Hierarchical Modelling for the Environmental Sciences
Statistical Methods and Applications
Edited by James S. Clark and Alan Gelfand
Table of Contents
Preface
Part I. Introduction to hierarchical modeling
1. Elements of hierarchical Bayesian influence, Bradley P. Carlin, James S. Clark and Alan E. Gelfand
2. Bayesian hierarchical models in geographical genetics, Kent Holsinger
Part II. Hierarchical models in experimental settings
3. Synthesizing ecological experiments and observational data with hierarchical Bayes, James S. Clark and Shannon LaDeau
4. Effects of global change on inflorescence production: a Bayesian hierarchical analysis, Janneke Hille Ris Lambers, Brian Aukean, Jeff Diez, Margaret Evans and Andrew Latimer
Part III. Spatial modeling
5. Building statistical models to analyse species distributions, Alan E. Gelfand, Andrew Latimer, Shanshan Wu and John A. Silander, Jr.
6. Implications of vulnerability to hurricane damage for long-term survival of tropical tree species: a Bayesian hierarchical analysis, Kiona Ogle, Maria Uriarte, Jill Thompson, Jill Johnstone, Andy Jones, Yiching Lin, Eliot J. B. McIntire and Jess K. Zimmmerman
Part IV. Spatio-temporal modeling
7. Spatial temporal statistical modeling and prediction of environmental processes, Li Chen, Montserrat Fuentes and Jerry M. Davis
8. Hierarchical Bayesian spatio-temporal models for population spread, Christopher K. Wikle and Melvin B. Hooten
9. Spatial models for the distribution of extremes, Eric Gilleland, Douglas Nychka and Uli Schneider
References
Index