Hierarchical modelling for the environmental sciences
Subtitle: statistical methods and applications
By: edited by James S. Clark and Alan E. Gelfand
Contributors: Clark, James Samuel, 1957-; Gelfand, Alan E., 1945-
Series: Oxford biology
Publisher: Oxford University Press
Published: 2006
Place of publication: Oxford; New York
Language: eng
Number of pages: 205
ISBN-13: 9780198569664; 9780198569671
Subjects: Bayesian statistical decision theory; Multilevel models (Statistics); Mathematical statistics -- Data processing; Environmental sciences -- Statistical methods
Description: 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 challenges.
Notes: Includes bibliographical references (p. 185-195) and index