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Tag: Earth Sciences

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  • 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, but does not require previous exposure to spatial statistical models or methods. The authors have used the material in MSc-level statistics courses.

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  • In the world of reality, we are often faced with describing and predicting the results of experiments. A mathematical model is a set of equations that encapsulates reality; it is a caricature of the real physical system that aids in our understanding of real phenomena. A good model extracts the essential features of the problem and lays out, in a simple manner, those processes and interactions that are important. By design, mathematical models should have predictive capability.

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