IDEAS home Printed from https://ideas.repec.org/a/taf/lstaxx/v46y2017i1p165-175.html
   My bibliography  Save this article

Some probability inequalities of least-squares estimator in non linear regression model with strong mixing errors

Author

Listed:
  • Wenzhi Yang
  • Yiwei Wang
  • Shuhe Hu

Abstract

In this paper, we investigate the non linear regression model when the errors are strong mixing. Some probabilityinequalities of the least-squares estimator are presented by using moment information of errors. Meanwhile, for some p > 2, two examples are given when errors satisfy supn≥1E|ξn|p=∞$\sup \nolimits _{n\ge 1}E|\xi _n|^p=\infty$ and supn≥1E|ξn|p

Suggested Citation

  • Wenzhi Yang & Yiwei Wang & Shuhe Hu, 2017. "Some probability inequalities of least-squares estimator in non linear regression model with strong mixing errors," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(1), pages 165-175, January.
    • Handle: RePEc:taf:lstaxx:v:46:y:2017:i:1:p:165-175
    DOI: 10.1080/03610926.2014.988261
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03610926.2014.988261
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/03610926.2014.988261?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. Gao, Min & Yang, Wenzhi & Wu, Shipeng & Yu, Wei, 2022. "Asymptotic normality of residual density estimator in stationary and explosive autoregressive models," Computational Statistics & Data Analysis, Elsevier, vol. 175(C).

    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:46:y:2017:i:1:p:165-175. 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.