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Verlag: John Wiley and Sons, 2011
ISBN 10: 0471692743ISBN 13: 9780471692744
Anbieter: Anybook.com, Lincoln, Vereinigtes Königreich
Buch
Zustand: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. Clean from markings. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1050grams, ISBN:9780471692744.
Verlag: Wiley 2011-04-19, Oxford, 2011
ISBN 10: 0471692743ISBN 13: 9780471692744
Anbieter: Blackwell's, London, Vereinigtes Königreich
Buch
hardback. Zustand: New. Language: ENG.
Verlag: John Wiley & Sons, 2011
ISBN 10: 0471692743ISBN 13: 9780471692744
Anbieter: moluna, Greven, Deutschland
Buch
Zustand: New. Noel Cressie, PhD, is Professor of Statistics and Director of the Program in Spatial Statistics and Environmental Statistics at The Ohio State University. A Fellow of the American Statistical Association and the Institute of Mathematical Statistics, he has .
Verlag: Wiley Apr 2011, 2011
ISBN 10: 0471692743ISBN 13: 9780471692744
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch
Buch. Zustand: Neu. Neuware - A state-of-the-art presentation of spatio-temporal processes, bridging classic ideas with modern hierarchical statistical modeling concepts and the latest computational methodsFrom understanding environmental processes and climate trends to developing new technologies for mapping public-health data and the spread of invasive-species, there is a high demand for statistical analyses of data that take spatial, temporal, and spatio-temporal information into account. Statistics for Spatio-Temporal Data presents a systematic approach to key quantitative techniques that incorporate the latest advances in statistical computing as well as hierarchical, particularly Bayesian, statistical modeling, with an emphasis on dynamical spatio-temporal models.Cressie and Wikle supply a unique presentation that incorporates ideas from the areas of time series and spatial statistics as well as stochastic processes. Beginning with separate treatments of temporal data and spatial data, the book combines these concepts to discuss spatio-temporal statistical methods for understanding complex processes.Topics of coverage include:\* Exploratory methods for spatio-temporal data, including visualization, spectral analysis, empirical orthogonal function analysis, and LISAs\* Spatio-temporal covariance functions, spatio-temporal kriging, and time series of spatial processes\* Development of hierarchical dynamical spatio-temporal models (DSTMs), with discussion of linear and nonlinear DSTMs and computational algorithms for their implementation\* Quantifying and exploring spatio-temporal variability in scientific applications, including case studies based on real-world environmental dataThroughout the book, interesting applications demonstrate the relevance of the presented concepts. Vivid, full-color graphics emphasize the visual nature of the topic, and a related FTP site contains supplementary material. Statistics for Spatio-Temporal Data is an excellent book for a graduate-level course on spatio-temporal statistics. It is also a valuable reference for researchers and practitioners in the fields of applied mathematics, engineering, and the environmental and health sciences.