Titlebook: Interpolation of Spatial Data; Some Theory for Krig Michael L. Stein Book 1999 Springer Science+Business Media New York 1999 Kriging.Likeli

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Properties of Random Fields,Billingsley (1995), Chung (1974), or Feller (1971)) should, for the most part, suffice. When interpolating a random field, the local behavior of the random field turn out to be critical (see Chapter 3). Accordingly, this chapter goes into considerable detail about the local behavior of random fields and its relationship to spectral theory.

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Linear Prediction,o obtain reasonable assessments of the uncertainty in these predictions. The approach to prediction I take is to consider the spatially varying quantity to be a realization of a real-valued random field, that is, a family of random variables whose index set is ..

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Equivalence of Gaussian Measures and Prediction, Supposing that our observations and predictions will all take place in some bounded region ., a useful first question to ask is what can be done if we observe the process everywhere in . Answering this question will put an upper bound on what one can hope to learn from some finite number of observations in .

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0172-7397 ences, and geography. Kriging, a prediction scheme defined as any prediction scheme that minimizes mean squared prediction error among some class of predictors under a particular model for the field, is commonly used in all these areas of prediction. This book summarizes past work and describes new

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Michael L. Stein ist die gemeinsame Sprache für die unverzichtbare Kommunikation zwischen späteren Anwendern, die beschreiben, was sie mit der Software machen wollen und Architekten, Testern, Analytikern und Programmierern, die die Software schließlich implementieren..978-3-658-14411-1978-3-658-14412-8