Amazon cover image
Image from Amazon.com

Bayesian inference : with ecological applications / William A. Link, Richard J. Barker.

By: Contributor(s): 2010Edition: 1st edDescription: 1 online resource (xiii, 339 pages) : illustrations (some color)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9780123748546
  • 0123748542
  • 9780080889801
  • 0080889808
Subject(s): Genre/Form: Additional physical formats: Print version:: Bayesian inference.LOC classification:
  • QA279.5 .L56 2010
Online resources:
Contents:
Chapter 1. Bayesian Inference -- Chapter 2. Probability -- Chapter 3. Statistical Inference -- Chapter 4. Posterior Calculations -- Chapter 5. Bayesian Prediction -- Chapter 6. Priors -- Chapter 7. Multimodel Inference -- Chapter 8. Hidden Data Models -- Chapter 9. Closed-Population Mark-Recapture Models -- Chapter 10. Latent Multinomials -- Chapter 11. Open Population Models -- Chapter 12. Individual Fitness -- Chapter 13. Autoregressive Smoothing.
Summary: 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. . 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.
Item type: eBooks
Star ratings
    Average rating: 0.0 (0 votes)
No physical items for this record

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. . 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.

Chapter 1. Bayesian Inference -- Chapter 2. Probability -- Chapter 3. Statistical Inference -- Chapter 4. Posterior Calculations -- Chapter 5. Bayesian Prediction -- Chapter 6. Priors -- Chapter 7. Multimodel Inference -- Chapter 8. Hidden Data Models -- Chapter 9. Closed-Population Mark-Recapture Models -- Chapter 10. Latent Multinomials -- Chapter 11. Open Population Models -- Chapter 12. Individual Fitness -- Chapter 13. Autoregressive Smoothing.

Includes bibliographical references and indexes.

Print version record.

Elsevier ScienceDirect All Books

Copyright © 2020 Alfaisal University Library. All Rights Reserved.
Tel: +966 11 2158948 Fax: +966 11 2157910 Email:
librarian@alfaisal.edu