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Activity Number: 426
Type: Contributed
Date/Time: Tuesday, August 2, 2016 : 2:00 PM to 3:50 PM
Sponsor: Section on Risk Analysis
Abstract #319239
Title: Strictly Archimedean Copula with Complete Association for Multivariate Dependence Based on the Clayton Family
Author(s): Kahadawala Cooray *
Companies: Central Michigan University
Keywords: Archimedean copula ; complete monotonicity ; coverage probability ; d-monotonicity ; Kendall's tau ; Kendall's distribution function
Abstract:

The family of Clayton copula is one of the most discussed Archimedean copulas for dependency measurement. The major drawback of this copula is that when it accounts for negative dependence, the copula becomes nonstrict and its support depends on the parameter. The main motivation of this paper is to address this issue by introducing a new two-parameter family of strict Archimedean copula to measure exchangeable multivariate dependence. Closed-form formulas for the complete monotonicity and the d?monotonicity parameter region of the generator, and copula distribution function are derived. In addition, recursive formulas for both copula and radial densities are obtained. Simulation studies are conducted to assess the performance of the maximum likelihood estimators of the d?variate copula under known margins. Furthermore, derivative-free closed-form formula for the Kendall's distribution function are derived. Real multivariate data example is provided to illustrate the flexibility of new copula for negative association.


Authors who are presenting talks have a * after their name.

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