IDEAS home Printed from https://ideas.repec.org/a/wly/apsmbi/v23y2007i5p373-383.html
   My bibliography  Save this article

Improved maximum‐likelihood estimation for the common shape parameter of several Weibull populations

Author

Listed:
  • Zhenlin Yang
  • Dennis K. J. Lin

Abstract

The biasness problem of the maximum‐likelihood estimate (MLE) of the common shape parameter of several Weibull populations is examined in detail. A modified MLE (MMLE) approach is proposed. In the case of complete and Type II censored data, the bias of the MLE can be substantial. This is noticeable even when the sample size is large. Such a bias increases rapidly as the degree of censorship increases and as more populations are involved. The proposed MMLE, however, is nearly unbiased and much more efficient than the MLE, irrespective of the degree of censorship, the sample sizes, and the number of populations involved. Copyright © 2007 John Wiley & Sons, Ltd.

Suggested Citation

  • Zhenlin Yang & Dennis K. J. Lin, 2007. "Improved maximum‐likelihood estimation for the common shape parameter of several Weibull populations," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 23(5), pages 373-383, September.
    • Handle: RePEc:wly:apsmbi:v:23:y:2007:i:5:p:373-383
    DOI: 10.1002/asmb.678
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/asmb.678
    Download Restriction: no
    File URL: https://libkey.io/10.1002/asmb.678?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
    ---><---

    Citations

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


    Cited by:

    1. Starling, James K. & Mastrangelo, Christina & Choe, Youngjun, 2021. "Improving Weibull distribution estimation for generalized Type I censored data using modified SMOTE," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    2. Lemonte, Artur J. & Cordeiro, Gauss M., 2009. "Birnbaum-Saunders nonlinear regression models," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4441-4452, October.
    3. Pushkal Kumar & Manas Ranjan Tripathy & Somesh Kumar, 2023. "Bayesian estimation and classification for two logistic populations with a common location," Computational Statistics, Springer, vol. 38(2), pages 711-748, June.

    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:wly:apsmbi:v:23:y:2007:i:5:p:373-383. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1002/(ISSN)1526-4025 .

    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.