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Estimation and Analysis of Insect Populations pp 81–92Cite as

From Cohort Data to Life Table Parameters Via Stochastic Modeling

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Part of the book series: Lecture Notes in Statistics ((LNS,volume 55))

Abstract

We develop a new method through which parameters such as the duration of stages and the mortality rates within them can be deduced from data on abundance of the stages over time in one cohort of individuals. This method involves modeling of the development process, modeling of the sampling process with its inherent errors, a statistical approach based on the models, and a numerical algorithm designed to perform the statistical estimation on real (noisy) data. We discuss the meaning of development time in the face of mortality, and illustrate the use and the validity of the method with real data from cohorts where the development times were independently measured in situ.

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Author information

Authors and Affiliations

  1. Section of Ecology and Systematics, Cornell University, Ithaca, New York, 14853, USA

    Moshe Braner & Nelson G. Hairston Jr.

Authors
  1. Moshe Braner
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  2. Nelson G. Hairston Jr.
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Editor information

Editors and Affiliations

  1. Departments of Statistics and Zoology, University of Wyoming, Laramie, WY, 82071, USA

    Lyman L. McDonald

  2. Department of Mathematics and Statistics, University of Otago, Dunedin, New Zealand

    Bryan F. J. Manly

  3. Department of Plant, Soil and Insect Sciences, University of Wyoming, Laramie, WY, 82071, USA

    Jeffrey A. Lockwood

  4. Departments of Entomology and Forestry, Virginia Polytechnic Institute, Blacksburg, VA, 24061, USA

    Jesse A. Logan

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© 1989 Springer-Verlag Berlin Heidelberg

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Braner, M., Hairston, N.G. (1989). From Cohort Data to Life Table Parameters Via Stochastic Modeling. In: McDonald, L.L., Manly, B.F.J., Lockwood, J.A., Logan, J.A. (eds) Estimation and Analysis of Insect Populations. Lecture Notes in Statistics, vol 55. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-3664-1_3

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  • DOI: https://doi.org/10.1007/978-1-4612-3664-1_3

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-96998-5

  • Online ISBN: 978-1-4612-3664-1

  • eBook Packages: Springer Book Archive

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