| 000 | 07954cam a2200985Ma 4500 | ||
|---|---|---|---|
| 001 | ocn844328650 | ||
| 003 | OCoLC | ||
| 005 | 20220711201221.0 | ||
| 006 | m o d | ||
| 007 | cr cn||||||||| | ||
| 008 | 960618s1997 njua ob 001 0 eng d | ||
| 010 | _z 96009638 | ||
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| 020 | _z9780691034973 | ||
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_aQH541.15.M3 _bH54 1997eb |
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_aQH541.15.M3H54 _b1997 |
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_aSCI _x020000 _2bisacsh |
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_aWI 1500 _2rvk _0(DE-625)rvk/148757: |
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| 049 | _aMAIN | ||
| 100 | 1 |
_aHilborn, Ray, _d1947- _eauthor. _9333566 |
|
| 245 | 1 | 4 |
_aThe ecological detective : _bconfronting models with data / _cRay Hilborn and Marc Mangel. |
| 260 |
_aPrinceton, N.J. : _bPrinceton University Press, _c1997. |
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| 300 |
_a1 online resource (xvii, 315 pages) : _billustrations |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 490 | 1 |
_aMonographs in population biology ; _v28 |
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| 504 | _aIncludes bibliographical references and index. | ||
| 505 | 0 | _aCover; MONOGRAPHS IN POPULATION BIOLOGY; Title; Copyright; Dedication; Contents; Preface: Beyond the Null Hypothesis; About the Title; The Audience and Assumed Background; Computer Programming; Realism and Professionalism; Acknowledgments; 1. An Ecological Scenario and the Tools of the Ecological Detective; An Ecological Scenario; The Tools for Ecological Detection; 2. Alternative Views of the Scientific Method and of Modeling; Alternative Views of the Scientific Method; Statistical Inference in Experimental Trees; Unique Aspects of Ecological Data. | |
| 505 | 8 | _aDistinguishing between Models and HypothesesTypes and Uses of Models; Nested Models; Model Complexity; 3. Probability and Probability Models: Know Your Data; Descriptions of Randomness; Always Plot Your Data; Experiments, Events, and Probability; Process and Observation Uncertainties; Some Useful Probability Distributions; The Monte Carlo Method; 4. Incidental Catch in Fisheries: Seabirds in the New Zealand Squid Trawl Fishery; Motivation; The Ecological Setting; Statistically Meaningful Data -- The Data; A Negative Binomial Model of By-Catch. | |
| 505 | 8 | _aA Monte Carlo Approach for Estimating the Chance of Success in an Observer ProgramImplications; 5. The Confrontation: Sum of Squares; The Basic Method; Goodness-of-Fit Profiles; Model Selection Using Sum of Squares; 6. The Evolutionary Ecology of Insect Oviposition Behavior; Motivation; The Ecological Setting; The Data; The Models; The Confrontation; Implications; 7. The Confrontation: Likelihood and Maximum Likelihood; Overview; Likelihood and Maximum Likelihood; Determining the Appropriate Likelihood; Model Selection Using Likelihoods; Robustness: Don't Let Outliers Ruin Your Life. | |
| 505 | 8 | _aBounding the Estimated Parameter: Confidence IntervalsThe Bootstrap Method; Linear Regression, Analysis of Variance, and Maximum Likelihood; 8. Conservation Biology of Wildebeest in the Serengeti; Motivation; The Ecological Setting; The Data; The Models: What Happens When Rainfall Returns to Normal (the 1978 Question)?; The Models: What Is the Intensity of Poaching (the 1992 Question)?; The Confrontation: The Effects of Rainfall; The Confrontation: The Effects of Poaching; Implications; 9. The Confrontation: Bayesian Goodness of Fit; Why Bother with Bayesian Analysis?; Some Examples. | |
| 505 | 8 | _aMore Technical ExamplesModel versus Model versus Model; 10. Management of Hake Fisheries in Namibia Motivation; The Impact of Environmental Change; The Ecological Setting; The Data; The Models; The Confrontation; Bayesian Analysis of the LRSG Parameters; Implications; 11. The Confrontation: Understanding How the Best Fit Is Found; Introduction; Direct Search and Graphics; Newton's Method and Gradient Search; Nongradient Methods: Avoiding the Derivative; The Art of Fitting; Hints for Special Problems; Appendix: The Method of Multiple Working Hypotheses -- References; Index. | |
| 520 | _aThe modern ecologist usually works in both the field and laboratory, uses statistics and computers, and often works with ecological concepts that are model-based, if not model-driven. How do we make the field and laboratory coherent? How do we link models and data? How do we use statistics to help experimentation? How do we integrate modeling and statistics? How do we confront multiple hypotheses with data and assign degrees of belief to different hypotheses? How do we deal with time series (in which data are linked from one measurement to the next) or put multiple sources of data into one. | ||
| 546 | _aEnglish. | ||
| 590 |
_aeBooks on EBSCOhost _bEBSCO eBook Subscription Academic Collection - Worldwide |
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| 650 | 0 |
_aEcology _xMathematical models. _9147409 |
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| 650 | 6 |
_aÉcologie _xModèles mathématiques. _9947478 |
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| 650 | 7 |
_aSCIENCE _xLife Sciences _xEcology. _2bisacsh _9865186 |
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| 650 | 7 |
_aEcology _xMathematical models. _2fast _0(OCoLC)fst00901509 _9147409 |
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| 650 | 7 |
_aMathematisches Modell _2gnd _9898593 |
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| 650 | 7 |
_aÖkologie _2gnd _9871443 |
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| 650 | 1 | 7 |
_aModellen. _2gtt _9864372 |
| 650 | 1 | 7 |
_aEcologie. _2gtt _9864701 |
| 650 | 7 |
_aÉcologie. _2rasuqam _9886172 |
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| 650 | 7 |
_aModèle mathématique. _2rasuqam _9906962 |
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| 655 | 0 | _aElectronic book. | |
| 655 | 4 | _aElectronic books. | |
| 700 | 1 |
_aMangel, Marc, _eauthor. _9209207 |
|
| 776 | 0 | 8 |
_iPrint version: _aHilborn, Ray. _tEcological Detective : Confronting Models with Data (MPB-28). _dPrinceton : Princeton University Press, ©2013 _z9780691034973 |
| 830 | 0 |
_aMonographs in population biology ; _v28. |
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| 856 | 4 | 0 | _uhttps://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=529481 |
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