Oliver Schabenberger, Carol A Gotway

Statistical Methods for Spatial Data Analysis

• Gebundenes Buch

Produktbeschreibung

Statistical Methods for Spatial Data Analysis is a comprehensive treatment of statistical theory and methods for spatial data analysis, employing a model-based and frequentist approach that emphasizes the spatial domain. The volume delivers an up-to-date treatment of semivariogram estimation and modeling and spatial analysis in the spectral domain, as well as a thorough analysis of spatial regression, covering linear models with uncorrelated errors, linear models with spatially-correlated errors and generalized linear mixed models for spatial data and succinctly discussing Bayesian hierarchical models. It concludes with a review of simulation, non-stationary covariance and spatio-temporal processes.

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Produktdetails

• Verlag: Taylor & Francis Ltd (Sales)
• Seitenzahl: 488
• Erscheinungstermin: 20. Dezember 2004
• Englisch
• Abmessung: 263mm x 182mm x 32mm
• Gewicht: 1021g
• ISBN-13: 9781584883227
• ISBN-10: 1584883227
• Artikelnr.: 21858107

Autorenporträt

Oliver Schabenberger, Carol A. Gotway

Inhaltsangabe

Introduction. Some theory on random fields. Mapped point patterns.
Semivariogram and covariance function analysis and estimation. Spatial
prediction and kriging. Spatial regression models. Simulation of random
fields. Non-stationary covariance. Spatio-temporal processes.

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Introduction. Some theory on random fields. Mapped point patterns. Semivariogram and covariance function analysis and estimation. Spatial prediction and kriging. Spatial regression models. Simulation of random fields. Non-stationary covariance. Spatio-temporal processes.

Rezensionen

"...well-presented research-level text with interesting examples and an extensive reference list, much of which relates to work which has appeared during the last five years or so."
International Statistics Institute, 2005

"This book tackles spatial data analysis from a statistician's point of view. It provides a very natural bridge to spatial data analysis for the classically trained statistician who is familiar with linear models and the like. In terms of detail, it is at a very good level for its stated audience of a graduate class in spatial statistics; there is much useful information....The authors have made a tightly written and well-planned contribution that updates much relevant material and provides welcome and thoughtful advice. ...I have no hesitation in recommending it for a graduate class in spatial statistics, and it is a welcome addition to my library."
-Journal of the Royal Statistical Society, Series A, Andrew Robinson, University of Melbourne

"This book provides an introduction to statistical methods for the analysis of spatial data. In a coherent manner, it presents statistical tools and approaches for analysis of three types of spatial data: geostatistical data, lattice data, and point patterns. ...The book is intended as a text for a graduate-level course in spatial statistics. I believe that it would be a suitable text for a variety of reasons. First of all, the book provides comprehensive coverage of statistical methods for geostatistical data, lattice data, and point patterns. Not many books on spatial statistics have this feature. ...The book has a nice balance of statistical theory, methodology, and applications, with an emphasis on statistical methods. It contains many concrete examples that illustrate both theory and methods. In illustrating the methods, real and interesting data examples are drawn from many disciplines such as agriculture, ecology, geology, epidemiology, and meteorology. ...This is a wonderful book that systematically introduces readers to spatial statistics. With a writing style that is illustrative, clear, thoughtful, and cogent, teachers and students alike should find it a delightful text for this diverse and exciting field."
-Journal of the American Statistical Association, Jun Zhu, University of Wisconsin-Madison

"I enjoyed this book and I am sure that it is a valuable addition to the literature which should be widely read."

- Stelios Zimeras, University of the Aegean, in Journal of Applied Statistics, Jan 2008, Vol. 35, No. 1