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(More customer reviews)I was very interested in "Model-based Geostatistics" by Diggle and Ribeiro because I teach a course in applied geostatistics. The book was informative. The preface was interesting read because most of the geostatistics of which I am familiar is based upon the work of Matheron. I was unaware that the Matheron work was "developed largely independently of the mainstream of spatial geostatistics." Topics that were of interest to me were ones such as 2.3 Exploratory data analysis. This concept is often not emphasized enough. Another interesting section was 6.4 What does Kriging actually do to the data? Section 8.1 Choosing the study region was interesting, but, as the authors state "...is often pre-determined by the context of the investigation...." Choosing the sample locations: Uniform designs (8.2) was another interesting section.
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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. 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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