Open AccessA bivariate Pareto type I models
Author(s) -
Mervat Abd Elaal,
Hind Alzahrani
Publication year - 2017
Publication title -
international journal of advanced statistics and probability
Language(s) - English
Resource type - Journals
ISSN - 2307-9045
DOI - 10.14419/ijasp.v5i1.7638
Subject(s) - lomax distribution , copula (linguistics) , bivariate analysis , pareto distribution , pareto principle , monte carlo method , pareto interpolation , generalized pareto distribution , mathematics , econometrics , statistics , computer science , extreme value theory
In this paper two new bivariate Pareto Type I distributions are introduced. The first distribution is based on copula, and the second distribution is based on mixture of and copula. Maximum likelihood and Bayesian estimations are used to estimate the parameters of the proposed distribution. A Monte Carlo Simulation study is carried out to study the behavior of the proposed distributions. A real data set is analyzed to illustrate the performance and flexibility of the proposed distributions.