample values. If the basic
assumptions for semi-variogram construction are
correct, differences are unrelated to the actual value
of each sample or to the actual absolute location of
the pair. Therefore, clustering does not influence the
If you have a situation where variance is related to
the mean, e.g. with highly skewed data, you need to
transform these values in some way before constructing
a semi-variogram. This is true whether or not you have
clustered sampling. Absolutely regular sampling will
not give you a valid semi-variogram if you violate the
assumptions upon which it is based.
> What about the effects of the possibleclustering?
> over-estimation of the global mean due to
If you are estimating the global mean based on a
distribution model, you need to decluster. If you are
estimating the global meaning on the basis of a kriged
grid, you do not need to decluster as the kriging
system does that for you.
You can experiment with these questions using our
totally free unlimited kriging game. This can be found
in my 'briefcase' at
Does this help?
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