IDEAS home Printed from https://ideas.repec.org/a/taf/lstaxx/v52y2023i24p8636-8657.html
   My bibliography  Save this article

High-dimensional Edgeworth expansion of LR statistic for testing block circular symmetry covariance structure and its errors

Author

Listed:
  • Gaoming Sun
  • Junshan Xie

Abstract

The paper considers the asymptotical expansion on the likelihood ratio (LR) statistic for testing the block circular symmetric (BCS) covariance structure of a multivariate Gaussian population. When the number of blocks u and the dimension of each block p satisfy p=p(n)→∞ and pu/(n−1)→c∈(0,1) as the sample size n→∞, the Edgeworth expansion of the null distribution of the LR test statistic and its uniform Berry-Esseen type bound are established. Some numerical simulations indicate that the proposed approximation is more accurate than the traditional Chi-square approximate method on dealing with the high-dimensional test.

Suggested Citation

  • Gaoming Sun & Junshan Xie, 2023. "High-dimensional Edgeworth expansion of LR statistic for testing block circular symmetry covariance structure and its errors," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 52(24), pages 8636-8657, December.
    • Handle: RePEc:taf:lstaxx:v:52:y:2023:i:24:p:8636-8657
    DOI: 10.1080/03610926.2022.2067877
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03610926.2022.2067877
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/03610926.2022.2067877?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.

    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:lstaxx:v:52:y:2023:i:24:p:8636-8657. 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/lsta .

    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.