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Bayesian inference = with ecological applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Bayesian inference/ William A. Link, Richard J. Barker.
Reminder of title:	with ecological applications /
Author:	Link, William August,
other author:	Barker, Richard J.
Published:	Amsterdam ;Elsevier/Academic, : 2010.,
Description:	1 online resource (xiii, 339 p.) :ill. (some col.)
[NT 15003449]:	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.
Subject:	Bayesian statistical decision theory. -
Online resource:	http://www.sciencedirect.com/science/book/9780123748546
ISBN:	9780123748546

Bayesian inference = with ecological applications /
Link, William August,1957-{me_controlnum}

Bayesian inferencewith ecological applications /[electronic resource] :William A. Link, Richard J. Barker. - 1st ed. - Amsterdam ;Elsevier/Academic,2010. - 1 online resource (xiii, 339 p.) :ill. (some col.)

Includes bibliographical references and indexes.

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.

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.

ISBN: 9780123748546

Source: 142169:142315Elsevier Science & Technologyhttp://www.sciencedirect.comSubjects--Topical Terms:

551404
Bayesian statistical decision theory.
Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: QA279.5 / .L56 2010

Dewey Class. No.: 333.701519542

Bayesian inference = with ecological applications /
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300 $a 1 online resource (xiii, 339 p.) : $b ill. (some col.)
504 $a Includes bibliographical references and indexes.
505 0 $a 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.
520 $a 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.
588 $a Description based on print version record.
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