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|a 9780123748546
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|a (OCoLC)ocn528581487
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|a (OCoLC)528581487
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|a 142169:142315
|b Elsevier Science & Technology
|n http://www.sciencedirect.com
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|b .L56 2010
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|a 333.701519542
|2 22
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| 100 |
1 |
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|a Link, William August,
|d 1957-
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| 245 |
1 |
0 |
|a Bayesian inference :
|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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| 264 |
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1 |
|a Amsterdam ;
|a Boston ;
|a London :
|b Elsevier/Academic,
|c 2010.
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| 300 |
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|a xiii, 339 pages :
|b illustrations (some color) ;
|c 25 cm.
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| 336 |
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|a text
|b txt
|2 rdacontent
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| 337 |
|
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|a computer
|b c
|2 rdamedia
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| 338 |
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|a online resource
|b cr
|2 rdacarrier
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| 533 |
|
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|a Electronic reproduction.
|b Amsterdam :
|c Elsevier Science & Technology,
|d 2010.
|n Mode of access: World Wide Web.
|n System requirements: Web browser.
|n Title from title screen (viewed on Feb. 24, 2010).
|n Access may be restricted to users at subscribing institutions.
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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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| 505 |
0 |
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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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| 504 |
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|a Includes bibliographical references and indexes.
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| 500 |
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|a Electronic resource.
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| 650 |
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0 |
|a Bayesian statistical decision theory.
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| 650 |
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0 |
|a Ecology
|x Mathematical models.
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| 650 |
1 |
7 |
|a Methode van Bayes.
|2 gtt
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| 650 |
1 |
7 |
|a Ecologische aspecten.
|2 gtt
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| 655 |
|
7 |
|a Electronic books.
|2 local
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| 700 |
1 |
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|a Barker, Richard J.
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| 776 |
1 |
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|c Original
|z 9780123748546
|z 0123748542
|w (OCoLC)432405804
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| 710 |
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|z Connect to the full text of this electronic book
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|a Texas A&M University
|b College Station
|c Electronic Resources
|d Available Online
|t 0
|e QA279.5 .L56 2010
|h Library of Congress classification
|
| 998 |
f |
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|a QA279.5 .L56 2010
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|l Available Online
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