Statistical Methods for Spatial Data Analysis - Couverture souple

Gotway, Carol A.; Schabenberger, Oliver

9781032477916: Statistical Methods for Spatial Data Analysis

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ISBN 10 : 1032477911 ISBN 13 : 9781032477916

Editeur : Chapman and Hall/CRC, 2023

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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 authors deliver an outstanding treatment of semivariogram estimation and modeling, spatial analysis in the s

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� propos de l?auteur

Oliver Schabenberger, Carol A. Gotway

Les informations fournies dans la section � A propos du livre � peuvent faire r�f�rence � une autre �dition de ce titre.

�diteurChapman and Hall/CRC
Date d'�dition2023
ISBN 10 1032477911
ISBN 13 9781032477916
ReliureBroch�
Langueanglais
Nombre de pages506
Coordonn�es du fabricantnon disponible

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9781584883227: Statistical Methods For Spatial Data Analysis

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Editeur : Chapman & Hall/CRC, 2004
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Statistical Methods for Spatial Data Analysis

Oliver Schabenberger (SAS Institute Inc., Cary, North Carolina, USA)|Carol A. Gotway (National Center for Environmental Health, Atlanta, Georgia, USA)

Edit� par CRC Press, 2023

ISBN 10 : 1032477911 ISBN 13 : 9781032477916

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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Oliver Schabenberger, Carol A. GotwayUnderstanding spatial statistics requires tools from applied and mathematical statistics, linear model theory, regression, time series, and stochastic processes. It also requires a mindset that focuses . N� de r�f. du vendeur 801266739

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Statistical Methods for Spatial Data Analysis

Oliver Schabenberger

Edit� par CRC Press Jan 2023, 2023

ISBN 10 : 1032477911 ISBN 13 : 9781032477916

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Understanding spatial statistics requires tools from applied and mathematical statistics, linear model theory, regression, time series, and stochastic processes. It also requires a mindset that focuses on the unique characteristics of spatial data and the development of specialized analytical tools designed explicitly for spatial data analysis. Statistical Methods for Spatial Data Analysis answers the demand for a text that incorporates all of these factors by presenting a balanced exposition that explores both the theoretical foundations of the field of spatial statistics as well as practical methods for the analysis of spatial data. This book is a comprehensive and illustrative treatment of basic statistical theory and methods for spatial data analysis, employing a model-based and frequentist approach that emphasizes the spatial domain. It introduces essential tools and approaches including: measures of autocorrelation and their role in data analysis; the background and theoretical framework supporting random fields; the analysis of mapped spatial point patterns; estimation and modeling of the covariance function and semivariogram; a comprehensive treatment of spatial analysis in the spectral domain; and spatial prediction and kriging. The volume also delivers a thorough analysis of spatial regression, providing a detailed development of linear models with uncorrelated errors, linear models with spatially-correlated errors and generalized linear mixed models for spatial data. It succinctly discusses Bayesian hierarchical models and concludes with reviews on simulating random fields, non-stationary covariance, and spatio-temporal processes.Additional material on the CRC Press website supplements the content of this book. The site provides data sets used as examples in the text, software code that can be used to implement many of the principal methods described and illustrated, and updates to the text itself. 504 pp. Englisch. N� de r�f. du vendeur 9781032477916

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Statistical Methods for Spatial Data Analysis: Texts in Statistical Science

Oliver Schabenberger

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Statistical Methods for Spatial Data Analysis: Texts in Statistical Science

Schabenberger, Oliver; Gotway, Carol A.

Edit� par Chapman and Hall/CRC, 2023

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Statistical Methods for Spatial Data Analysis (Chapman & Hall/CRC Texts in Statistical Science)

Schabenberger, Oliver; Gotway, Carol A.

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Statistical Methods for Spatial Data Analysis : Texts in Statistical Science

Schabenberger, Oliver; Gotway, Carol A.; Zidek, Jim (EDT); Lindsey, Jim (EDT)

Edit� par Chapman and Hall/CRC, 2023

ISBN 10 : 1032477911 ISBN 13 : 9781032477916

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Statistical Methods for Spatial Data Analysis

Oliver Schabenberger

Edit� par CRC Press, 2023

ISBN 10 : 1032477911 ISBN 13 : 9781032477916

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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Understanding spatial statistics requires tools from applied and mathematical statistics, linear model theory, regression, time series, and stochastic processes. It also requires a mindset that focuses on the unique characteristics of spatial data and the development of specialized analytical tools designed explicitly for spatial data analysis. Statistical Methods for Spatial Data Analysis answers the demand for a text that incorporates all of these factors by presenting a balanced exposition that explores both the theoretical foundations of the field of spatial statistics as well as practical methods for the analysis of spatial data. This book is a comprehensive and illustrative treatment of basic statistical theory and methods for spatial data analysis, employing a model-based and frequentist approach that emphasizes the spatial domain. It introduces essential tools and approaches including: measures of autocorrelation and their role in data analysis; the background and theoretical framework supporting random fields; the analysis of mapped spatial point patterns; estimation and modeling of the covariance function and semivariogram; a comprehensive treatment of spatial analysis in the spectral domain; and spatial prediction and kriging. The volume also delivers a thorough analysis of spatial regression, providing a detailed development of linear models with uncorrelated errors, linear models with spatially-correlated errors and generalized linear mixed models for spatial data. It succinctly discusses Bayesian hierarchical models and concludes with reviews on simulating random fields, non-stationary covariance, and spatio-temporal processes.Additional material on the CRC Press website supplements the content of this book. The site provides data sets used as examples in the text, software code that can be used to implement many of the principal methods described and illustrated, and updates to the text itself. N� de r�f. du vendeur 9781032477916

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