Analysis of discrete data by Conway–Maxwell Poisson distribution

Ramesh C. Gupta; S. Z. Sim; S. H. Ong

doi:10.1007/s10182-014-0226-4

Analysis of discrete data by Conway–Maxwell Poisson distribution

Ramesh C. Gupta, S. Z. Sim, S. H. Ong

Research output: Contribution to journal › Article › Research › peer-review

26 Citations (Scopus)

Abstract

In this paper, we further study the Conway–Maxwell Poisson distribution having one more parameter than the Poisson distribution and compare it with the Poisson distribution with respect to some stochastic orderings used in reliability theory. Likelihood ratio test and the score test are developed to test the importance of this additional parameter. Simulation studies are carried out to examine the performance of the two tests. Two examples are presented, one showing overdispersion and the other showing underdispersion, to illustrate the procedure. It is shown that the COM-Poisson model fits better than the generalized Poisson distribution.

Original language	English
Pages (from-to)	327-343
Number of pages	17
Journal	AStA Advances in Statistical Analysis
Volume	98
Issue number	4
DOIs	https://doi.org/10.1007/s10182-014-0226-4
Publication status	Published - Jan 2014
Externally published	Yes

Keywords

Failure rate
Overdispersion
Score test
Stochastic comparisons
Underdispersion

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10.1007/s10182-014-0226-4

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abstract = "In this paper, we further study the Conway–Maxwell Poisson distribution having one more parameter than the Poisson distribution and compare it with the Poisson distribution with respect to some stochastic orderings used in reliability theory. Likelihood ratio test and the score test are developed to test the importance of this additional parameter. Simulation studies are carried out to examine the performance of the two tests. Two examples are presented, one showing overdispersion and the other showing underdispersion, to illustrate the procedure. It is shown that the COM-Poisson model fits better than the generalized Poisson distribution.",

keywords = "Failure rate, Overdispersion, Score test, Stochastic comparisons, Underdispersion",

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AU - Sim, S. Z.

AU - Ong, S. H.

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N2 - In this paper, we further study the Conway–Maxwell Poisson distribution having one more parameter than the Poisson distribution and compare it with the Poisson distribution with respect to some stochastic orderings used in reliability theory. Likelihood ratio test and the score test are developed to test the importance of this additional parameter. Simulation studies are carried out to examine the performance of the two tests. Two examples are presented, one showing overdispersion and the other showing underdispersion, to illustrate the procedure. It is shown that the COM-Poisson model fits better than the generalized Poisson distribution.

AB - In this paper, we further study the Conway–Maxwell Poisson distribution having one more parameter than the Poisson distribution and compare it with the Poisson distribution with respect to some stochastic orderings used in reliability theory. Likelihood ratio test and the score test are developed to test the importance of this additional parameter. Simulation studies are carried out to examine the performance of the two tests. Two examples are presented, one showing overdispersion and the other showing underdispersion, to illustrate the procedure. It is shown that the COM-Poisson model fits better than the generalized Poisson distribution.

KW - Failure rate

KW - Overdispersion

KW - Score test

KW - Stochastic comparisons

KW - Underdispersion

UR - https://www.scopus.com/pages/publications/84907592735

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JO - AStA Advances in Statistical Analysis

JF - AStA Advances in Statistical Analysis

IS - 4

ER -

Analysis of discrete data by Conway–Maxwell Poisson distribution

Abstract

Keywords

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