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Tail Dependence of a Pareto Process

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New Advances in Statistical Modeling and Applications

Part of the book series: Studies in Theoretical and Applied Statistics ((STASSPSS))

Abstract

Heavy-tailed autoregressive processes defined with minimum or maximum operator are good alternatives to classic linear ARMA with heavy tail noises, in what concerns extreme values modeling. In this paper we present a full characterization of the tail dependence of the autoregressive minima process, Yeh–Arnold–Robertson Pareto(III).

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Correspondence to Marta Ferreira .

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Ferreira, M. (2014). Tail Dependence of a Pareto Process. In: Pacheco, A., Santos, R., Oliveira, M., Paulino, C. (eds) New Advances in Statistical Modeling and Applications. Studies in Theoretical and Applied Statistics(). Springer, Cham. https://doi.org/10.1007/978-3-319-05323-3_17

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