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

  • Dmitry A. MatsypaevEmail author
  • Andrey G. Bronevich
Chapter
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 315)

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.

Keywords

distortion function triangular norm fuzzy set Neyman-Pearson criterion outliers Lipschitz continuity 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Southern Federal UniversityTaganrogRussia
  2. 2.National Research University Higher School of EconomicsMoscowRussia

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