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Title: On the trade-off between experimental effort and information content in optimal experimental design for calibrating a predictive microbiology model
Authors: Telen, Dries ×
Logist, Filip
Van Derlinden, Eva
Van Impe, Jan #
Issue Date: Apr-2013
Publisher: Association Recherche Statistique et Applications
Series Title: Journal de la Societe Francaise de Statistique & Revue de Statistique Appliquee vol:154 issue:3 pages:95-112
Abstract: In predictive microbiology, dynamic mathematical models are developed to describe microbial evolution under time-varying environmental conditions. Next to an acceptable model structure, reliable parameter values are necessary to obtain valid model predictions. To obtain these accurate estimates of the model parameters, labor-and cost-intensive experiments have to be performed. Optimal experimental design techniques for parameter estimation are beneficial to limit the experimental burden. An important issue in optimal experimental design, included in this work, is the sampling scheme. Recent work illustrates that identifying sampling decisions results in bang-bang control of the weighting function in the Fisher information matrix. A second point addressed in this work is the trade-off between the amount of time an experimenter has available for measurements on the one hand, and information content on the other hand. Recently, multi-objective optimization is applied to several different optimal experimental design criteria, whereas in this paper the workload expressed as when to sample, is considered. The procedure is illustrated through simulations with a case study for the Cardinal Temperature Model with Inflection. The viability of the obtained experiments is assessed by calculating the confidence regions with two different methods: the Fisher information matrix approach and the Monte-Carlo method approach
ISSN: 0037-914X
Publication status: published
KU Leuven publication type: AT
Appears in Collections:Bio- & Chemical Systems Technology, Reactor Engineering and Safety Section
× corresponding author
# (joint) last author

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