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Document Details
Document Type
:
Thesis
Document Title
:
Bivariate Exponentiated Pareto Distributions Based on Mixture and Copula
توزيعات باريتو الأسي ثنائية المتغيرات على أساس الرابطة والخليط
Subject
:
Faculty of Sciences
Document Language
:
Arabic
Abstract
:
The exponentiated Pareto distribution has been used quite effectively to model many lifetime data. Constructing and studying bivariate probability distributions are of great interests of many statisticians. A popular and flexible way to derive different bivariate lifetime distributions using copula functions. In this Thesis, two new bivariate exponentiated Pareto distributions are introduced. The first proposed bivariate distribution is constructed based on Gaussian copula with exponentiated Pareto distribution as marginals and the second bivariate distribution is constructed based on M mixture representation and Gaussian copula. Several properties of the proposed bivariate distributions can be obtained using the Gaussian copula property. Different methods of estimation of the unknown parameters of proposed bivariate distributions are considered. The Markov Chain Monte Carlo technique has been used to compute the Bayesian estimates based on squared error loss function. Moreover, Monte Carlo simulation study is used to investigate and compare the different estimates for different sample sizes and for different values of the Gaussian copula parameter. Simulation results showed that Bayesian method in most cases provides more accurate estimates compared to other methods. In addition, the results based on mean square error showed that second bivariate distribution provides more accurate estimates compared to the first bivariate distribution. Finally, real data set is analyzed and the results showed that the proposed distributions gave more satisfactory performance compared to some other very well-known distributions.
Supervisor
:
Dr. Lamya Baharith
Thesis Type
:
Master Thesis
Publishing Year
:
1438 AH
2016 AD
Co-Supervisor
:
Dr. Mervat Khalifa
Added Date
:
Wednesday, January 11, 2017
Researchers
Researcher Name (Arabic)
Researcher Name (English)
Researcher Type
Dr Grade
Email
أشواق سليم العروي
ALerwi, Ashwag Saleem
Researcher
Master
Files
File Name
Type
Description
39571.pdf
pdf
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