Hierarchical Modelling for the Environmental Sciences

Name: Hierarchical Modelling for the Environmental Sciences
Availability: OutOfStock
ISBN: 9780198569664

ISBN-10: 0198569661

ISBN-13: 9780198569664

Edition: 2006

Authors: James S. Clark, Alan Gelfand

List price: $125.00

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New Statistical tools are changing the wau in which scientists analyze and interpret data and models. Many of these are emerging as a result of the wide availability of inexpensive, high speed computational power. In particular, hierarchical Bayes and Markov Chain Monte Carlo methods for analysis provide constant framework for inference and prediction where information is heterogeneous and uncertain, processes are complex, and responses depend on scale. Nowhere are these methods more promising than in the environmental sciences. Models have developed rapidly, and there is now a requirment for a clear exposition of the methodology through to application for a range of environmental…

Book details

List price: $125.00
Copyright year: 2006
Publisher: Oxford University Press, Incorporated
Publication date: 6/29/2006
Binding: Hardcover
Pages: 216
Size: 7.44" wide x 9.69" long x 0.66" tall
Weight: 1.408
Language: English



Preface



Introduction to hierarchical modeling



Elements of hierarchical Bayesian influence




Bayesian hierarchical models in geographical genetics




Hierarchical models in experimental settings



Synthesizing ecological experiments and observational data with hierarchical




Effects of global change on inflorescence production: a Bayesian hierarchical analysis




Spatial modeling



Building statistical models to analyse species distributions




Implications of vulnerability to hurricane damage for long-term survival of tropical tree species: a Bayesian hierarchical analysis




Spatio-temporal modeling



Spatial temporal statistical modeling and prediction of environmental processes




Hierarchical Bayesian spatio-temporal models for population spread




Spatial models for the distribution of extremes



References


Index