## AI-GEOSTATS: sample distances bigger than range

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• hell list, i did a little exercise with ordinary kriging with extreme sample distances. as i understand: if all distances between samples and gridpoint are
Message 1 of 2 , Dec 17, 2003
hell list,

i did a little exercise with ordinary kriging with extreme sample distances.
as i understand: if all distances between samples and gridpoint are bigger
than the range, the kriging estimation should be equal to the sample mean =>
all samples should get the same weight.

in my example everything works well as long as the sample-grid-point
distances are smaller than the range. when i "put" all sample-points very
far away from the gridpoint (without changing the spatial pattern!) then the
values of the right hand side (d-kovariance-matrix/vector) become zero
except for the lagrange parameter (=1), that's ok, but why do the weights
all get individual values and the estimated value is not equal the
arithmetic mean ?? is there any mistake i don't recognized

hope someone can help

Lorenz Dobler

Universität Münster
Institut für Geoinformatik
Robert-Koch-Strasse 26-28
D-48149 Münster

Tel.: 0251/83-30089
Fax: 0251/83-39763
email: doblerl@...

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• Lorenz Your samples also have to be out of the range of influence of one another to get equal weights. The left hand side of the equations needs to be an
Message 2 of 2 , Dec 17, 2003
Lorenz

Your samples also have to be out of the range of
influence of one another to get equal weights. The
left hand side of the equations needs to be an
identity matrix (well, with the total sill down the
diagonal and zeroes everywhere else) to get equal
weights.

Isobel {Clark}
http://geoecosse.bizland.com/whatsnew.htm

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