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Stochastic Population and Epidemic Models: Persistence and Extinction /

Stochastic Population and Epidemic Models: Persistence and Extinction /
Catalogue Information
Field name Details
Dewey Class 519.2
Title Stochastic Population and Epidemic Models ([EBook]) : Persistence and Extinction / / by Linda J. S. Allen.
Author Allen, Linda J. S.
Other name(s) SpringerLink (Online service)
Edition statement 1st ed. 2015.
Publication Cham : : Springer International Publishing : : Imprint: Springer, , 2015.
Physical Details X, 47 p. 12 illus. in color. : online resource.
Series Mathematical Biosciences Institute Lecture Series ; 1.3
ISBN 9783319215549
Summary Note This monograph provides a summary of the basic theory of branching processes for single-type and multi-type processes. Classic examples of population and epidemic models illustrate the probability of population or epidemic extinction obtained from the theory of branching processes. The first chapter develops the branching process theory, while in the second chapter two applications to population and epidemic processes of single-type branching process theory are explored. The last two chapters present multi-type branching process applications to epidemic models, and then continuous-time and continuous-state branching processes with applications. In addition, several MATLAB programs for simulating stochastic sample paths  are provided in an Appendix. These notes originated as part of a lecture series on Stochastics in Biological Systems at the Mathematical Biosciences Institute in Ohio, USA. Professor Linda Allen is a Paul Whitfield Horn Professor of Mathematics in the Department of Mathematics and Statistics at Texas Tech University, USA.:
Contents note Continuous-Time and Discrete-State Branching Processes -- Applications of Single-Type Branching Processes -- Applications of Multi-Type Branching Processes -- Continuous-Time and Continuous-State Branching Processes.-MatLaB Programs.
System details note Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users).
Internet Site http://dx.doi.org/10.1007/978-3-319-21554-9
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