Springer
Model-Based Geostatistics
Model-Based Geostatistics
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This volume is the first book-length treatment of model-based geostatistics. Geostatistics is concerned with estimation and prediction problems for spatially continuous phenomena, using data obtained at a limited number of spatial locations. Model-based geostatistics refers to the application of general statistical principles of modeling and inference to geostatistical problems. The authors have written an expository text, 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' R-based 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.
Author: Peter Diggle,Paulo Justiniano Ribeiro
Publisher: Springer
Published: 12/01/2010
Pages: 232
Binding Type: Paperback
Weight: 0.77lbs
Size: 9.21h x 6.14w x 0.52d
ISBN: 9781441921932
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