Bayesian Analysis for Population Ecology

Scientists can predict future population development by gathering information on demographic parameters and external influences. Modern Bayesian methods have become important in this area of statistical inference and forecasting due to their ability to incorporate random effects, fit state-space models, evaluate posterior model probabilities, and deal with missing data. Bayesian Analysis for Population Ecology presents up-to-date methods for analyzing complex ecological data, emphasizing model choice and model averaging. The authors apply the theory to real-world case studies and illustrate the methods using WinBUGS and R. The book is available on the book's website with computer programs and full data sets.

Format: Paperback / softback
Length: 456 pages
Publication date: 21 January 2023
Publisher: Taylor & Francis Ltd

Scientists can frequently anticipate how populations will evolve in the future by collecting data on important demographic characteristics, and they can connect these parameters to external factors like global warming. Modern Bayesian techniques have gained significance in this field of statistical inference and forecasting because of their capacity to effortlessly incorporate random effects, fit state-space models, assess posterior model probabilities, and handle missing data.

Bayesian Analysis for Population Ecology provides up-to-date approaches for analysing complex ecological data, emphasising model choice and model averaging. The authors, prominent figures in the statistical ecology field, apply the theory to a diverse range of real-world case studies and demonstrate the methods using WinBUGS and R. The book's website offers access to the computer programs and complete data sets.

The first part of the book delves into models and their associated likelihood functions, examining classical methods of inference for estimating model parameters, including maximum-likelihood estimates using numerical optimisation algorithms. Building upon this foundation, the authors introduce the Bayesian approach for fitting models to data, comparing it to traditional model fitting and inference methods.

In the subsequent chapters, the book explores challenging problems in population ecology, demonstrating how to employ the latest Bayesian methods to analyse data. It empowers readers to apply these methods confidently to their own research or practical applications.

By leveraging the power of modern Bayesian techniques, scientists can gain valuable insights into population dynamics, predict future trends, and make informed decisions for conservation and management. This book serves as a valuable resource for researchers, practitioners, and students interested in advancing their understanding of population ecology and statistical inference.

Weight: 840g
Dimension: 234 x 156 (mm)
ISBN-13: 9781032477718