Introduction to Bayesian Methods in Ecology and Natural Resources
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Beschreibung
This book presents modern Bayesian analysis in a format that is accessible to researchers in the fields of ecology, wildlife biology, and natural resource management. Bayesian analysis has undergone a remarkable transformation since the early 1990s. Widespread adoption of Markov chain Monte Carlo techniques has made the Bayesian paradigm the viable alternative to classical statistical procedures for scientific inference. The Bayesian approach has a number of desirable qualities, three chief ones being: i) the mathematical procedure is always the same, allowing the analyst to concentrate on the scientific aspects of the problem; ii) historical information is readily used, when appropriate; and iii) hierarchical models are readily accommodated.
This monograph contains numerous worked examples and the requisite computer programs. The latter are easily modified to meet new situations. A primer on probability distributions is also included because these form the basis of Bayesian inference.
Researchers and graduate students in Ecology and Natural Resource Management will find this book a valuable reference.
This book presents modern Bayesian analysis in a format that is accessible to researchers in the fields of ecology, wildlife biology, and natural resource management. Bayesian analysis has undergone a remarkable transformation since the early 1990s. Widespread adoption of Markov chain Monte Carlo techniques has made the Bayesian paradigm the viable alternative to classical statistical procedures for scientific inference. The Bayesian approach has a number of desirable qualities, three chief ones being: i) the mathematical procedure is always the same, allowing the analyst to concentrate on the scientific aspects of the problem; ii) historical information is readily used, when appropriate; and iii) hierarchical models are readily accommodated.
This monograph contains numerous worked examples and the requisite computer programs. The latter are easily modified to meet new situations. A primer on probability distributions is also included because these form the basis of Bayesian inference.
Researchers and graduate students in Ecology and Natural Resource Management will find this book a valuable reference.
Provides insightful background and rationale in support of the Bayesian approach for natural resource and ecological applications Offers extensive worked examples of biological data analysis, using open source software, with emphasis on model choice, fit diagnostics, and interpretation Details and illustrates application of spatial data models with focus on computationally efficient software tools for tackling large and complex datasets
Autor*in
Edwin J. Green
Themen in »Introduction to Bayesian Methods in Ecology and Natural Resources«
Markov Chain Monte Carlo (MCMC) techniques Bayesian inference wildlife biology scientific inference Winbugs code Forestry Management