IDEAS home Printed from https://ideas.repec.org/a/hin/jnljps/5902839.html
   My bibliography  Save this article

Hybrid Clayton-Frank Convolution-Based Bivariate Archimedean Copula

Author

Listed:
  • Maxwell Akwasi Boateng
  • Akoto Yaw Omari-Sasu
  • Richard Kodzo Avuglah
  • Nana Kena Frempong

Abstract

This study exploits the closure property of the converse convolution operator to come up with a hybrid Clayton-Frank Archimedean copula for two random variables. Pairs of random variables were generated and the upper tail observation of the cumulative distribution function (CDF) was used to assess the right skew behavior of the proposed model. Various values of the converse convolution operator were used to see their effect on the proposed model. The simulation covered lengths , and 6. The proposed model was compared with about 40 other bivariate copulas (both Archimedean and elliptical). The proposed model had parameters that spanned the entire real line, thus removing restrictions on the parameters. The parameters theta and omega were varied for a selected interval and the hybrid Clayton-Frank model was, in most cases, found to outperform the other copulas under consideration.

Suggested Citation

  • Maxwell Akwasi Boateng & Akoto Yaw Omari-Sasu & Richard Kodzo Avuglah & Nana Kena Frempong, 2018. "Hybrid Clayton-Frank Convolution-Based Bivariate Archimedean Copula," Journal of Probability and Statistics, Hindawi, vol. 2018, pages 1-9, March.
    • Handle: RePEc:hin:jnljps:5902839
    DOI: 10.1155/2018/5902839
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/JPS/2018/5902839.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/JPS/2018/5902839.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2018/5902839?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
    ---><---

    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:hin:jnljps:5902839. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    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.