Bayesian Analysis for Population Ecology

Morgan Byron King Ruth Gimenez Olivier

ISBN 10: 1439811873 / ISBN 13: 9781439811870

Published by Taylor & Francis Group, 2009

About this Item

pp. 458.

Seller Inventory # 18585559

Bibliographic Details

• Title: Bayesian Analysis for Population Ecology
• Publisher: Taylor & Francis Group
• Publication Date: 2009
• Language: English
• ISBN 10: 1439811873
• ISBN 13: 9781439811870
• Binding: Hardcover
• Condition: New

About this title

Synopsis

Novel Statistical Tools for Conserving and Managing Populations

By gathering information on key demographic parameters, scientists can often predict how populations will develop in the future and relate these parameters to external influences, such as global warming. Because of their ability to easily incorporate random effects, fit state-space models, evaluate posterior model probabilities, and deal with missing data, modern Bayesian methods have become important in this area of statistical inference and forecasting.

Emphasising model choice and model averaging, Bayesian Analysis for Population Ecology presents up-to-date methods for analysing complex ecological data. Leaders in the statistical ecology field, the authors apply the theory to a wide range of actual case studies and illustrate the methods using WinBUGS and R. The computer programs and full details of the data sets are available on the book’s website.

The first part of the book focuses on models and their corresponding likelihood functions. The authors examine classical methods of inference for estimating model parameters, including maximum-likelihood estimates of parameters using numerical optimisation algorithms. After building this foundation, the authors develop the Bayesian approach for fitting models to data. They also compare Bayesian and traditional approaches to model fitting and inference.

Exploring challenging problems in population ecology, this book shows how to use the latest Bayesian methods to analyse data. It enables readers to apply the methods to their own problems with confidence.

About the Author

Ruth King is a reader in statistics at the University of St. Andrews and a former EPSRC post-doctoral Research Fellow.

Byron J.T. Morgan is a professor of applied statistics at the University of Kent and co-director of the EPSRC National Centre for Statistical Ecology.

Olivier Gimenez is a research scientist in biostatistics at CNRS and a former Marie Curie research fellow.

Stephen P. Brooks is director of research at ATASS Ltd and a former professor of statistics at the University of Cambridge and EPSRC Advanced Fellow.