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Erschienen in:
2017 | OriginalPaper | Buchkapitel
One-Factor Lévy-Frailty Copulas with Inhomogeneous Trigger Rates
verfasst von : Janina Engel, Matthias Scherer, Leonhard Spiegelberg
Erschienen in: Soft Methods for Data Science
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Abstract
A new parametric family of high-dimensional, non-exchangeable extreme-value copulas is presented. The construction is based on the Lévy-frailty construction and stems from a subfamily of the Marshall–Olkin distribution. In contrast to the classical Lévy-frailty construction, non-exchangeability is achieved by inhomogeneous trigger-rate parameters. This family is studied with respect to its distributional properties and a sampling algorithm is developed. Moreover, a new estimator for its parameters is given. The estimation strategy consists in minimizing the mean squared error of the underlying Bernstein function and certain strongly consistent estimates thereof.