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Statistical Methods for Spatial and Spatio-Temporal Data Analysis provides a unified approach to modeling spatial and spatio-temporal data whilst combining formal statements of the results including mathematical proofs with informal and naïve statements of classical and new results. This book is divided into several parts, part I focuses on the classical approach and techniques to deal with data showing spatial dependencies, part II presents an up-to-date account of strategies for dealing with data evolving in space and time whilst part III enters a new area in Geostatistics when data come in form of functions.
Furthermore this book provides a detailed exposition of spatial kriging methodology illustrating the different situations that the researcher could face. An in-depth look into spatial dependencies is also featured, which explores valid candidate covariance functions and variograms for representing the existing spatial dependencies in the data, how to construct the empirical counterparts and the methods for selecting a valid covariance function or variogram from the empirical counterpart. Finally, the book presents a series of methods indicating the goodness of the predictions which are provided
