Re: AI-GEOSTATS: Variogram estimation
- View SourceI do not know if it is a rule of thumb. But it also depends on the
variability of your data values. I think it is quite subjective how much
pairs you will use.
But you should also consider some more robust variogram estimators as correlogram or standardized variograms to see if
there are no artificial structures or erratic structures caused by extreme
values or outliers or even trends...
There is a paper which is quite interesting:
Srivastava, R.M.; Parker, H.M., 1989:Robust measures of spatial
continuity. In: Armstrong, M., 1989 (editor):Geostatistics. Vol.I.
Dordrecht, pp. 295-308.
On Wed, 1 May 2002, Arie Croitoru wrote:
> Dear list members,
> Following Ruben Roa's email, I would like to add that I did not find any clear criterion to what is the minimum number of data pairs that should be used in each lag and this would certainly affect the variogram uncertainty. I know that a minimum of 30 data pairs is used frequently but my impression is that this is a "rule of thumb". I guess this rule originated from the central limit theorem (?). I found that the lack of a clear criterion might have a big effect on the estimation of the Variogram especially in cases where the data points are non regular and in cases where a non parametric variogram might be considered.
> I would gratefully appreciate any comments on this as well.
Ulrich Leopold MSc.
Department of Physical Geography
Institute for Biodiversity and Ecosystem Dynamics
Faculty of Science
University of Amsterdam
Nieuwe Achtergracht 166
Phone: +31-(0)20-525-7456 (7451 Secretary)
Check us also out at:
Netherlands Centre for Geo-ecological Research
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