IDEAS home Printed from https://ideas.repec.org/a/bot/rivsta/v78y2018i2p183-193.html
   My bibliography  Save this article

Methods of Estimating the Parameters of the Quasi Lindley Distribution

Author

Listed:
  • Festus Opone

    (University of Benin - Nigeria)

  • Nosakhare Ekhosuehi

    (University of Benin - Nigeria)

Abstract

In this paper, we review the quasi Lindley distribution and established its quantile function. A simulation study is conducted to examine the bias and mean square error of the parameter estimates of the distribution through the method of moment estimation and the maximum likelihood estimation. Result obtained shows that the method of maximum likelihood is a better choice of estimation method for the parameters of the quasi Lindley distribution. Finally, an applicability of the quasi Lindley disttribution to a waiting time data set suggests that the distribution demonstrates superiority over the power Lindley distribution, Sushila distribution and the classical oneparameter Lindley distribution in terms of the maximized loglikelihood, the Akaike information criterion, the Kolmogorov-Smirnov and Cramér von Mises test statistic.

Suggested Citation

  • Festus Opone & Nosakhare Ekhosuehi, 2018. "Methods of Estimating the Parameters of the Quasi Lindley Distribution," Statistica, Department of Statistics, University of Bologna, vol. 78(2), pages 183-193.
    • Handle: RePEc:bot:rivsta:v:78:y:2018:i:2:p:183-193
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:bot:rivsta:v:78:y:2018:i:2:p:183-193. 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: Giovanna Galatà (email available below). General contact details of provider: https://edirc.repec.org/data/dsbolit.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.