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Statistical Methods for Spatial Data Analysis - Texts in Statistical Science (Hardcover) Loot Price: R4,116
Discovery Miles 41 160
Statistical Methods for Spatial Data Analysis - Texts in Statistical Science (Hardcover): Oliver Schabenberger, Carol A. Gotway

Statistical Methods for Spatial Data Analysis - Texts in Statistical Science (Hardcover)

Oliver Schabenberger, Carol A. Gotway; Series edited by Jim Zidek, Jim Lindsey, Chris Chatfield

Series: Chapman & Hall/CRC Texts in Statistical Science

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Loot Price R4,116 Discovery Miles 41 160 | Repayment Terms: R386 pm x 12*

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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 websitesupplements 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.

General

Imprint: Chapman & Hall/CRC
Country of origin: United States
Series: Chapman & Hall/CRC Texts in Statistical Science
Release date: December 2004
First published: 2005
Authors: Oliver Schabenberger • Carol A. Gotway
Series editors: Jim Zidek • Jim Lindsey • Chris Chatfield
Dimensions: 254 x 178 x 33mm (L x W x T)
Format: Hardcover
Pages: 506
ISBN-13: 978-1-58488-322-7
Categories: Books > Science & Mathematics > Mathematics > Probability & statistics
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LSN: 1-58488-322-7
Barcode: 9781584883227

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