Bayesian methods for ecology /:
The interest in using Bayesian methods in ecology is increasing, however many ecologists have difficulty with conducting the required analyses. McCarthy bridges that gap, using a clear and accessible style. The text also incorporates case studies to demonstrate mark-recapture analysis, development o...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge, UK ; New York :
Cambridge University Press,
2007.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | The interest in using Bayesian methods in ecology is increasing, however many ecologists have difficulty with conducting the required analyses. McCarthy bridges that gap, using a clear and accessible style. The text also incorporates case studies to demonstrate mark-recapture analysis, development of population models and the use of subjective judgement. The advantages of Bayesian methods, are also described here, for example, the incorporation of any relevant prior information and the ability to assess the evidence in favour of competing hypotheses. Free software is available as well as an accompanying web-site containing the data files and WinBUGS codes. Bayesian Methods for Ecology will appeal to academic researchers, upper undergraduate and graduate students of Ecology. |
| Beschreibung: | 1 online resource (xiii, 296 pages) : illustrations |
| Bibliographie: | Includes bibliographical references (pages 282-292) and index. |
| ISBN: | 9780511286445 0511286449 0511285701 9780511285707 9780511802454 0511802455 |
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| 505 | 0 | |a Introduction -- Critiques of statistical methods -- Analysing averages and frequencies -- How good are the models? -- Regression and correlation -- Analysis of variance -- Case studies -- Mark-recapture analysis -- Effects of marking frogs -- Population dynamics -- Subjective priors -- Conclusion -- Appendices: A.A tutorial for running WinBUGS ; B. Probability distributions ; C. MCMC algorithms. | |
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| contents | Introduction -- Critiques of statistical methods -- Analysing averages and frequencies -- How good are the models? -- Regression and correlation -- Analysis of variance -- Case studies -- Mark-recapture analysis -- Effects of marking frogs -- Population dynamics -- Subjective priors -- Conclusion -- Appendices: A.A tutorial for running WinBUGS ; B. Probability distributions ; C. MCMC algorithms. |
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| indexdate | 2024-11-27T13:18:11Z |
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| publisher | Cambridge University Press, |
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| spelling | McCarthy, Michael A., 1968- https://id.oclc.org/worldcat/entity/E39PBJckVFJVrJ7BtPcqcwVQv3 http://id.loc.gov/authorities/names/n2006096583 Bayesian methods for ecology / Michael A. McCarthy. Cambridge, UK ; New York : Cambridge University Press, 2007. 1 online resource (xiii, 296 pages) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier Introduction -- Critiques of statistical methods -- Analysing averages and frequencies -- How good are the models? -- Regression and correlation -- Analysis of variance -- Case studies -- Mark-recapture analysis -- Effects of marking frogs -- Population dynamics -- Subjective priors -- Conclusion -- Appendices: A.A tutorial for running WinBUGS ; B. Probability distributions ; C. MCMC algorithms. Includes bibliographical references (pages 282-292) and index. Print version record. The interest in using Bayesian methods in ecology is increasing, however many ecologists have difficulty with conducting the required analyses. McCarthy bridges that gap, using a clear and accessible style. The text also incorporates case studies to demonstrate mark-recapture analysis, development of population models and the use of subjective judgement. The advantages of Bayesian methods, are also described here, for example, the incorporation of any relevant prior information and the ability to assess the evidence in favour of competing hypotheses. Free software is available as well as an accompanying web-site containing the data files and WinBUGS codes. Bayesian Methods for Ecology will appeal to academic researchers, upper undergraduate and graduate students of Ecology. Ecology Research Statistical methods. Bayesian statistical decision theory. http://id.loc.gov/authorities/subjects/sh85012506 Écologie Recherche Méthodes statistiques. Théorie de la décision bayésienne. NATURE Ecology. bisacsh NATURE Ecosystems & Habitats Wilderness. bisacsh SCIENCE Environmental Science. bisacsh SCIENCE Life Sciences Ecology. bisacsh Bayesian statistical decision theory fast Bayes-Entscheidungstheorie gnd http://d-nb.info/gnd/4144220-9 Ökologie gnd Bayes-Verfahren gnd http://d-nb.info/gnd/4204326-8 has work: Bayesian methods for ecology (Text) https://id.oclc.org/worldcat/entity/E39PCGMPCGd9WMb3hFcvtgc4C3 https://id.oclc.org/worldcat/ontology/hasWork Print version: McCarthy, Michael A., 1968- Bayesian methods for ecology. Cambridge, UK ; New York : Cambridge University Press, 2007 9780521850575 (DLC) 2006102405 (OCoLC)76798224 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=206695 Volltext |
| spellingShingle | McCarthy, Michael A., 1968- Bayesian methods for ecology / Introduction -- Critiques of statistical methods -- Analysing averages and frequencies -- How good are the models? -- Regression and correlation -- Analysis of variance -- Case studies -- Mark-recapture analysis -- Effects of marking frogs -- Population dynamics -- Subjective priors -- Conclusion -- Appendices: A.A tutorial for running WinBUGS ; B. Probability distributions ; C. MCMC algorithms. Ecology Research Statistical methods. Bayesian statistical decision theory. http://id.loc.gov/authorities/subjects/sh85012506 Écologie Recherche Méthodes statistiques. Théorie de la décision bayésienne. NATURE Ecology. bisacsh NATURE Ecosystems & Habitats Wilderness. bisacsh SCIENCE Environmental Science. bisacsh SCIENCE Life Sciences Ecology. bisacsh Bayesian statistical decision theory fast Bayes-Entscheidungstheorie gnd http://d-nb.info/gnd/4144220-9 Ökologie gnd Bayes-Verfahren gnd http://d-nb.info/gnd/4204326-8 |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85012506 http://d-nb.info/gnd/4144220-9 http://d-nb.info/gnd/4204326-8 |
| title | Bayesian methods for ecology / |
| title_auth | Bayesian methods for ecology / |
| title_exact_search | Bayesian methods for ecology / |
| title_full | Bayesian methods for ecology / Michael A. McCarthy. |
| title_fullStr | Bayesian methods for ecology / Michael A. McCarthy. |
| title_full_unstemmed | Bayesian methods for ecology / Michael A. McCarthy. |
| title_short | Bayesian methods for ecology / |
| title_sort | bayesian methods for ecology |
| topic | Ecology Research Statistical methods. Bayesian statistical decision theory. http://id.loc.gov/authorities/subjects/sh85012506 Écologie Recherche Méthodes statistiques. Théorie de la décision bayésienne. NATURE Ecology. bisacsh NATURE Ecosystems & Habitats Wilderness. bisacsh SCIENCE Environmental Science. bisacsh SCIENCE Life Sciences Ecology. bisacsh Bayesian statistical decision theory fast Bayes-Entscheidungstheorie gnd http://d-nb.info/gnd/4144220-9 Ökologie gnd Bayes-Verfahren gnd http://d-nb.info/gnd/4204326-8 |
| topic_facet | Ecology Research Statistical methods. Bayesian statistical decision theory. Écologie Recherche Méthodes statistiques. Théorie de la décision bayésienne. NATURE Ecology. NATURE Ecosystems & Habitats Wilderness. SCIENCE Environmental Science. SCIENCE Life Sciences Ecology. Bayesian statistical decision theory Bayes-Entscheidungstheorie Ökologie Bayes-Verfahren |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=206695 |
| work_keys_str_mv | AT mccarthymichaela bayesianmethodsforecology |