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Estimation of Mortality Rates in Stage-Structured Population

53,49 €*

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Produktnummer: 18e6d4c332a58b4e5f947ce006eaafca4c
Autor: Nisbet, Roger M. Wood, Simon N.
Themengebiete: Age structured Altersstruktur Histospline Mortality Estimation Zooplankton mortality
Veröffentlichungsdatum: 07.08.1991
EAN: 9783540539797
Sprache: Englisch
Seitenzahl: 101
Produktart: Kartoniert / Broschiert
Verlag: Springer Berlin
Produktinformationen "Estimation of Mortality Rates in Stage-Structured Population"
The stated aims of the Lecture Notes in Biomathematics allow for work that is "unfinished or tentative". This volume is offered in that spirit. The problem addressed is one of the classics of statistical ecology, the estimation of mortality rates from stage-frequency data, but in tackling it we found ourselves making use of ideas and techniques very different from those we expected to use, and in which we had no previous experience. Specifically we drifted towards consideration of some rather specific curve and surface fitting and smoothing techniques. We think we have made some progress (otherwise why publish?), but are acutely aware of the conceptual and statistical clumsiness of parts of the work. Readers with sufficient expertise to be offended should regard the monograph as a challenge to do better. The central theme in this book is a somewhat complex algorithm for mortality estimation (detailed at the end of Chapter 4). Because of its complexity, the job of implementing the method is intimidating. Any reader interested in using the methods may obtain copies of our code as follows: Intelligible Structured Code 1. Hutchinson and deHoog's algorithm for fitting smoothing splines by cross validation 2. Cubic covariant area-approximating splines 3. Cubic interpolating splines 4. Cubic area matching splines 5. Hyman's algorithm for monotonic interpolation based on cubic splines. Prototype User-Hostile Code 6. Positive constrained interpolation 7. Positive constrained area matching 8. The "full method" from chapter 4 9. The "simpler" method from chapter 4.

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