Hierarchical Modelling for the Environmental Sciences: Statistical Methods and Applications (Oxford Biology) [Paperback]James S. Clark (Editor), Alan Gelfand (Editor)
Editorial Reviews
Review
"...if you are already quite well acquainted with Bayesian concepts and terminology then this book should provide an excellent guide to the application of these advanced statistical techniques within ecology." --Bulletin of the British Ecological Society
"This book provides rare examples of how to apply HB in the environmental sciences and will be a key component of the analytical toolbox for environmental scientists using or learning to use this approach." --The Quarterly Review of Biology
About the Author
James Clark is the Blomquist Professor at Duke University, where his research focuses on how global change affects forests and grasslands. He received a B.S. from the North Carolina State University in Entomology (1979), a M.S. from the University of Massachusetts in Forestry and Wildlife (1984), and a Ph.D. from the University of Minnesota in Ecology (1988). At Duke University, Clark teaches Community Ecology and Ecological Models & Data. He has served as the Director of Graduate Studies for the University Program in Ecology and as Director of the Center on Global Change. Alan E. Gelfand is the J B Duke Professor of Statistics and Decision Sciences at Duke University. An early contributor to the development of computational machinery for fitting hierarchical Bayesian models, his current research focuses on the analysis of spatial and spatio-temporal data. His primary areas of application are to problems in environmental science, ecology, and climatology. He received a B.S. from the City College of New York and an M.S. and Ph.D. from Stanford University. After many years at the University of Connecticut, he joined the faculty at Duke University in August 2002.
Product Details
Series: Oxford Biology
Paperback: 216 pages
Publisher: Oxford University Press, USA (June 29, 2006)
Language: English
ISBN-10: 019856967X
ISBN-13: 978-0198569671
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