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Asymptotic and Bootstrap techniques for testing the expected value of a fuzzy random variable
Authors:Manuel?Montenegro,Ana?Colubi,María?Rosa Casals,María?ángeles Gil  author-information"  >  author-information__contact u-icon-before"  >  mailto:angeles@pinon.ccu.uniovi.es"   title="  angeles@pinon.ccu.uniovi.es"   itemprop="  email"   data-track="  click"   data-track-action="  Email author"   data-track-label="  "  >Email author
Affiliation:(1) Dpto. de Estadística, I.O. y D.M. Universidad de Oviedo, 33071, Oviedo, Spain
Abstract:In this paper we will consider hypothesis-tests for the (fuzzy-valued) mean value of a fuzzy random variable in a population. For this purpose, we will make use of a generalized metric for fuzzy numbers, and we will develop an approach for normal fuzzy random variables, and two different approaches for the case of fuzzy random variables taking on a finite number of different values. A real-life example illustrates the use of the last two approaches. Finally, a comparison between the introduced techniques is developed by means of simulation studies leading to close inferential conclusions.Acknowledgements.enspThe research in this paper has been partially supported by MCYT Grants BFM2002-01057 and BFM2001-3494. Their financial support is gratefully acknowledged. The authors are sincerely grateful to their colleague Gil González-Rodríguez for all his comments and suggestions in connection with this paper; his scientific support has been very valuable. The authors want also thank the referees of the first version of the paper because of their useful hints to improve it.
Keywords:Boot strap  Distance between fuzzy numbers  Fuzzy random variables  Large Smaple Theory
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