Skip to main content

Bayesian Inference

With Ecological Applications

  • 1st Edition - August 4, 2009
  • Latest edition
  • Authors: William A Link, Richard J Barker
  • Language: English

This text is written to provide a mathematically sound but accessible and engaging introduction to Bayesian inference specifically for environmental scientists, ecologists and wi… Read more

Early spring sale

Nurture your knowledge

Grow your expertise with up to 25% off trusted resources.

Description

This text is written to provide a mathematically sound but accessible and engaging introduction to Bayesian inference specifically for environmental scientists, ecologists and wildlife biologists. It emphasizes the power and usefulness of Bayesian methods in an ecological context.

The advent of fast personal computers and easily available software has simplified the use of Bayesian and hierarchical models . One obstacle remains for ecologists and wildlife biologists, namely the near absence of Bayesian texts written specifically for them. The book includes many relevant examples, is supported by software and examples on a companion website and will become an essential grounding in this approach for students and research ecologists.

Key features

  • Engagingly written text specifically designed to demystify a complex subject
  • Examples drawn from ecology and wildlife research
  • An essential grounding for graduate and research ecologists in the increasingly prevalent Bayesian approach to inference
  • Companion website with analytical software and examples
  • Leading authors with world-class reputations in ecology and biostatistics

Readership

Students and researchers in animal ecology, population ecology, wildlife management, conservation biology, and ecological and biological statistics

Table of contents

Chapter 1. Bayesian InferenceChapter 2. ProbabilityChapter 3. Statistical InferenceChapter 4. Posterior CalculationsChapter 5. Bayesian PredictionChapter 6. PriorsChapter 7. Multimodel InferenceChapter 8. Hidden Data ModelsChapter 9. Closed-Population Mark-Recapture ModelsChapter 10. Latent MultinomialsChapter 11. Open Population ModelsChapter 12. Individual FitnessChapter 13. Autoregressive Smoothing

Product details

  • Edition: 1
  • Latest edition
  • Published: August 7, 2009
  • Language: English

View book on ScienceDirect

Read Bayesian Inference on ScienceDirect