Bivariate Conway-Maxwell Poisson Distributions with Given Marginals and Correlation

被引：5

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.

引用

页数：19

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