Overview
- 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
Part of the book series: Mathematical Biosciences Institute Lecture Series (MBILS, volume 1.6)
Part of the book sub series: Stochastics in Biological Systems (STOCHBS)
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Table of contents(8 chapters)
About this book
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.
Reviews
“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)
Authors and Affiliations
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Institut de Math´ematiques de Marseille, Aix-Marseille Universit´e, Marseilles, France
Étienne Pardoux
About the author
Bibliographic Information
Book Title: Probabilistic Models of Population Evolution
Book Subtitle: Scaling Limits, Genealogies and Interactions
Authors: Étienne Pardoux
Series Title: Mathematical Biosciences Institute Lecture Series
DOI: https://doi.org/10.1007/978-3-319-30328-4
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing Switzerland 2016
Softcover ISBN: 978-3-319-30326-0Published: 27 June 2016
eBook ISBN: 978-3-319-30328-4Published: 17 June 2016
Edition Number: 1
Number of Pages: VIII, 125
Number of Illustrations: 4 b/w illustrations, 2 illustrations in colour
Additional Information: Copublished with the Mathematical Biosciences Institute, Columbus, OH, USA
Topics: Mathematical and Computational Biology, Probability Theory and Stochastic Processes, Theoretical Ecology/Statistics