Statistical Analysis of Environmental Space-Time Processes
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ISBN-13:
9780387262093
Veröffentl:
2006
Erscheinungsdatum:
09.05.2006
Seiten:
342
Autor:
Nhu D Le
Gewicht:
654 g
Format:
242x162x22 mm
Sprache:
Englisch
Beschreibung:
This book provides a broad introduction to the fascinating subject of environmental space-time processes; addressing the role of uncertainty. Within that context, it covers a spectrum of technical matters from measurement to environmental epidemiology to risk assessment. It showcases non-stationary vector-valued processes, while treating stationarity as a special case. The contents reflect the authors' cumulative knowledge gained over many years of consulting and research collaboration. In particular, with members of their research group, they developed within a hierarchical Bayesian framework, the new statistical approaches presented in the book for analyzing, modeling, and monitoring environmental spatio-temporal processes. Furthermore they indicate new directions for development.
This book provides a broad introduction to the fascinating subject of environmental space-time processes; addressing the role of uncertainty. Within that context, it covers a spectrum of technical matters from measurement to environmental epidemiology to risk assessment. The contents reflect the authors' cumulative knowledge gained over many years of consulting and research collaboration. In particular, with members of their research group, they developed within a hierarchical Bayesian framework, the new statistical approaches presented in the book for analyzing, modeling, and monitoring environmental spatio-temporal processes. Furthermore they indicate new directions for development. This book contains technical and non-technical material and it is written for statistical scientists as well as consultants, subject area researchers and students in related fields.
Environmental Processes.- First Encounters.- Case Study.- Uncertainty.- Measurement.- Modeling.- Space-Time Modeling.- Covariances.- Spatial Prediction: Classical Approaches.- Bayesian Kriging.- Hierarchical Bayesian Kriging.- Design and Risk Assessment.- Multivariate Modeling***.- Environmental Network Design.- Extremes.- Implementation.- Risk Assessment.- A Tutorial in R.- Appendices.- References.
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