
arXiv: 1405.7963
Population dynamics and in particular microbial population dynamics, though they are complex but also intrinsically discrete and random, are conventionally represented as deterministic differential equations systems. We propose to revisit this approach by complementing these classic formalisms by stochastic formalisms and to explain the links between these representations in terms of mathematical analysis but also in terms of modeling and numerical simulations. We illustrate this approach on the model of chemostat.
arXiv admin note: substantial text overlap with arXiv:1308.2411
Stochastic chemostat model, Mass structured chemostat model, Populations and Evolution (q-bio.PE), [MATH] Mathematics [math], Quantitative Biology - Quantitative Methods, 510, FOS: Biological sciences, [MATH]Mathematics [math], Individually-based model (IBM), Quantitative Biology - Populations and Evolution, Monte Carlo, Quantitative Methods (q-bio.QM), Chemostat model
Stochastic chemostat model, Mass structured chemostat model, Populations and Evolution (q-bio.PE), [MATH] Mathematics [math], Quantitative Biology - Quantitative Methods, 510, FOS: Biological sciences, [MATH]Mathematics [math], Individually-based model (IBM), Quantitative Biology - Populations and Evolution, Monte Carlo, Quantitative Methods (q-bio.QM), Chemostat model
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