Spatial Statistics and Spatio-Temporal Data

Beschreibung

In the spatial or spatio-temporal context, specifying the correctcovariance function is fundamental to obtain efficient predictions,and to understand the underlying physical process of interest. Thisbook focuses on covariance and variogram functions, their role inprediction, and appropriate choice of these functions inapplications. Both recent and more established methods areillustrated to assess many common assumptions on these functions,such as, isotropy, separability, symmetry, and intrinsiccorrelation. After an extensive introduction to spatial methodology, the bookdetails the effects of common covariance assumptions and addressesmethods to assess the appropriateness of such assumptions forvarious data structures. Key features: * An extensive introduction to spatial methodology including asurvey of spatial covariance functions and their use in spatialprediction (kriging) is given. * Explores methodology for assessing the appropriateness ofassumptions on covariance functions in the spatial,spatio-temporal, multivariate spatial, and point patternsettings. * Provides illustrations of all methods based on data andsimulation experiments to demonstrate all methodology and guide toproper usage of all methods. * Presents a brief survey of spatial and spatio-temporal models,highlighting the Gaussian case and the binary data setting, alongwith the different methodologies for estimation and model fittingfor these two data structures. * Discusses models that allow for anisotropic and nonseparablebehaviour in covariance functions in the spatial, spatio-temporaland multivariate settings. * Gives an introduction to point pattern models, includingtesting for randomness, and fitting regular and clustered pointpatterns. The importance and assessment of isotropy of pointpatterns is detailed. Statisticians, researchers, and data analysts working withspatial and space-time data will benefit from this book as well aswill graduate students with a background in basic statisticsfollowing courses in engineering, quantitative ecology oratmospheric science.

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Michael Sherman

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Angewandte Wahrscheinlichkeitsrechnung u. Statistik Applied Probability & Statistics Biometrics Biometrie Computational & Graphical Statistics Räumliche Statistik Rechnergestützte u. graphische Statistik Statistics Statistik

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