A bivariate exponentiated Pareto distribution derived from Gaussian copula

Al-Urwi, Ashwag S.; Baharith, Lamya A.

International Journal of Advanced and Applied Sciences

Int. j. adv. appl. sci.

EISSN: 2313-3724

Print ISSN: 2313-626X

Volume 4, Issue 7 (July 2017), Pages: 66-73

Title: A bivariate exponentiated Pareto distribution derived from Gaussian copula

Author(s): Ashwag S. Al-Urwi, Lamya A. Baharith *

Affiliation(s):

Department of Statistics, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia

https://doi.org/10.21833/ijaas.2017.07.010

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Abstract:

The exponentiated Pareto distribution has been used quite effectively to model many lifetime data. In this paper, a new bivariate exponentiated Pareto distribution is introduced. The proposed bivariate distribution is derived from Gaussian copula with exponentiated Pareto distribution as marginals. Some properties of the bivariate exponentiated Pareto distribution can be obtained using the Gaussian copula property. Moreover, several methods of estimation are considered to estimate the unknown parameters of the proposed bivariate distribution. Numerical simulations are carried out to compare the performances of different estimators. Finally, one real data is analyzed and the results showed that the proposed bivariate distribution is useful for real life applications.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Keywords: Exponentiated Pareto distribution, Gaussian copula, Maximum likelihood estimators, Inference functions for margins estimators, Canonical maximum likelihood estimators, Bayesian estimators

Article History: Received 25 March 2017, Received in revised form 4 May 2017, Accepted 10 May 2017

Digital Object Identifier:

https://doi.org/10.21833/ijaas.2017.07.010

Citation:

Al-Urwi AS and Baharith LA (2017). A bivariate exponentiated Pareto distribution derived from Gaussian copula. International Journal of Advanced and Applied Sciences, 4(7): 66-73

http://www.science-gate.com/IJAAS/V4I7/Urwi.html

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