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Probabilistic Models of Population Evolution: Scaling Limits, Genealogies and Interactions de Étienne Pardoux

Probabilistic Models of Population Evolution: Scaling Limits, Genealogies and Interactions: Mathematical Biosciences Institute Lecture Series, cartea 1.6

Autor Étienne Pardoux
en Limba Engleză Paperback – 27 iun 2016
This expository book presents the mathematical description of evolutionary models of populations subject to interactions (e.g. competition) within the population. The author includes both models of finite populations, and limiting models as the size of the population tends to infinity. The size of the population is described as a random function of time and of the initial population (the ancestors at time 0). The genealogical tree of such a population is given. Most models imply that the population is bound to go extinct in finite time. It is explained when the interaction is strong enough so that the extinction time remains finite, when the ancestral population at time 0 goes to infinity. The material could be used for teaching stochastic processes, together with their applications.

Étienne Pardoux is Professor at Aix-Marseille University, working in the field of Stochastic Analysis, stochastic partial differential equations, and probabilistic models in evolutionary biology and population genetics. He obtained his PhD in 1975 at University of Paris-Sud.
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Specificații

ISBN-13: 9783319303260
ISBN-10: 3319303260
Pagini: 126
Ilustrații: VIII, 125 p. 6 illus., 2 illus. in color.
Dimensiuni: 155 x 235 x 9 mm
Greutate: 0.27 kg
Ediția:1st ed. 2016
Editura: Springer International Publishing
Colecția Springer
Seriile Mathematical Biosciences Institute Lecture Series, Stochastics in Biological Systems

Locul publicării:Cham, Switzerland

Cuprins

Introduction.- Branching Processes.- Convergence to a Continuous State Branching Process.- Continuous State Branching Process (CSBP).- Genealogies.- Models of Finite Population with Interaction.- Convergence to a Continuous State Model.- Continuous Model with Interaction.- Appendix.

Recenzii

“This book presents the mathematical description of evolutionary models of populations subject to interactions within the population. … For readers’ convenience, the book contains an appendix summarizing the necessary backgrounds and technical results on stochastic calculus. The materials are presented with clarity, brevity and styles. … The book provides nice supplementary material for courses in stochastic processes and stochastic calculus.” (Chao Zhu, Mathematical Reviews, April, 2017)

“The main originality of the book is the fact that it describes the evolution of a population where the birth or death rates of the various individuals are affected by the size of the population. … The book is mainly intended to readers with some basic knowledge of stochastic processes and stochastic calculus. All in all, this is a serious piece of work.” (Marius Iosifescu, zbMATH 1351.92003, 2017)

Notă biografică

Étienne Pardoux is Professor at Aix-Marseille University, working in the field of Stochastic Analysis, in particular Stochastic partial differential equations. He obtained his PhD in 1975 at University of Paris-Sud.

Textul de pe ultima copertă

This expository book presents the mathematical description of evolutionary models of populations subject to interactions (e.g. competition) within the population. The author includes both models of finite populations, and limiting models as the size of the population tends to infinity. The size of the population is described as a random function of time and of the initial population (the ancestors at time 0). The genealogical tree of such a population is given. Most models imply that the population is bound to go extinct in finite time. It is explained when the interaction is strong enough so that the extinction time remains finite, when the ancestral population at time 0 goes to infinity. The material could be used for teaching stochastic processes, together with their applications.

Étienne Pardoux is Professor at Aix-Marseille University, working in the field of Stochastic Analysis, stochastic partial differential equations, and probabilistic models in evolutionary biology and population genetics. He obtained his PhD in 1975 at University of Paris-Sud.

Caracteristici

Includes deep mathematical notions in connection with motivating applications Suitable for graduate students and researchers in mathematical biology Co-published jointly with Mathematical Biosciences Institute