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Stochastic modeling of population growth

  • Mimmo Iannelli
  • Andrea Pugliese
Chapter
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Part of the UNITEXT book series (UNITEXT, volume 79)

Abstract

Models so far discussed are all deterministic, meaning that, if the present state were perfectly known, it would be possible to predict exactly all future states. Now we try to face the Babylonian lottery considering models that can describe the possible infusion of chaos (but we would rather say chance) into the cosmos, within a probabilistic framework that can take care of all circumstances of events like birth and death.

Keywords

Stationary Distribution Sterile Male Extinction Probability Extinction Time Stationary Probability Distribution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

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    Ethier, S.N., Kurtz, T.G.: Markov processes: characterization and convergence. John Wiley & Sons (2009)Google Scholar
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    Kurtz, T.G.: Approximation of population processes. SIAM (1981)CrossRefGoogle Scholar
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    Norris, J.R.: Markov Chains. Cambridge University Press, Cambridge (1997)CrossRefzbMATHGoogle Scholar
  5. 5.
    Taylor, H.M., Karlin, S.: An Introduction to Stochastic Modeling. Academic Press, San Diego (1998)zbMATHGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Mimmo Iannelli
    • 1
  • Andrea Pugliese
    • 1
  1. 1.Department of MathematicsUniversity of TrentoItaly

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