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141222 ||| eng |
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|a 0080889808
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|a 9780123748546
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|a 0123748542
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|a 9780080889801
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| 100 |
1 |
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|a Link, William August
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| 245 |
0 |
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|a Bayesian inference
|h [electronic resource]
|h Elektronische Ressource
|b with ecological applications
|c William A. Link, Richard J. Barker
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| 250 |
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|a 1st ed
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| 260 |
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|a Amsterdam
|b Elsevier/Academic
|c 2010, 2010
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| 300 |
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|a online resource (xiii, 339 pages)
|b illustrations (some color)
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| 505 |
0 |
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|a Includes bibliographical references and indexes
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| 505 |
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|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
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| 653 |
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|a NATURE / Natural Resources / bisacsh
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| 653 |
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|a Methode van Bayes / gtt
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| 653 |
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|a BUSINESS & ECONOMICS / Green Business / bisacsh
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| 653 |
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|a Ecology / Mathematical models / fast / (OCoLC)fst00901509
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| 653 |
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|a Bayesian statistical decision theory
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| 653 |
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|a Ecology / Mathematical models
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| 653 |
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|a Bayesian statistical decision theory / fast / (OCoLC)fst00829019
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| 653 |
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|a Ecologische aspecten / gtt
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| 653 |
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|a BUSINESS & ECONOMICS / Environmental Economics / bisacsh
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| 700 |
1 |
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|a Barker, Richard J.
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b ESD
|a Elsevier ScienceDirect eBooks
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| 856 |
4 |
0 |
|u http://www.sciencedirect.com/science/book/9780123748546
|x Verlag
|3 Volltext
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| 082 |
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|a 333.701519542
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| 520 |
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|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
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