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maxdist for kriging with an external drift

May be worth adding here that, despite algorithms and the
"funny naming conventions" (good descrition Edzer!)
SK and others are diferent in the following way:

SK, as described in Edzer post, assumes you **know** the mean, in other 
words, there is no uncertainty about it.
On the other hand, variants such as OK, UK, KED, SKlm uses (explicitly 
or implicitly) estimated means.
Therefore, such uncertainty has to be propagated and reflected in the 
predictions.

Suposse the fixed mean in SK is the same as the (implicitly) estimated by 
OK. The point predictions will be the same, however, the uncertainty 
around them will not (and should not) refleting  the uncertainty (or lack 
of it) in the process mean.
The prediction variance expressions for SK ond OK will reflect this
whatever the kriging neighborhood is used.

best
P.J.
On Tue, 26 Jan 2010, Edzer Pebesma wrote:

            
Paulo Justiniano Ribeiro Jr
LEG (Laboratorio de Estatistica e Geoinformacao)
Universidade Federal do Parana
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CEP 81.531-990
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Tel: (+55) 41 3361 3573
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e-mail: paulojus AT  ufpr  br
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