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An Asymptotic Test for Symmetry of Random Variables Based on Fuzzy Tools

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Part of the book series: Advances in Soft Computing ((AINSC,volume 37))

Abstract

A new measure of skewness for real random variables is proposed in this paper. The measure is based on a fuzzy representation of real-valued random variables which can be used to characterize the distribution of the original variable through the expected value of the ‘fuzzified’ random variable. Inferential studies concerning the expected value of fuzzy random variables provide us with a tool to analyze the asymmetry degree from random samples. As a first step, we propose an asymptotic test of symmetry. We present some examples and simulations to illustrate the behaviour of the proposed test.

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References

  1. C. Bertoluzza, N. Corral, and A. Salas. On a new class of distances between fuzzy numbers. Mathware Soft Comput., 2:71–84, 1995.

    MATH  MathSciNet  Google Scholar 

  2. A. Colubi, J. S. Domínguez-Menchero, M. López-Díaz, and D. A. Ralescu. A d e [0,1]-representation of random upper semicontinuous functions. Proc. Amer. Math. Soc., 130:3237–3242, 2002.

    Article  MATH  MathSciNet  Google Scholar 

  3. P. Diamond and P. Kloeden. Metric Spaces of Fuzzy Sets: Theory and Applications. World Scientific, Singapore, 1994.

    MATH  Google Scholar 

  4. D. García, M. A. Lubiano, and M. C. Alonso. Estimating the expected value of fuzzy random variables in the stratified random sampling from finite populations. Inform. Sci., 138:165–184, 2001.

    Article  MATH  MathSciNet  Google Scholar 

  5. M.A. Gil, M. Montenegro, G. González-Rodríguez, A. Colubi, and M.R. Casals. Bootstrap approach to the multi-sample test of means with imprecise data. Comput. Statist. Data Anal., 2006. (accepted, in press).

    Google Scholar 

  6. G. González-Rodríguez, A. Colubi, and M.A. Gil. A fuzzy representation of random variables: an operational oool in exploratory analysis and hypothesis testing. Comput. Statist. Data Anal, 2006. (accepted, in press).

    Google Scholar 

  7. G. González-Rodríguez, A. Colubi, M.A. Gil, and P. D’Urso. An asymptotic two dependent samples test of equality of means of fuzzy random variables. In COMPSTAT, 2006. (in press).

    Google Scholar 

  8. G. González-Rodríguez, M. Montenegro, A. Colubi, and M.A. Gil. Bootstrap techniques and fuzzy random variables: Synergy in hypothesis testing with fuzzy data. Fuzzy Sets and Systems, 2006. (accepted, in press).

    Google Scholar 

  9. R. Körner. An asymptotic α-test for the expectation of random fuzzy variables. J. Statist. Plann. Inference, 83:331–346, 2000.

    Article  MATH  MathSciNet  Google Scholar 

  10. M. A. Lubiano and M. A. Gil. Estimating the expected value of fuzzy random variables in random samplings from finite populations. Statist. Papers, 40:277–295, 1999.

    Article  MATH  MathSciNet  Google Scholar 

  11. M. A. Lubiano, M. A. Gil, and M. López-Díaz. On the rao-blackwell theorem for fuzzy random variables. Kybernetika, 35:167–175, 1999.

    MathSciNet  Google Scholar 

  12. M. Montenegro, M. R. Casals, M. A. Lubiano, and M. A. Gil. Two-sample hypothesis tests of means of a fuzzy random variable. Inform. Sci., 133:89–100, 2001.

    Article  MATH  MathSciNet  Google Scholar 

  13. M. Montenegro, A. Colubi, M. R. Casals, and M. A. Gil. Asymptotic and bootstrap techniques for testing the expected value of a fuzzy random variable. Metrika, 59:31–49, 2004.

    Article  MATH  MathSciNet  Google Scholar 

  14. M. Montenegro, G. González-Rodríguez, M. A. Gil, A. Colubi, and M. R. Casals. Introduction to ANOVA with fuzzy random variables. In M. López- Díaz, M. A. Gil, P. Grzegorzewski, O. Hryniewicz, and J. Lawry, editors, Soft Methodology and Random Information Systems, pages 487–494. Springer- Verlag, Berlin, 2004.

    Google Scholar 

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

    Article  MATH  MathSciNet  Google Scholar 

  16. L.A. Zadeh. The concept of a linguistic variable and its application to approximate reasoning, II. Inform. Sci., 8:301–353, 1975.

    Article  MathSciNet  Google Scholar 

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G., GR., A., C., P., D., P., G. (2006). An Asymptotic Test for Symmetry of Random Variables Based on Fuzzy Tools. In: Lawry, J., et al. Soft Methods for Integrated Uncertainty Modelling. Advances in Soft Computing, vol 37. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-34777-1_12

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  • DOI: https://doi.org/10.1007/3-540-34777-1_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34776-7

  • Online ISBN: 978-3-540-34777-4

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