Statistical Analysis of Environmental Space-Time Processes

Author:   Nhu D Le ,  James V Zidek
Publisher:   Springer
Volume:   10
ISBN:  

9780387507866


Pages:   360
Publication Date:   03 September 2008
Format:   Undefined
Availability:   Out of stock   Availability explained


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Statistical Analysis of Environmental Space-Time Processes


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Overview

This book provides a broad introduction to the subject of environmental space-time processes, addressing the role of uncertainty. 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. In particular, with members of their research group the authors 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.

Full Product Details

Author:   Nhu D Le ,  James V Zidek
Publisher:   Springer
Imprint:   Springer
Volume:   10
Dimensions:   Width: 23.40cm , Height: 1.90cm , Length: 15.60cm
Weight:   0.503kg
ISBN:  

9780387507866


ISBN 10:   0387507868
Pages:   360
Publication Date:   03 September 2008
Audience:   General/trade ,  General
Format:   Undefined
Publisher's Status:   Unknown
Availability:   Out of stock   Availability explained

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<p>From the reviews: <p> The authors are experts in environmental space-time processes and cover in this book a wealth of methodology for dealing with data from this field. ...It is certainly a very useful book for researchers and consultants in this challenging field. N.D.C. Veraverbeke for Short Book Reviews of the ISI, December 2006<p> This book contains a very interesting summarization of the current state of space-time process modeling, a topic on which the authors are eminently qualified to write upon, having worked extensively on this subject for over 30 years. ...I found this book very stimulating and would recommend it to any statistician wishing to analyze, or gain an understanding of, environmental space-time data. Jon Wakefield for Biometrics 63, 624-625, June 2007<p> The book has several distinct features, namely the writing style, topics covered, case studies used and guidance for numerical implementation. The book is well written and well structured. It is also self-co


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