The kriging update equations and their application to the selection of neighboring data |
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| Authors: | Xavier Emery |
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| Institution: | (1) Department of Mining Engineering, University of Chile, Avenida Tupper 2069, Santiago, 837 0451, Chile |
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| Abstract: | A key problem in the application of kriging is the definition of a local neighborhood in which to search for the most relevant
data. A usual practice consists in selecting data close to the location targeted for prediction and, at the same time, distributed
as uniformly as possible around this location, in order to discard data conveying redundant information. This approach may
however not be optimal, insofar as it does not account for the data spatial correlation. To improve the kriging neighborhood
definition, we first examine the effect of including one or more data and present equations in order to quickly update the
kriging weights and kriging variances. These equations are then applied to design a stepwise selection algorithm that progressively
incorporates the most relevant data, i.e., the data that make the kriging variance decrease more. The proposed algorithm is
illustrated on a soil contamination dataset. |
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| Keywords: | Kriging weights Kriging variance Additivity relationships Stepwise data selection Moving neighborhood |
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