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Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/58705
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dc.contributor.authorSongsak Sriboonchittaen_US
dc.contributor.authorVladik Kreinovichen_US
dc.date.accessioned2018-09-05T04:29:03Z-
dc.date.available2018-09-05T04:29:03Z-
dc.date.issued2018-01-01en_US
dc.identifier.issn1687711Xen_US
dc.identifier.issn16877101en_US
dc.identifier.other2-s2.0-85047815768en_US
dc.identifier.other10.1155/2018/5872195en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85047815768&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/58705-
dc.description.abstract© 2018 Songsak Sriboonchitta and Vladik Kreinovich. One of the most computationally convenient nonredundant ways to describe the dependence between two variables is by describing the corresponding copula. In many applications, a special class of copulas - known as FGM copulas - turned out to be most successful in describing the dependence between quantities. The main result of this paper is that these copulas are the fastest to compute, and this explains their empirical success. As an auxiliary result, we also show that a similar explanation can be given in terms of fuzzy logic.en_US
dc.subjectEngineeringen_US
dc.subjectMathematicsen_US
dc.titleWhy Are FGM Copulas Successful? A Simple Explanationen_US
dc.typeJournalen_US
article.title.sourcetitleAdvances in Fuzzy Systemsen_US
article.volume2018en_US
article.stream.affiliationsChiang Mai Universityen_US
article.stream.affiliationsUniversity of Texas at El Pasoen_US
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