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Hierarchical modeling and analysis for spatial data. (English) Zbl 1053.62105
Monographs on Statistics and Applied Probability 101. Boca Raton, FL: Chapman and Hall/CRC (ISBN 1-58488-410-X/hbk; 978-0-203-48780-8/ebook). xvii, 452 p. (2004).
This book deals with the subject of hierarchical methods, modeling and data analysis for spatial and spatio-temporal data. After giving an overview of spatial data problems and a discussion on the basics of point-referenced data models and areal data models and a review of the basics of Bayesian inference, the authors investigate the area of hierarchical modeling for univariate spatial data. In addition, they consider the problems of spatial misalignment, methods for handling multivariate spatial responses, spatiotemporal models and spatial survival models. The last chapter in the book deals with special topics in spatial process modeling including spatial varying coefficients models. An appendix at the end of the book contains some elements of matrix theory relevant for use for the material discussed in the book, and a discussion on spatial computing methods using Gibbs sampling and MCMC sampling methods.
The book contains a wealth of material not available elsewhere in a unified manner. Each chapter contains worked out examples using some well known software packages and has exercises with related computer code and data on a supporting web page. The book is up to date in its coverage.
Having said this, I am not however in agreement with the authors that the book can be used as a textbook for a course even though one of the authors mentions that he has used a preliminary version for a course. A textbook needs a formal approach to the subject for a clear understanding of the subject apart from details in the development of mathematical techniques needed for the subject. My impression is that the book is more a collection of various topics put together from this new and importnat area of hierarchical modeling and spatial data analysis. In spite of the comments made above, the book is an important addition to the literature on spatial data analysis.

MSC:
62M30 Inference from spatial processes
62H11 Directional data; spatial statistics
62-02 Research exposition (monographs, survey articles) pertaining to statistics
62M99 Inference from stochastic processes
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