This book presents knowledge gained by the authors along with methods they developed, over more than 30 years of experience measuring, mod- ing, and mapping environmental space-time ?elds. That experience embraces both large (continentwide) spatial domains and small. In part it comes from their research, working with students as well as coinvestigators. But much was gained from all sorts of interactions with many individuals who have had to contend with the challenges these ?elds present. They include statistical as well as subject area scientists, in areas as diverse as analytical chemistry, airsampling,atmosphericscience,environmentalepidemiology,environmental risk management, and occupational health among others. We have colla- rated and consulted with government scientists as well as policy-makers, in all,alargegroupofindividualsfromwhomwehavelearnedalotandtowhom we are indebted. We hope all in these diverse groups will ?nd something of value in this book. We believe it will also bene?t graduate students, both in statistics and subject areas who must deal with the analysis of environmental ?elds. In fact we have given a successful statistics graduate course based on it. The book (and course) re?ect our conviction about the need for statistical scientiststolearnaboutthephenomenatheypurporttoexplain. Totheextent feasible, we have covered important nonstatistical issues involved in dealing with environmental processes. Thus in writing the book we have tried to strike a balance between important qualitative and quantitative aspects of the subject. Much of the most technical statistical-mathematical material has been placed in the starred sections, chapters, and appendices.
Reviews / Votes
From the reviews:
"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
"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
"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-contained and nits material flows in a natural and systematic order. Each chapter starts with motivating examples, which help to orient the reader to the broader picture. ...I give the authors a very high mark for producing such an excellent book, one that will be of great service to the field of environmental statistics." Abdel El-Shaarawi, Environmentrics, January 2007
"Le and Zidek's well-written book presents a predominantly Bayesian approach to spatiotemporal statistics, with an emphasis on entropy-based sampling design methods. . They provide a superb review of spatial statistics . . The book's main selling points are its readability and coverage of methods not found elsewhere in a single volume . . Le and Zidek have provided an excellent reference on design-based models for environmental processes . ." (Mevin B. Hooten, Journal of the American Statistical Association, Vol. 102 (480), 2007)
Series
Edition
Language
Place of publication
Target group
Professional and scholarly
Research
Product notice
sewn/stitched
Cloth over boards
Illustrations
Dimensions
Height: 242 mm
Width: 162 mm
Thickness: 22 mm
Weight
ISBN-13
978-0-387-26209-3 (9780387262093)
DOI
Schweitzer Classification
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.
