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Interpolation of Spatial Data: Some Theory for Kriging (Springer Series in Statistics) - Hardcover
Book 43 of 160: Springer Series in Statistics
Synopsis
A summary of past work and a description of new approaches to thinking about kriging, commonly used in the prediction of a random field based on observations at some set of locations in mining, hydrology, atmospheric sciences, and geography.
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About the Author
Michael L. Stein is Professor of Statistics at the University of Chicago.
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Interpolation of Spatial Data: Some Theory for Kriging (Springer Series in Statistics)
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Interpolation of Spatial Data: Some Theory for Kriging (Springer Series in Statistics)
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Interpolation of Spatial Data: Some Theory for Kriging (Springer Series in Statistics)
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Interpolation of Spatial Data: Some Theory for Kriging (Springer Series in Statistics)
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Interpolation of Spatial Data: Some Theory for Kriging (Springer Series in Statistics)
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INTERPOLATION OF SPATIAL DATA (EN INGLÉS)(TAPA DURA)
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GENERICA, DE VECCHI EDICIONES, S.A., 1999
ISBN 10: 0387986294
ISBN 13: 9780387986296
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Rústica. Condition: Muy Bien. Dust Jacket Condition: Muy Bien. 1. Prediction of a random field based on observations of the random field at some set of locations arises in mining, hydrology, atmospheric sciences, 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 approaches to thinking about kriging. LIBRO. Seller Inventory # 144927
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Interpolation of Spatial Data: Some Theory for Kriging (Springer Series in Statistics)
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SPRINGER VERLAG, 1999
ISBN 10: 0387986294
ISBN 13: 9780387986296
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Interpolation of Spatial Data: Some Theory for Kriging (Springer Series in Statistics)
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Interpolation of Spatial Data: Some Theory for Kriging (Springer Series in Statistics)
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Interpolation of Spatial Data: Some Theory for Kriging (Springer Series in Statistics)
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