IDEAS home Printed from https://ideas.repec.org/a/oup/biomet/v98y2011i3p755-759.html
   My bibliography  Save this article

Multinomial logit bias reduction via the Poisson log-linear model

Author

Listed:
  • Ioannis Kosmidis
  • David Firth

Abstract

For the parameters of a multinomial logistic regression, it is shown how to obtain the bias-reducing penalized maximum likelihood estimator by using the equivalent Poisson log-linear model. The calculation needed is not simply an application of the Jeffreys prior penalty to the Poisson model. The development allows a simple and computationally efficient implementation of the reduced-bias estimator, using standard software for generalized linear models. Copyright 2011, Oxford University Press.

Suggested Citation

  • Ioannis Kosmidis & David Firth, 2011. "Multinomial logit bias reduction via the Poisson log-linear model," Biometrika, Biometrika Trust, vol. 98(3), pages 755-759.
    • Handle: RePEc:oup:biomet:v:98:y:2011:i:3:p:755-759
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/biomet/asr026
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    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. Iranitalab, Amirfarrokh & Khattak, Aemal & Thompson, Eric, 2019. "Statistical modeling of types and consequences of rail-based crude oil release incidents in the United States," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 232-239.
    2. Xing Ju Lee & Christopher C. Drovandi & Anthony N. Pettitt, 2015. "Model choice problems using approximate Bayesian computation with applications to pathogen transmission data sets," Biometrics, The International Biometric Society, vol. 71(1), pages 198-207, March.
    3. Di Caterina, Claudia & Kosmidis, Ioannis, 2019. "Location-adjusted Wald statistics for scalar parameters," Computational Statistics & Data Analysis, Elsevier, vol. 138(C), pages 126-142.
    4. Tran, Yen & Yamamoto, Toshiyuki & Sato, Hitomi & Miwa, Tomio & Morikawa, Takayuki, 2020. "The analysis of influences of attitudes on mode choice under highly unbalanced mode share patterns," Journal of choice modelling, Elsevier, vol. 36(C).

    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:oup:biomet:v:98:y:2011:i:3:p:755-759. 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: Oxford University Press (email available below). General contact details of provider: https://academic.oup.com/biomet .

    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.