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- W3129091179 abstract "Lévy copulas are an important tool which can be used to build dependent Lévy processes. In a classical setting, they have been used to model financial applications. In a Bayesian framework they have been employed to introduce dependent nonparametric priors which allow to model heterogeneous data. This paper focuses on introducing a new class of Lévy copulas based on a class of subordinators recently appeared in the literature, called compound random measures. The well-known Clayton Lévy copula is a special case of this new class. Furthermore, we provide some novel results about the underlying vector of subordinators such as a series representation and relevant moments. The article concludes with an application to a Danish fire dataset." @default.
- W3129091179 created "2021-02-15" @default.
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- W3129091179 date "2021-05-01" @default.
- W3129091179 modified "2023-10-02" @default.
- W3129091179 title "Compound vectors of subordinators and their associated positive Lévy copulas" @default.
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- W3129091179 doi "https://doi.org/10.1016/j.jmva.2021.104728" @default.
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