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Industrial Statistics pp 17–25Cite as

The Calibration Problem in Industry

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

Abstract

The calibration problem has been faced from different lines of thought (classical, Bayesian, structural, nonparametric, robust approach) and for different applications in industry (gas liquid chromatography, flame emission spectrometry, photometric analysis, etc.). The problem remains the evaluation of confidence intervals. This paper proposes an optimal design approach, adopting D and c-optimality, to obtain the asymptotic variance of the calibrating value, so that approximate confidence intervals can be evaluated.

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Author information

Authors and Affiliations

  1. Athens University of Economics and Business, Patission 76, Athens, 10434, Greece

    C. P. Kitsos & V. L. Ninni

Authors
  1. C. P. Kitsos
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  2. V. L. Ninni
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Editor information

Editors and Affiliations

  1. Department of Statistics, Athens University of Economics and Business, 76 Patission Street, 104 34, Athens, Greece

    Christos P. Kitsos

  2. German Cancer Research Center, Biostatistics Unit, Im Neuenheimer Feld 280, D-69120, Heidelberg, Germany

    Lutz Edler

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© 1997 Springer-Verlag Berlin Heidelberg

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Kitsos, C.P., Ninni, V.L. (1997). The Calibration Problem in Industry. In: Kitsos, C.P., Edler, L. (eds) Industrial Statistics. Contributions to Statistics. Physica, Heidelberg. https://doi.org/10.1007/978-3-642-59268-3_2

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  • DOI: https://doi.org/10.1007/978-3-642-59268-3_2

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-1042-4

  • Online ISBN: 978-3-642-59268-3

  • eBook Packages: Springer Book Archive

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