Abstract
A new measure of skewness for real-valued random variables based on fuzzy tools has been recently introduced. The measure is derived from certain fuzzy representations of real-valued random variables which can be used to characterize the distribution of the original variables through the expected value of the ‘fuzzified’ random variables. In this communication, the empirical behaviour of an asymptotic testing procedure for the symmetry of real random variables based on this approach will be examined by simulating different distributions. Some advantages of the proposed test will be illustrated by means of these simulations.
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Lubiano, M.A., Colubi, A., González-Rodríguez, G. (2008). Empirical Results Concerning a Fuzzy-Based Measure of Symmetry of Real Random Variables. In: Dubois, D., Lubiano, M.A., Prade, H., Gil, M.Á., Grzegorzewski, P., Hryniewicz, O. (eds) Soft Methods for Handling Variability and Imprecision. Advances in Soft Computing, vol 48. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85027-4_19
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DOI: https://doi.org/10.1007/978-3-540-85027-4_19
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