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2016•DOAJ (DOAJ: Directory of Open Access Journals)Open access

The Cambanis family of bivariate distributions: Properties and applications

N. Unnikrishnan Nair, Johny Scaria, Sithara Mohan

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Abstract

The Cambanis family of bivariate distributions was introduced as a generalization of the Farlie-Gumbel-Morgenstern system. The present work is an attempt to investigate the distributional characteristics and applications of the family. We derive various coecients of association, dependence concepts and time-dependent measures. Bivariate reliability functions such as hazard rates and mean residual life functions are analysed. The application of the family as a model for bivariate lifetime data is also demonstrated.

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What this paper is about

The Cambanis family of bivariate distributions was introduced as a generalization of the Farlie-Gumbel-Morgenstern system. The present work is an attempt to investigate the distributional characteristics and applications of the family. We derive various coecients of association, dependence concepts and time-dependent measures. Bivariate reliability functions such as hazard rates and mean residual life functions are analysed. The application of the family as a model for bivariate lifetime data is also demonstrated.

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Available abstract

The Cambanis family of bivariate distributions was introduced as a generalization of the Farlie-Gumbel-Morgenstern system. The present work is an attempt to investigate the distributional characteristics and applications of the family. We derive various coecients of association, dependence concepts and time-dependent measures. Bivariate reliability functions such as hazard rates and mean residual life functions are analysed. The application of the family as a model for bivariate lifetime data is also demonstrated.

Key concepts: Bivariate analysis, Mathematics, Statistics, Econometrics, Statistical physics, Physics

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