A textbook and reference describing hierarchical Bayesian methods as they apply to spatial and spatiotemporal statistics. It acknowledges the breadth of such applications by keeping the mathematics to a level apprehendable by epidemiologists, foresters, computer scientists, and others who are not adept in mathematical statistics, and by focusing on practical use.
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Hierarchical Modeling and Analysis for Spatial Data is the first accessible, up-to-date treatment of Bayesian methods, modeling, and data analysis for spatial and spatio-temporal data. Self-contained, it includes overviews of the necessary background material, exercises, and brief tutorial on using WinBUGS, R, and S-Plus software for Bayesian modeling. This book provides clear explanations, plentiful illustrations--some in full color--and lays the groundwork for using easily accessible software to immediately apply the techniques to your data. Written by a team of real leaders in the field, it will undoubtedly remain the primary textbook and reference on the subject for years to come.