Stochastic modeling of the chemostat

被引:74
作者
Campillo, F. [1 ]
Joannides, M. [1 ,2 ]
Larramendy-Valverde, I. [2 ]
机构
[1] UMR MISTEA, INRIA INRA, MERE Project Team, F-34060 Montpellier 01, France
[2] Univ Montpellier 2 13M, F-34095 Montpellier 5, France
关键词
Stochastic differential equations; Chemostat; Pure jump process; Diffusion approximation; Tau-leap method; Monte Carlo method; Gillespie algorithm; CHEMICALLY REACTING SYSTEMS; JUMP MARKOV PROCESSES; TAU-LEAPING SCHEMES; POPULATIONS; SIMULATION; GROWTH;
D O I
10.1016/j.ecolmodel.2011.04.027
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
The chemostat is classically represented, at large population scale, as a system of ordinary differential equations. Our goal is to establish a set of stochastic models that are valid at different scales: from the small population scale to the scale immediately preceding the one corresponding to the deterministic model. At a microscopic scale we present a pure jump stochastic model that gives rise, at the macroscopic scale, to the ordinary differential equation model. At an intermediate scale, an approximation diffusion allows us to propose a model in the form of a system of stochastic differential equations. We expound the mechanism to switch from one model to another, together with the associated simulation procedures. We also describe the domain of validity of the different models. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码:2676 / 2689
页数:14
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