IDEAS home Printed from https://ideas.repec.org/a/taf/lstaxx/v45y2016i14p4117-4135.html
   My bibliography  Save this article

A COM-Poisson-type generalization of the negative binomial distribution

Author

Listed:
  • S. Chakraborty
  • S. H. Ong

Abstract

This paper introduces a generalization of the negative binomial (NB) distribution in analogy with the COM-Poisson distribution. Many well-known distributions are particular and limiting distributions. The proposed distribution belongs to the modified power series, generalized hypergeometric and exponential families, and also arises as weighted NB and COM-Poisson distributions. Probability and moment recurrence formulae, and probabilistic and reliability properties have been derived. With the flexibility to model under-, equi- and over-dispersion, and its various interesting properties, this NB generalization will be a useful model for count data. An application to empirical modeling is illustrated with a real data set.

Suggested Citation

  • S. Chakraborty & S. H. Ong, 2016. "A COM-Poisson-type generalization of the negative binomial distribution," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 45(14), pages 4117-4135, July.
    • Handle: RePEc:taf:lstaxx:v:45:y:2016:i:14:p:4117-4135
    DOI: 10.1080/03610926.2014.917184
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03610926.2014.917184
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/03610926.2014.917184?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sudip Roy & Ram C. Tripathi & Narayanaswamy Balakrishnan, 2023. "A Conway–Maxwell–Poisson Type Generalization of Hypergeometric Distribution," Mathematics, MDPI, vol. 11(3), pages 1-15, February.
    2. Seng Huat Ong & Shin Zhu Sim & Shuangzhe Liu & Hari M. Srivastava, 2023. "A Family of Finite Mixture Distributions for Modelling Dispersion in Count Data," Stats, MDPI, vol. 6(3), pages 1-14, September.
    3. Morris, Darcy Steeg & Raim, Andrew M. & Sellers, Kimberly F., 2020. "A Conway–Maxwell-multinomial distribution for flexible modeling of clustered categorical data," Journal of Multivariate Analysis, Elsevier, vol. 179(C).
    4. Boris Forthmann & Philipp Doebler, 2021. "Reliability of researcher capacity estimates and count data dispersion: a comparison of Poisson, negative binomial, and Conway-Maxwell-Poisson models," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3337-3354, April.
    5. Subrata Chakraborty & S. H. Ong, 2017. "Mittag - Leffler function distribution - a new generalization of hyper-Poisson distribution," Journal of Statistical Distributions and Applications, Springer, vol. 4(1), pages 1-17, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:lstaxx:v:45:y:2016:i:14:p:4117-4135. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/lsta .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.