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The Fuzzy Representation of Prior Information for Separating Outliers in Statistical Experiments

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Strengthening Links Between Data Analysis and Soft Computing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 315))

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Abstract

The paper presents a new fuzzy set based description which helps to distinguish the expected values of the statistical experiment from the outliers. Since the Neyman-Pearson criterion is not adequate in some real applications for such purpose, we propose to use triangular norms for conjuction of two propositions about typical and non-typical values and describe both of them as a fuzzy set that is called the typical transform. We also investigate such a property of the typical transform as stability.

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References

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Author information

Authors and Affiliations

  1. Southern Federal University, Taganrog, Russia

    Dmitry A. Matsypaev

  2. National Research University Higher School of Economics, Moscow, Russia

    Andrey G. Bronevich

Authors
  1. Dmitry A. Matsypaev
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  2. Andrey G. Bronevich
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Corresponding author

Correspondence to Dmitry A. Matsypaev .

Editor information

Editors and Affiliations

  1. Polish Academy of Sciences, Faculty of Mathematics and Information Sciences, Systems Research Institute and Warsaw University of Technology, Warsaw, Poland

    Przemyslaw Grzegorzewski

  2. Polish Academy of Sciences, Faculty of Mathematics and Information Sciences, Systems Research Institute and Warsaw University of Technology, Warsaw, Poland

    Marek Gagolewski

  3. Polish Academy of Sciences Systems Research Institute, Warsaw, Poland

    Olgierd Hryniewicz

  4. Departamento de Estadistica e I.O. y D.M., University of Oviedo, Oviedo, Spain

    María Ángeles Gil

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Matsypaev, D.A., Bronevich, A.G. (2015). The Fuzzy Representation of Prior Information for Separating Outliers in Statistical Experiments. In: Grzegorzewski, P., Gagolewski, M., Hryniewicz, O., Gil, M. (eds) Strengthening Links Between Data Analysis and Soft Computing. Advances in Intelligent Systems and Computing, vol 315. Springer, Cham. https://doi.org/10.1007/978-3-319-10765-3_20

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  • DOI: https://doi.org/10.1007/978-3-319-10765-3_20

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10764-6

  • Online ISBN: 978-3-319-10765-3

  • eBook Packages: EngineeringEngineering (R0)

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