IDEAS home Printed from https://ideas.repec.org/a/spr/compst/v28y2013i4p1715-1724.html
   My bibliography  Save this article

Reducing bias of the maximum likelihood estimator of shape parameter for the gamma Distribution

Author

Listed:
  • Jin Zhang

Abstract

The gamma distribution is an important probability distribution in statistics. The maximum likelihood estimator (MLE) of its shape parameter is well known to be considerably biased, so that it has some modified versions. A new modified MLE of the shape for the gamma distribution is proposed in this paper, which is consistent, asymptotically normal and efficient. For finite-sample behavior, the new estimator improves the traditional MLE not only for reducing bias but also for gaining estimation efficiency significantly. In terms of estimation efficiency, it dominates other existing modified estimators. Copyright Springer-Verlag Berlin Heidelberg 2013

Suggested Citation

  • Jin Zhang, 2013. "Reducing bias of the maximum likelihood estimator of shape parameter for the gamma Distribution," Computational Statistics, Springer, vol. 28(4), pages 1715-1724, August.
  • Handle: RePEc:spr:compst:v:28:y:2013:i:4:p:1715-1724
    DOI: 10.1007/s00180-012-0375-4
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s00180-012-0375-4
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s00180-012-0375-4?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.

    References listed on IDEAS

    as
    1. T. Yanagimoto, 1988. "The conditional maximum likelihood estimator of the shape parameter in the gamma distribution," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 35(1), pages 161-175, December.
    2. Tea-Yuan Hwang & Ping-Huang Huang, 2002. "On New Moment Estimation of Parameters of the Gamma Distribution Using its Characterization," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 54(4), pages 840-847, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Takemi Yanagimoto & Kazuo Anraku, 1989. "Possible superiority of the conditional MLE over the unconditional MLE," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 41(2), pages 269-278, June.
    2. Takemi Yanagimoto, 1991. "Estimating a model through the conditional MLE," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 43(4), pages 735-746, December.
    3. Jung Min Lee & Chanjin Chung, 2024. "Estimating Market Power Exertion in the U.S. Beef Packing Industry: An Illustration of Data Aggregation Bias Using Simulated Data," Sustainability, MDPI, vol. 16(9), pages 1-19, April.
    4. Fujisawa, Hironori, 2003. "Asymptotic properties of conditional maximum likelihood estimator in a certain exponential model," Journal of Multivariate Analysis, Elsevier, vol. 86(1), pages 126-142, July.
    5. Zaigraev, A. & Podraza-Karakulska, A., 2014. "Maximum integrated likelihood estimator of the interest parameter when the nuisance parameter is location or scale," Statistics & Probability Letters, Elsevier, vol. 88(C), pages 99-106.

    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:spr:compst:v:28:y:2013:i:4:p:1715-1724. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.