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International Conference Series on Soft Methods in Probability and Statistics

SMPS 2018: Uncertainty Modelling in Data Science pp 191–199Cite as

Empirical Comparison of the Performance of Location Estimates of Fuzzy Number-Valued Data

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 832))

Abstract

Several location measures have already been proposed in the literature in order to summarize the central tendency of a random fuzzy number in a robust way. Among them, fuzzy trimmed means and fuzzy M-estimators of location extend two successful approaches from the real-valued settings. The aim of this work is to present an empirical comparison of different location estimators, including both fuzzy trimmed means and fuzzy M-estimators, to study their differences in finite sample behaviour.

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References

  1. Sinova, B., Gil, M.Á., Van Aelst, S.: M-estimates of location for the robust central tendency of fuzzy data. IEEE Trans. Fuzzy Syst. 24(4), 945–956 (2016)

    Article  Google Scholar 

  2. Sinova, B., Pérez-Fernández, S., Montenegro, M.: The Wabl/Ldev/Rdev median of a random fuzzy number and statistical properties. In: Grzegorzewski, P., Gagolewski, M., Hryniewicz, O., Gil, M.Á. (eds.) Strengthening Links Between Data Analysis and Soft Computing. Advances in Intelligent Systems and Computing, vol. 315, pp. 143–150. Springer, Cham (2015)

    MATH  Google Scholar 

  3. Colubi, A., González-Rodríguez, G.: Fuzziness in data analysis: towards accuracy and robustness. Fuzzy Sets Syst. 281, 260–271 (2015)

    Article  MathSciNet  Google Scholar 

  4. Sinova, B., de la Rosa de Sáa, S., Gil, M.Á.: A generalized L1-type metric between fuzzy numbers for an approach to central tendency of fuzzy data. Inf. Sci. 242, 22–34 (2013)

    Article  MathSciNet  Google Scholar 

  5. Sinova, B., Gil, M.Á., Colubi, A., Van Aelst, S.: The median of a random fuzzy number. The 1-norm distance approach. Fuzzy Sets Syst. 200, 99–115 (2012)

    Article  MathSciNet  Google Scholar 

  6. Puri, M.L., Ralescu, D.A.: Fuzzy random variables. J. Math. Anal. Appl. 114, 409–422 (1986)

    Article  MathSciNet  Google Scholar 

  7. Lubiano, M.A., Salas, A., Gil, M.Á.: A hypothesis testing-based discussion on the sensitivity of means of fuzzy data with respect to data shape. Fuzzy Sets Syst. 328, 54–69 (2017)

    Article  MathSciNet  Google Scholar 

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Acknowledgements

This research has been partially supported by the Spanish Ministry of Economy, Industry and Competitiveness Grant MTM2015-63971-P. Its support is gratefully acknowledged.

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Authors and Affiliations

  1. Departamento de Estadística e I.O. y D.M., Universidad de Oviedo, Oviedo, Spain

    Beatriz Sinova

  2. Department of Mathematics, KU Leuven, Leuven, Belgium

    Stefan Van Aelst

Authors
  1. Beatriz Sinova
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  2. Stefan Van Aelst
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Corresponding author

Correspondence to Beatriz Sinova .

Editor information

Editors and Affiliations

  1. CNRS, Heudiasyc, Sorbonne universités, Université de technologie de Compiègne, Compiegne, France

    Sébastien Destercke

  2. CNRS, Heudiasyc, Sorbonne universités, Université de technologie de Compiègne, Compiegne, France

    Thierry Denoeux

  3. Department of Statistics and Operational Research and Mathematics Didactics, University of Oviedo, Oviedo, Asturias, Spain

    María Ángeles Gil

  4. Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland

    Przemyslaw Grzegorzewski

  5. Department of Stochastic Methods, Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Olgierd Hryniewicz

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Sinova, B., Van Aelst, S. (2019). Empirical Comparison of the Performance of Location Estimates of Fuzzy Number-Valued Data. In: Destercke, S., Denoeux, T., Gil, M., Grzegorzewski, P., Hryniewicz, O. (eds) Uncertainty Modelling in Data Science. SMPS 2018. Advances in Intelligent Systems and Computing, vol 832. Springer, Cham. https://doi.org/10.1007/978-3-319-97547-4_25

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