Statistics for Spatial Data (Wiley Series in Probability and Statistics), by Noel Cressie
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Statistics for Spatial Data (Wiley Series in Probability and Statistics), by Noel Cressie
Read and Download Ebook Statistics for Spatial Data (Wiley Series in Probability and Statistics), by Noel Cressie
The Wiley Classics Library consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.
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 is very difficult.
Designed exclusively for scientists eager to tap into the enormous potential of this analytical tool and upgrade their range of technical skills, Statistics for Spatial Data is a comprehensive, single-source guide to both the theory and applied aspects of spatial statistical methods. The hard-cover edition was hailed by Mathematical Reviews as an "excellent book which will become a basic reference." This paper-back edition of the 1993 edition, is designed to meet the many technological challenges facing the scientist and engineer. 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
Designed to accommodate the practical needs of the professional, it features a unified and common notation for its subject as well as many detailed examples woven into the text, numerous illustrations (including graphs that illuminate the theory discussed) and over 1,000 references.
Fully balancing theory with applications, Statistics for Spatial Data, Revised Edition 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.
Statistics for Spatial Data (Wiley Series in Probability and Statistics), by Noel Cressie - Amazon Sales Rank: #1694240 in eBooks
- Published on: 2015-03-23
- Released on: 2015-03-23
- Format: Kindle eBook
Statistics for Spatial Data (Wiley Series in Probability and Statistics), by Noel Cressie 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.
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
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Most helpful customer reviews
27 of 28 people found the following review helpful. thorough account of spatial statistical methods including resampling approaches By Michael R. Chernick 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.
13 of 16 people found the following review helpful. The best book for Geostatistician and not only ... By A Customer 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.
3 of 4 people found the following review helpful. Excellent book to learn geostatistics By F. Yucel I am a beginner in geostatistics and this book helped me alot to learn and analyze my data for my thesis. Excellent reference book to keep.
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Statistics for Spatial Data (Wiley Series in Probability and Statistics), by Noel Cressie
Statistics for Spatial Data (Wiley Series in Probability and Statistics), by Noel Cressie
