Bivariate Conway-Maxwell Poisson Distributions with Given Marginals and Correlation

被引：7
|
作者：
Ong, Seng Huat [1 ]
Gupta, Ramesh C. [2 ]
Ma, Tiefeng [3 ]
Sim, Shin Zhu [4 ]
机构：
[1] UCSI Univ, Dept Actuarial Sci & Appl Stat, Kuala Lumpur 56000, Malaysia
[2] Univ Maine, Dept Math & Stat, Orono, ME 04469 USA
[3] Southwestern Univ Finance & Econ, Sch Stat, Chengdu 611130, Sichuan, Peoples R China
[4] Univ Tunku Abdul Rahman, Dept Math & Actuarial Sci, Kajang 43000, Selangor, Malaysia
来源：
JOURNAL OF STATISTICAL THEORY AND PRACTICE | 2020年 / 15卷 / 01期
关键词：
Conway-Maxwell Poisson; Negative and positive correlation; Positive likelihood ratio dependence; Test of independence; Likelihood ratio test; Score test; Weighted distribution; CORRELATION CURVES; SARMANOV FAMILY; DISCRETE-DATA; ASSOCIATION; DEPENDENCE;
D O I：
10.1007/s42519-020-00141-4
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
The Conway-Maxwell Poisson (CMP) distribution is a popular model for analyzing data that exhibit under or over dispersion. In this article, we construct bivariate CMP distributions with given marginal CMP distributions and range of correlation coefficient over (- 1, 1) based on the Sarmanov family of bivariate distributions. One of the constructions is based on a general method for weighted distributions. The dependence property is examined. Parameter estimation, tests of independence and adequacy of model and a Monte Carlo power study are discussed. A real data set is used to exemplify its usefulness with comparison to other bivariate models.
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页数：19
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