IDEAS home Printed from https://ideas.repec.org/a/gam/jrisks/v11y2023i10p169-d1250041.html
   My bibliography  Save this article

An Exponentiality Test of Fit Based on a Tail Characterization against Heavy and Light-Tailed Alternatives

Author

Listed:
  • Alex Karagrigoriou

    (Lab of Statistics and Data Analysis, University of the Aegean, 83200 Karlovasi, Greece
    These authors contributed equally to this work.)

  • Ioannis Mavrogiannis

    (M2P2, Centrale Méditerranée, 13013 Marseille, France
    These authors contributed equally to this work.)

  • Georgia Papasotiriou

    (Department of Mathematics, National Technical University of Athens, 15780 Athens, Greece
    These authors contributed equally to this work.)

  • Ilia Vonta

    (Department of Mathematics, National Technical University of Athens, 15780 Athens, Greece
    These authors contributed equally to this work.)

Abstract

Log-concavity and log-convexity play a key role in various scientific fields, especially in those where the distinction between exponential and non-exponential distributions is necessary for inferential purposes. In the present study, we introduce a testing procedure for the tail part of a distribution which can be used for the distinction between exponential and non-exponential distributions. The conspiracy and catastrophe principles are initially used to establish a characterization of (the tail part of) the exponential distribution, which is one of the main contributions of the present work, leading the way for the construction of the new test of fit. The proposed test and its implementation are thoroughly discussed, and an extended simulation study has been undertaken to clarify issues related to its implementation and explore the extent of its capabilities. A real data case is also investigated.

Suggested Citation

  • Alex Karagrigoriou & Ioannis Mavrogiannis & Georgia Papasotiriou & Ilia Vonta, 2023. "An Exponentiality Test of Fit Based on a Tail Characterization against Heavy and Light-Tailed Alternatives," Risks, MDPI, vol. 11(10), pages 1-22, September.
    • Handle: RePEc:gam:jrisks:v:11:y:2023:i:10:p:169-:d:1250041
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-9091/11/10/169/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-9091/11/10/169/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Moosup Kim & Sangyeol Lee, 2016. "On the tail index inference for heavy-tailed GARCH-type innovations," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 68(2), pages 237-267, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yongqing Guo & Xiaoyuan Wang & Qing Xu & Feifei Liu & Yaqi Liu & Yuanyuan Xia, 2019. "Change-Point Analysis of Eye Movement Characteristics for Female Drivers in Anxiety," IJERPH, MDPI, vol. 16(7), pages 1-17, April.
    2. Moosup Kim & Sangyeol Lee, 2019. "Test for tail index constancy of GARCH innovations based on conditional volatility," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(4), pages 947-981, August.

    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:gam:jrisks:v:11:y:2023:i:10:p:169-:d:1250041. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.