Growing synthetic data through differentially-private vine copulas
نویسندگان
چکیده
منابع مشابه
Selection of Vine Copulas
Vine copula models have proven themselves as a very flexible class of multivariate copula models with regard to symmetry and tail dependence for pairs of variables. The full specification of a vine model requires the choice of vine tree structure, copula families for each pair copula term and their corresponding parameters. In this survey we discuss the different approaches, both frequentist as...
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Tail dependence and conditional tail dependence functions describe, respectively, the tail probabilities and conditional tail probabilities of a copula at various relative scales. The properties as well as the interplay of these two functions are established based upon their homogeneous structures. The extremal dependence of a copula, as described by its extreme value copulas, is shown to be co...
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Vine copulas are flexible multivariate dependence models, which are built up from a set of bivariate copulas in different hierarchical levels. However, vine copulas have a computational complexity that is increasing quadratically in the number of variables. This complexity can be reduced by focusing on the sub-class of truncated vine copulas, which use only a limited number of hierarchical leve...
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ژورنال
عنوان ژورنال: Proceedings on Privacy Enhancing Technologies
سال: 2021
ISSN: 2299-0984
DOI: 10.2478/popets-2021-0040