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Consistent micro, macro and state-based population modelling
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
2010 (English)In: Mathematical Biosciences, ISSN 0025-5564, E-ISSN 1879-3134, Vol. 225, no 2, 94-107 p.Article in journal (Refereed) Published
Abstract [en]

A population system can be modelled using a micro model focusing on the individual entities, a macro model where the entities are aggregated into compartments, or a state-based model where each possible discrete state in which the system can exist is represented. However, the concepts, building blocks, procedural mechanisms and the time handling for these approaches are very different. For the results and conclusions from studies based on micro, macro and state-based models to be consistent (contradiction-free), a number of modelling issues must be understood and appropriate modelling procedures be applied. This paper presents a uniform approach to micro, macro and state-based population modelling so that these different types of models produce consistent results and conclusions. In particular, we demonstrate the procedures (distribution, attribute and combinatorial expansions) necessary to keep these three types of models consistent. We also show that the different time handling methods usually used in micro, macro and state-based models can be regarded as different integration methods that can be applied to any of these modelling categories. The result is free choice in selecting the modelling approach and the time handling method most appropriate for the study without distorting the results and conclusions.

Place, publisher, year, edition, pages
2010. Vol. 225, no 2, 94-107 p.
Keyword [en]
Model comparison, Poisson Simulation, Population model, Simulation methodology, Stochastic integration, Stochastic time handling
National Category
Signal Processing
Research subject
Electrical Engineering with specialization in Signal Processing
Identifiers
URN: urn:nbn:se:uu:diva-133007DOI: 10.1016/j.mbs.2010.02.003ISI: 000278589100002OAI: oai:DiVA.org:uu-133007DiVA: diva2:359983
Available from: 2010-11-01 Created: 2010-11-01 Last updated: 2017-12-12Bibliographically approved

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Sternad, Mikael

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