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dc.contributor.authorVladik Kreinovichen_US
dc.contributor.authorHung T. Nguyenen_US
dc.contributor.authorSongsak Sriboonchittaen_US
dc.description.abstractIn econometrics, many distributions are non-Gaussian. To describe dependence between non-Gaussian variables, it is usually not sufficient to provide their correlation: it is desirable to also know the corresponding copula. There are many different families of copulas; which family shall we use? In many econometric applications, two families of copulas have been most efficient: the Clayton and the Gumbel copulas. In this paper, we provide a theoretical explanation for this empirical efficiency, by showing that these copulas naturally follow from reasonable symmetry assumptions. This symmetry justification also allows us to provide recommendations about which families of copulas we should use when we need a more accurate description of dependence. © 2013 Springer-Verlag Berlin Heidelberg.en_US
dc.subjectComputer Scienceen_US
dc.titleWhy clayton and gumbel copulas: A symmetry-based explanationen_US
dc.typeBook Seriesen_US
article.title.sourcetitleAdvances in Intelligent Systems and Computingen_US
article.volume200 AISCen_US of Texas at El Pasoen_US Mexico State University Las Crucesen_US Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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