Statistics for Spatial Data (Wiley Series in Probability and Statistics) [Hardcover]

Noel Cressie (Author)

Book Description

ISBN-10: 0471002550 | ISBN-13: 978-0471002550 | Publication Date: January 15, 1993 | Edition: Revised Edition

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.

Editorial Reviews

Review

"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)

From the Inside Flap

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.

See all Editorial Reviews

Product Details

• Hardcover: 928 pages
• Publisher: Wiley-Interscience; Revised Edition edition (January 15, 1993)
• Language: English
• ISBN-10: 0471002550
• ISBN-13: 978-0471002550
• Product Dimensions: 9.5 x 6.8 x 1.9 inches
• Shipping Weight: 3 pounds (View shipping rates and policies)
• Average Customer Review: 4.6 out of 5 stars  See all reviews (5 customer reviews)
• Amazon Best Sellers Rank: #500,507 in Books (See Top 100 in Books)

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Customer Reviews

Most Helpful Customer Reviews

24 of 25 people found the following review helpful:

5.0 out of 5 stars thorough account of spatial statistical methods including resampling approaches, February 12, 2008

By 

Michael R. Chernick "statman31147" (Holland PA) - See all my reviews
(REAL NAME)   

This review is from: Statistics for Spatial Data (Wiley Series in Probability and Statistics) (Hardcover)

This is a wonderful source of information on methods for analyzing spatial data. It is still reasonably current for this rapidly developing area in statistics. You won't find some of the latest research on the joint modeling of space and time. But I expect that Cressie is working on a book that will cover it. It is an encyclopedia of references. The author covers the gamut of techniques. This explains why the book is so lengthy. I think that if he plans a revision he will be more selective and only cover those methods that have proved to be the most promising. Here you can finally learn what kriging is and even see how the bootstrap can be applied to spatial data.
Michael Stein's book is also very good and specializes in kriging. This book may look pricy at $138 but given the size of the book, the content and current textbook prices, this is a good buy.

12 of 15 people found the following review helpful:

5.0 out of 5 stars The best book for Geostatistician and not only ..., May 30, 2000

By A Customer

This review is from: Statistics for Spatial Data (Wiley Series in Probability and Statistics) (Hardcover)

The book covers very wide spectrum of different simulation and prediction methods and techniques. One can really merit from this book but under good mathematical background. The large number of practical examples helps for better understanding. The most of them can be recommended to apply for the development and testing of own statistical and mathematical software.

30 of 44 people found the following review helpful:

3.0 out of 5 stars Bible or Paperweight? I hope you are a mathematical guru!, November 4, 2000

By A Customer

This review is from: Statistics for Spatial Data (Wiley Series in Probability and Statistics) (Hardcover)

This text is more of a formula-reference with examples and is written for persons with substantial statistical / mathematical background. While I am sure that the text represents substantial value for those with substantial backgrounds in statistics / mathematics/ calculus, the rest of us may be somewhat less enlightened by the text. Make sure you have read over your Statistics 101, 102, 201, 202, 301, 302, 401, 402, 501, 502, Calculus 101, 102, 201, 202, and committed these texts to memory before reading this text. If you never met a formula you didn't like...this text is for you. The author does not hold your hand through the math and if you lack the background required, the book may have better use as a paperweight.