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BIVARIATE MARSHALL–OLKIN EXPONENTIAL SHOCK MODEL

Published online by Cambridge University Press:  17 April 2020

H.A. Mohtashami-Borzadaran ,
H. Jabbari Open the ORCID record for H. Jabbari [Opens in a new window]  and
M. Amini
H.A. Mohtashami-Borzadaran
Affiliation:
Department of Statistics, Ferdowsi University of Mashhad, Mashhad, Iran. E-mail: [email protected]
H. Jabbari
Affiliation:
Department of Statistics, Ferdowsi University of Mashhad, Mashhad, Iran. E-mail: [email protected]
M. Amini
Affiliation:
Department of Statistics, Ferdowsi University of Mashhad, Mashhad, Iran. E-mail: [email protected]
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Abstract

The well-known Marshall–Olkin model is known for its extension of exponential distribution preserving lack of memory property. Based on shock models, a new generalization of the bivariate Marshall–Olkin exponential distribution is given. The proposed model allows wider range tail dependence which is appealing in modeling risky events. Moreover, a stochastic comparison according to this shock model and also some properties, such as association measures, tail dependence and Kendall distribution, are presented. The new shock model is analytically quite tractable, and it can be used quite effectively, to analyze discrete–continuous data. This has been shown on real data. Finally, we propose the multivariate extension of the Marshall–Olkin model that has some intersection with the well-known multivariate Archimax copulas.

Keywords

distortion copulaMarshall–Olkin modelshock modelstochastic comparison
Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 35 , Issue 3 , July 2021 , pp. 745 - 765
Copyright
© Cambridge University Press 2020

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