Stochastic Models for Structured Populations
Produktnummer:
18143d4f0767304144b124898cdba07476
Autor: | Bansaye, Vincent Meleard, Sylvie |
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Themengebiete: | Birth and death processes Branching processes in random environment Cell division dynamics Continuous state branching processes Large population approximations Martingale properties Measure-valued Markov processes Population models Two-level models |
Veröffentlichungsdatum: | 15.09.2015 |
EAN: | 9783319217109 |
Sprache: | Englisch |
Seitenzahl: | 107 |
Produktart: | Kartoniert / Broschiert |
Verlag: | Springer International Publishing |
Untertitel: | Scaling Limits and Long Time Behavior |
Produktinformationen "Stochastic Models for Structured Populations"
In this contribution, several probabilistic tools to study population dynamics are developed. The focus is on scaling limits of qualitatively different stochastic individual based models and the long time behavior of some classes of limiting processes.Structured population dynamics are modeled by measure-valued processes describing the individual behaviors and taking into account the demographic and mutational parameters, and possible interactions between individuals. Many quantitative parameters appear in these models and several relevant normalizations are considered, leading to infinite-dimensional deterministic or stochastic large-population approximations. Biologically relevant questions are considered, such as extinction criteria, the effect of large birth events, the impact of environmental catastrophes, the mutation-selection trade-off, recovery criteria in parasite infections, genealogical properties of a sample ofindividuals.These notes originated from a lecture series on Structured Population Dynamics at Ecole polytechnique (France).Vincent Bansaye and Sylvie Méléard are Professors at Ecole Polytechnique (France). They are a specialists of branching processes and random particle systems in biology. Most of their research concerns the applications of probability to biodiversity, ecology and evolution.

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