IDEAS home Printed from https://ideas.repec.org/a/bla/jorssc/v44y1995i3p323-341.html
   My bibliography  Save this article

Applications of the Em Algorithm to the Analysis of Life Length Data

Author

Listed:
  • Jose Ramon G. Albert
  • Laurence A. Baxter

Abstract

The parameters of the life length distribution of a given component are to be estimated. The observations on which inference is to be based are field data which are incomplete in some fashion. Thus, for example, the reported life length may include a period of unknown duration during which the component is not in use, the life length distribution may be affected by an unobserved environmental factor or the component may be part of a larger system, and failure mode analysis reveals only the module containing the failed component, not its identity. It is shown how the EM algorithm can be used to calculate the maximum likelihood estimates of the parameters of interest in these instances. The methodology is applied to some data on the life lengths of electronic components used in the telecommunications industry, yielding values that are similar to those obtained from complete observations on comparable components.

Suggested Citation

  • Jose Ramon G. Albert & Laurence A. Baxter, 1995. "Applications of the Em Algorithm to the Analysis of Life Length Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 44(3), pages 323-341, September.
    • Handle: RePEc:bla:jorssc:v:44:y:1995:i:3:p:323-341
    DOI: 10.2307/2986040
    as

    Download full text from publisher

    File URL: https://doi.org/10.2307/2986040
    Download Restriction: no
    File URL: https://libkey.io/10.2307/2986040?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. K. Sultan & A. Al-Moisheer, 2013. "Updating a nonlinear discriminant function estimated from a mixture of two inverse Weibull distributions," Statistical Papers, Springer, vol. 54(1), pages 163-175, February.
    2. Karl Mosler & Christoph Scheicher, 2008. "Homogeneity testing in a Weibull mixture model," Statistical Papers, Springer, vol. 49(2), pages 315-332, April.
    3. Chanseok Park & Min Wang, 2024. "Parameter Estimation of Birnbaum-Saunders Distribution under Competing Risks Using the Quantile Variant of the Expectation-Maximization Algorithm," Mathematics, MDPI, vol. 12(11), pages 1-17, 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:bla:jorssc:v:44:y:1995:i:3:p:323-341. 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://edirc.repec.org/data/rssssea.html .

    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.