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Zero-inflated Conway-Maxwell Poisson Distribution to Analyze Discrete Data

Author

Listed:
  • Sim Shin Zhu

    (Department of Mathematical and Actuarial Sciences, Universiti Tunku Abdul Rahman, Kajang43000, Selangor, Malaysia)

  • Gupta Ramesh C.

    (Department of Mathematics and Statistics, University of Maine, Orono, ME 04469-5752USA)

  • Ong Seng Huat

    (Institute of Mathematical Sciences, University of Malaya, Kuala Lumpur50603, Malaysia)

Abstract

In this paper, we study the zero-inflated Conway-Maxwell Poisson (ZICMP) distribution and develop a regression model. Score and likelihood ratio tests are also implemented for testing the inflation/deflation parameter. Simulation studies are carried out to examine the performance of these tests. A data example is presented to illustrate the concepts. In this example, the proposed model is compared to the well-known zero-inflated Poisson (ZIP) and the zero- inflated generalized Poisson (ZIGP) regression models. It is shown that the fit by ZICMP is comparable or better than these models.

Suggested Citation

  • Sim Shin Zhu & Gupta Ramesh C. & Ong Seng Huat, 2018. "Zero-inflated Conway-Maxwell Poisson Distribution to Analyze Discrete Data," The International Journal of Biostatistics, De Gruyter, vol. 14(1), pages 1-12, May.
    • Handle: RePEc:bpj:ijbist:v:14:y:2018:i:1:p:12:n:1
    DOI: 10.1515/ijb-2016-0070
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    References listed on IDEAS

    as
    1. Seth D. Guikema & Jeremy P. Goffelt, 2008. "A Flexible Count Data Regression Model for Risk Analysis," Risk Analysis, John Wiley & Sons, vol. 28(1), pages 213-223, February.
    2. Verbeke, Geert & Molenberghs, Geert, 2007. "What Can Go Wrong With the Score Test?," The American Statistician, American Statistical Association, vol. 61, pages 289-290, November.
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