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Interval Analysis for Guaranteed Nonlinear Parameter Estimation

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MODA 5 — Advances in Model-Oriented Data Analysis and Experimental Design

Part of the book series: Contributions to Statistics ((CONTRIB.STAT.))

Abstract

Estimating the parameters of nonlinear models from experimental data often involves optimizing nonconvex cost functions. This introductory paper illustrates how interval analysis can be used to perform this task in a guaranteed way, in contrast with the usual local iterative methods.

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References

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Authors
  1. M. Kieffer
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  2. E. Walter
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Editor information

Editors and Affiliations

  1. Department of Statistics, The London School of Economics and Political Science, Houghton Street, London, WC2A 2AE, UK

    Anthony C. Atkinson

  2. Laboratoire I3S, Centre National de la Recherche Scientifique (CNRS), 250 rue Albert Einstein, Sophia Antipolis, Valbonne, F-06560, France

    Luc Pronzato

  3. Department of Statistics, University of Warwick, Gibbet Hill Road, Coventry, CV4 7AL, UK

    Henry P. Wynn

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© 1998 Springer-Verlag Berlin Heidelberg

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Kieffer, M., Walter, E. (1998). Interval Analysis for Guaranteed Nonlinear Parameter Estimation. In: Atkinson, A.C., Pronzato, L., Wynn, H.P. (eds) MODA 5 — Advances in Model-Oriented Data Analysis and Experimental Design. Contributions to Statistics. Physica, Heidelberg. https://doi.org/10.1007/978-3-642-58988-1_13

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  • DOI: https://doi.org/10.1007/978-3-642-58988-1_13

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-1111-7

  • Online ISBN: 978-3-642-58988-1

  • eBook Packages: Springer Book Archive

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