IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v49y2022i5p1277-1304.html
   My bibliography  Save this article

A review of tests for exponentiality with Monte Carlo comparisons

Author

Listed:
  • Everestus O. Ossai
  • Mbanefo S. Madukaife
  • Abimibola V. Oladugba

Abstract

In this paper, 91 different tests for exponentiality are reviewed. Some of the tests are universally consistent while others are against some special classes of life distributions. Power performances of 40 of these different tests for exponentiality of datasets are compared through extensive Monte Carlo simulations. The comparisons are conducted for different sample sizes of 10, 25, 50 and 100 for different groups of distributions according to the shape of their hazard functions at 5 percent level of significance. Also, the techniques are applied to two real-world datasets and a measure of power is employed for the comparison of the tests. The results show that some tests which are very good under one group of alternative distributions are not so under another group. Also, some tests maintained relatively high power over all the groups of alternative distributions studied while some others maintained poor power performances over all the groups of alternative distributions. Again, the result obtained from real-world datasets agree completely with those of the simulation studies.

Suggested Citation

  • Everestus O. Ossai & Mbanefo S. Madukaife & Abimibola V. Oladugba, 2022. "A review of tests for exponentiality with Monte Carlo comparisons," Journal of Applied Statistics, Taylor & Francis Journals, vol. 49(5), pages 1277-1304, April.
    • Handle: RePEc:taf:japsta:v:49:y:2022:i:5:p:1277-1304
    DOI: 10.1080/02664763.2020.1854202
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02664763.2020.1854202
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/02664763.2020.1854202?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.

    Citations

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


    Cited by:

    1. Naglaa A. Hassan & Mayar M. Said & Rasha Abd El-Wahab Attwa & Taha Radwan, 2024. "Applying the Laplace Transform Procedure, Testing Exponentiality against the NBRU mgf Class," Mathematics, MDPI, vol. 12(13), pages 1-14, 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:taf:japsta:v:49:y:2022:i:5:p:1277-1304. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    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.