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Generalized sensitivity functions for size-structured population models

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Veröffentlicht/Copyright: 21. Mai 2015

Abstract

Size-structured population models provide a popular means to mathematically describe phenomena such as bacterial aggregation, schooling fish, and planetesimal evolution. For parameter estimation, a generalized sensitivity function (GSF) provides a tool that quantifies the impact of data from specific regions of the experimental domain. This function helps to identify the most relevant data subdomains, which enhances the optimization of experimental design. To our knowledge, GSFs have not been used in the partial differential equation (PDE) realm, so we provide a novel PDE extension of the discrete and continuous ordinary differential equation (ODE) concepts of Thomaseth and Cobelli and Banks et al. respectively. We analyze a GSF in the context of size-structured population models, and specifically analyze the Smoluchowski coagulation equation to determine the most relevant time and volume domains for three, distinct aggregation kernels. Finally, we provide evidence that parameter estimation for the Smoluchowski coagulation equation does not require post-gelation data.

MSC: 92D25; 62K99

Award Identifier / Grant number: DMS-1225878

Funding statement: This work was supported in part by the National Science Foundation grant DMS-1225878.

We would like to thank Dr. John Younger in the Department of Emergency Medicine at the University of Michigan for discussions concerning experimental data. We would also like to acknowledge the anonymous reviewers who made several suggestions that greatly improved the clarity of this article.

Received: 2014-6-2
Revised: 2015-2-27
Accepted: 2015-3-17
Published Online: 2015-5-21
Published in Print: 2016-6-1

© 2016 by De Gruyter

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