Model-based Geostatistics

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This volume is the first book-length treatment of model-based geostatistics. The text is expository, emphasizing statistical methods and applications rather than the underlying mathematical theory. It features analyses of datasets from a range of scientific contexts.
Introduction.- An Overview of Model-Based Geostatistics.- Gaussian Models for Geostatistical Data.- Generalized Linear Models for Geostatistical Data.- Classical Parameter Estimation.- Spatial Prediction.- Bayesian Inference.- Geostatistical Design.
This volume is the first book-length treatment of model-based geostatistics. The text is expository, emphasizing statistical methods and applications rather than the underlying mathematical theory. Analyses of datasets from a range of scientific contexts feature prominently, and simulations are used to illustrate theoretical results. Readers can reproduce most of the computational results in the book by using the authors' software package, geoR, whose usage is illustrated in a computation section at the end of each chapter. The book assumes a working knowledge of classical and Bayesian methods of inference, linear models, and generalized linear models.

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Autor: Peter Diggle
ISBN-13 :: 9781441921932
ISBN: 1441921931
Erscheinungsjahr: 01.12.2010
Verlag: Springer New York
Gewicht: 374g
Seiten: 244
Sprache: Englisch
Auflage Softcover reprint of hardcover 1st ed. 2007
Sonstiges: Taschenbuch, 235x155x13 mm
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