## Re: [ai-geostats] Typical sample sizes for variogram calculations

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• Mark, this really depends on how you want to estimate the parameters of the covariance / variogram. If you want to use maximum likelihood, then due to the need
Message 1 of 4 , Nov 4, 2004
Mark,

this really depends on how you want to estimate the parameters of the
covariance / variogram. If you want to use maximum likelihood, then due
to the need to invert a matrix, which is O(n^3), generally sizes above
about 1000 become rather prohibitive on a desktop computer. One possible
alternative that attempts to retain statistical rigour but scale
gracefully with sample size is our Sparse Sequential method:

http://www.ncrg.aston.ac.uk/~csatol/ogp/index.html

Alternatively you could use methods of moment estimators (i.e. the
classic sample variogram) and fit these empirically using some function.
Note that in computing the sample variograms one can work in a
sequential fashion, so that not all pair comparissons need be stored,
but they must be computed .... so it will be slower, scaling as O(n^2)
in the computation of the sample variogram.

cheers

Dan

Mark Coleman wrote:
> Greetings,
>
> I am coding some basic geostatistical procedures and was curious about
> the "typical" sorts of sample sizes researchers run into. I know that
> sizes of n=1000 are fairly common. How about sizes of N=10,000 or
> greater? Are variograms computed on samples this large?
>
> Thanks,
>
> -mark
>
>
>
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--

Dr Dan Cornford d.cornford@...
Computer Science
Aston University
Aston Triangle tel +44 (0)121 204 3451
Birmingham B4 7ET fax +44 (0)121 333 6215

http://www.ncrg.aston.ac.uk/~cornfosd/
• Mark Our free downloadable data sets range from 16 to over 20,000. The biggest set I worked wth was a small section of a South African gold mine - 450,000.
Message 2 of 4 , Nov 4, 2004
Mark