Titlebook: Geostatistics for Engineers and Earth Scientists; Ricardo A. Olea Book 1999 Kluwer Academic Publishers 1999 Estimator.Kriging.Time series.

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Ordinary Kriging, seen that simple kriging requires knowledge of the mean to solve the problem of finding weights that minimize the variance of the estimation error. Ordinary kriging elegantly discards the requirement by filtering out the mean, taking advantage of Corollary 2.11. And by removing the mean from the es

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Universal Kriging,d an effort to lift the constant mean requirement by moving from a global constant mean to a locally constant mean. There are several instances of attributes— water depth near the shore, temperature in the upper part of the earth’s crust, water table elevation in the High Plains aquifer of Kansas—th

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imperfectly describe natural processes or attributesmeasured at geographical locations. Inference from imperfect knowledgeis the realm of classical statistics. In the case of many naturalphenomena, auto- and cross- correlation preclude the use of classicalstatistics. The appropriate choice in such

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Sebastian Gawron,Sebastian Gerthributes— water depth near the shore, temperature in the upper part of the earth’s crust, water table elevation in the High Plains aquifer of Kansas—that have a clear systematic variation. Models that presume constancy of the mean are inadequate for the characterization of such attributes.