A hierarchical kinetic theory of birth, death, and fission in age-structured interacting populations

Chou, Tom and Greenman, Chris D. (2016) A hierarchical kinetic theory of birth, death, and fission in age-structured interacting populations. Journal of Statistical Physics, 164 (1). pp. 49-76. ISSN 0022-4715

[img]
Preview
PDF (Published_version) - Published Version
Available under License Creative Commons Attribution.

Download (1MB) | Preview

Abstract

We study mathematical models describing the evolution of stochastic age-structured populations. After reviewing existing approaches, we develop a complete kinetic framework for age-structured interacting populations undergoing birth, death and fission processes in spatially dependent environments. We define the full probability density for the population-size age chart and find results under specific conditions. Connections with more classical models are also explicitly derived. In particular, we show that factorial moments for non-interacting processes are described by a natural generalization of the McKendrick-von Foerster equation, which describes mean-field deterministic behavior. Our approach utilizes mixed-type, multidimensional probability distributions similar to those employed in the study of gas kinetics and with terms that satisfy BBGKY-like equation hierarchies.

Item Type: Article
Additional Information: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Uncontrolled Keywords: age structure,birth death process,kinetics,fission
Faculty \ School: Faculty of Science > School of Computing Sciences

University of East Anglia > Faculty of Science > Research Groups > Computational Biology (subgroups are shown below) > Analysis and models of genomic variation
Related URLs:
Depositing User: Pure Connector
Date Deposited: 23 May 2016 15:00
Last Modified: 24 Jun 2020 23:58
URI: https://ueaeprints.uea.ac.uk/id/eprint/59002
DOI: 10.1007/s10955-016-1524-x

Actions (login required)

View Item View Item