On Characterizing Generalized Cambanis Family of Bivariate Distributions

Authors

  • Johny Scaria

  • N. Unnikrishnan Nair

cambanis family, FGM system, characterization, regression functions, conditional expectations

Abstract

In this work we present characterizations of a generalized version of Cambanis family of bivariate distributions. This family contains extensions of the Farlie-Gumbel-Morgenstern system as special cases. The characterizations are by properties of P(X>Y), regression functions and E(XjX > Y) which were found to be useful in many applications.

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How to Cite

On Characterizing Generalized Cambanis Family of Bivariate Distributions. (2017). Global Journal of Science Frontier Research, 17(F1), 31-38. https://www.journalofscience.org/index.php/GJSFR/article/view/1947

References

C Amblard, S Girard (2009) A new extension of FGM copulas. 70, 1-17.

Ismihan Bairamov, Samuel Kotz (2002) Dependence structure and symmetry of Huang-Kotz FGM distributions and their extensions. 56(1), 55-72.

I Bairamov, S Kotz, M Bekçi (2001) New generalized Farlie-Gumbel-Morgenstern distributions and concomitants of order statistics. 28(5), 521-536.

Wlodzimierz Bryc (2012) Normal distributions. 23-38.

Stamatis Cambanis (1977) Some properties and generalizations of multivariate Eyraud-Gumbel-Morgenstern distributions. 7(4), 551-559.

M Carles, C Cudras, Walter Daz (2012) Another generaization of the bivariate FGM distribution with two-dimensional extensions. 16(1).

Filippo Domma, Sabrina Giordano (2013) A copula-based approach to account for dependence in stress-strength models. 54(3), 807-826.

On Characterizing Generalized Cambanis Family of Bivariate Distributions

Published

2017-02-26

How to Cite

On Characterizing Generalized Cambanis Family of Bivariate Distributions. (2017). Global Journal of Science Frontier Research, 17(F1), 31-38. https://www.journalofscience.org/index.php/GJSFR/article/view/1947