"This book should be bought. It is a landmark in statistical literature, a comprehensive discourse on a topic previously mostly in the domain of nonstatisticians." (Technometrics, Vol. 36 No. 4, Nov. 1994)
Spatial statistics-analyzing spatial data through statistical models-has proven exceptionally versatile, encompassing problems ranging from the microscopic to the astronomic. However, for the scientist and engineer faced only with scattered and uneven treatments of the subject in the scientific literature, learning how to make practical use of spatial statistics in day-to-day analytical work has approached the impossible. Designed exclusively for the scientist eager to tap into the enormous potential of this analytical tool and upgrade his range of technical skills, Statistics for Spatial Data is a comprehensive, single-source guide to both the theory and applied aspects of current spatial statistical methods. The previous edition was hailed by Mathematical Reviews as an "excellent book which.will become a basic reference." This revised edition, an update of the 1991 edition, has been designed to meet the many technological challenges facing the scientist and engineer today. Concentrating on the three areas of geostatistical data, lattice data, and point patterns, the book sheds light on the link between data and model, revealing how design, inference, and diagnostics are an outgrowth of that link. It then explores new methods to reveal just how spatial statistical models can be used to solve important problems in a host of areas in science and engineering. Discussion includes:
* Exploratory spatial data analysis
* Spectral theory for stationary processes
* Spatial scale
* Simulation methods for spatial processes
* Spatial bootstrapping
* Statistical image analysis and remote sensing
* Computational aspects of model fitting
* Application of models to disease mapping
Including material heretofore unavailable in book form, the book is unique in its emphasis on Markov random fields in its presentation of models for spatial lattice data. Designed to accommodate the practical needs of the professional, it also features the first unified and common notation for its subject as well as many detailed examples woven into the text, numerous illustrations (including graphs which illuminate the theory discussed) and over 1,000 references. Fully balancing theory with applications, Statistics for Spatial Data is an exceptionally clear guide on making optimal use of one of the ascendant analytical tools of the decade, one that has begun to capture the imagination of professionals in biology, earth science, civil, electrical, and agricultural engineering, geography, epidemiology, and ecology.
From the Back Cover
The first practical look at spatial statistics for the scientist and engineer. Designed for the scientific and engineering professional eager to exploit its enormous potential, Statistics for Spatial Data is a primer to the theory as well as the nuts-and-bolts of this influential technique. Focusing on the three areas of geostatistical data, lattice data, and point patterns, the book sheds light on the link between data and model, and reveals how spatial statistical models can be used to solve a host of problems in science and engineering. Revised to reflect state-of-the-art developments, this edition also features many detailed examples, numerous illustrations, and over 1,000 references. The first fully comprehensive introduction, Statistics for Spatial Data is an essential guide for professionals in biology, earth science, civil, electrical, and agricultural engineering, geography, epidemiology, and ecology. "This excellent book, which presents the most important branches of modern spatial statistics in an exemplary manner, will become a basic reference book and will popularize many methods which have been used until now only by small circles of specialists." -Mathematical Reviews "The majority of geoscientists should make sure they have access to this volume, while for those who are actively involved in applying statistical methods to data (of all sorts) this book should be in their personal libraries. As a compendium of statistical procedures to use to analyze data, this volume will surely provide a good solid framework for some time to come." -Geophysics
About the Author
NOEL A.C. CRESSIE is Professor of Statistics at Iowa State University. He has previously served as Lecturer and Senior Lecturer of Mathematics at the Flinders University of South Australia. A fellow of the American Statistical Association and the Institute of Mathematical Statistics, Dr. Cressie is coauthor of Goodness-of-Fit Statistics for Discrete Multivariate Data. He received his PhD in statistics from Princeton University.
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