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Journal of Inverse and Ill-posed Problems

Editor-in-Chief: Kabanikhin, Sergey I.

6 Issues per year


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CiteScore 2017: 0.91

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1569-3945
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Volume 24, Issue 3

Issues

Generalized sensitivity functions for size-structured population models

Dustin D. Keck / David M. BortzORCID iD: http://orcid.org/0000-0003-1163-7317
Published Online: 2015-05-21 | DOI: https://doi.org/10.1515/jiip-2014-0041

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.

Keywords: Size-structured population model; generalized sensitivity; Smoluchowski coagulation equation

MSC: 92D25; 62K99

About the article

Received: 2014-06-02

Revised: 2015-02-27

Accepted: 2015-03-17

Published Online: 2015-05-21

Published in Print: 2016-06-01


Funding Source: National Science Foundation

Award identifier / Grant number: DMS-1225878

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


Citation Information: Journal of Inverse and Ill-posed Problems, Volume 24, Issue 3, Pages 309–321, ISSN (Online) 1569-3945, ISSN (Print) 0928-0219, DOI: https://doi.org/10.1515/jiip-2014-0041.

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