Includes bibliographical references and index.

From classical statistics to geostatistics -- Geostatistics: preliminaries -- Structural analysis -- Spatial prediction and kriging -- Geostatistics and spatio-temporal random functions -- Spatio-temporal structural analysis (I): empirical semivariogram and covariogram estimation and model fitting -- Spatio-temporal structural analysis (II): theoretical covariance models -- Spatio-temporal prediction and kriging -- An introduction to functional geostatistics -- Appendices A: Spectral representations -- Appendices B: Probabilistic aspects of -- Basic theory on restricted maximum likelihood -- Most relevant proofs (Chapter 7) -- Bibliography and further reading -- Index -- Supplemental Images -- Wiley Series in Probability and Statistics.

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.

Print version record and CIP data provided by publisher.