Spatial and Spatio-Temporal Geostatistical Modeling and Kriging: 998 (Wiley Series in Probability and Statistics) - Hardcover

Montero, José-María; Fernández-Avilés, Gema; Mateu, Jorge

Hardcover

ISBN 10: 1118413180 ISBN 13: 9781118413180

Publisher: Wiley, 2015

Synopsis

Statistical Methods for Spatial and Spatio-Temporal Data Analysis provides a complete range of spatio-temporal covariance functions and discusses ways of constructing them. This book is a unified approach to modeling spatial and spatio-temporal data together with significant developments in statistical methodology with applications in R.

This book includes:

• Methods for selecting valid covariance functions from the empirical counterparts that overcome the existing limitations of the traditional methods.
• The most innovative developments in the different steps of the kriging process.
• An up-to-date account of strategies for dealing with data evolving in space and time.
• An accompanying website featuring R code and examples

About this title

About the Author

José-María Montero and Gema Fernández-Avilés, Department of Statistics, University of Castilla-La Mancha, Spain

Jorge Mateu,  Department of Mathematics, University Jaume I of Castellon, Spain

From the Back Cover

A unified approach to modeling spatial and spatio-temporal data together with significant developments in statistical methodology with applications in R

This book provides a comprehensive treatment of spatial and spatio-temporal geostatistics in a unified and integrated way. Motivated by the high demand for statistical analysis of data that take spatial and spatio-temporal information into account, this book incorporates ideas from the areas of time series, spatial statistics and stochastic processes, and combines them to provide the necessary material needed to deal with spatial and spatio-temporal problems.

Spatial and Spatio-Temporal Geostatistical Modeling and Kriging:

• Provides a complete range of spatio-temporal covariance functions, as well as discussing the ways of constructing them.
• Explores methods for selecting valid covariance functions from the empirical counterpart that overcomes the existing limitations of more traditional methods.

• Includes the most innovative developments for the different steps of the kriging process.
• Presents strategies for dealing with data evolving in space and time.
• Is supported by a website featuring R code and examples.

Statisticians, researchers, and data analysts working with spatial and space-time data will benefit from this book as well as graduate students with a background in basic statistics following courses in engineering, quantitative ecology or environmental sciences. This text will also prove to be a valuable reference for researchers and practitioners in the fields of applied mathematics, engineering, and the environmental and health sciences.

From the Inside Flap

A unified approach to modeling spatial and spatio-temporal data together with significant developments in statistical methodology with applications in R

 

This book provides a comprehensive treatment of spatial and spatio-temporal geostatistics in a unified and integrated way. Motivated by the high demand for statistical analysis of data that take spatial and spatio-temporal information into account, this book incorporates ideas from the areas of time series, spatial statistics and stochastic processes, and combines them to provide the necessary material needed to deal with spatial and spatio-temporal problems.

Spatial and Spatio-Temporal Geostatistical Modeling and Kriging:

• Provides a complete range of spatio-temporal covariance functions, as well as discussing the ways of constructing them.
• Explores methods for selecting valid covariance functions from the empirical counterpart that overcomes the existing limitations of more traditional methods.

• Includes the most innovative developments for the different steps of the kriging process.   
• Presents strategies for dealing with data evolving in space and time.
• Is supported by a website featuring R code and examples.

  

Statisticians, researchers, and data analysts working with spatial and space-time data will benefit from this book as well as graduate students with a background in basic statistics following courses in engineering, quantitative ecology or environmental sciences. This text will also prove to be a valuable reference for researchers and practitioners in the fields of applied mathematics, engineering, and the environmental and health sciences.

Edition details

• Publisher: Wiley
• Publication date: 2015
• Language: English
• ISBN 10: 1118413180
• ISBN 13: 9781118413180
• Binding: Hardcover
• Edition number: 1
• Number of pages: 400