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Exploiting the bootstrap method for quantifying parameter confidence intervals in dynamical systems.

M Joshi·A Seidel-Morgenstern·A Kremling
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Abstract

A quantitative description of dynamical systems requires the estimation of uncertain kinetic parameters and an analysis of their precision. A method frequently used to describe the confidence intervals of estimated parameters is based on the Fisher-Information-Matrix. The application of this traditional method has two important shortcomings: (i) it gives only lower bounds for the variance of a parameter if the solution of the underlying model equations is non-linear in parameters. (ii) The resulting confidence interval is symmetric with respect to the estimated parameter. Here, we show that by applying the bootstrap method a better approximation of (possibly) asymmetric confidence intervals for parameters could be obtained. In contrast to previous applications devoted to non-parametric problems, a dynamical model describing a bio-chemical network is used to evaluate the method.

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AlgorithmsCell Physiological PhenomenaComputer SimulationModels, BiologicalProteomeReproducibility of ResultsSensitivity and SpecificitySignal TransductionJournal ArticleResearch Support, Non-U.S. Gov't

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M Joshi, A Seidel-Morgenstern, A Kremling. 2006-05-06. Exploiting the bootstrap method for quantifying parameter confidence intervals in dynamical systems.. https://doi.org/10.1016/j.ymben.2006.04.003

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