IDEAS home Printed from https://ideas.repec.org/a/cup/etheor/v41y2025i2p391-420_5.html
   My bibliography  Save this article

Performance Of Empirical Risk Minimization For Linear Regression With Dependent Data

Author

Listed:
  • Brownlees, Christian
  • Guđmundsson, Guđmundur Stefán

Abstract

This paper establishes bounds on the performance of empirical risk minimization for large-dimensional linear regression. We generalize existing results by allowing the data to be dependent and heavy-tailed. The analysis covers both the cases of identically and heterogeneously distributed observations. Our analysis is nonparametric in the sense that the relationship between the regressand and the regressors is not specified. The main results of this paper show that the empirical risk minimizer achieves the optimal performance (up to a logarithmic factor) in a dependent data setting.

Suggested Citation

  • Brownlees, Christian & Guđmundsson, Guđmundur Stefán, 2025. "Performance Of Empirical Risk Minimization For Linear Regression With Dependent Data," Econometric Theory, Cambridge University Press, vol. 41(2), pages 391-420, April.
  • Handle: RePEc:cup:etheor:v:41:y:2025:i:2:p:391-420_5
    as

    Download full text from publisher

    File URL: https://www.cambridge.org/core/product/identifier/S0266466623000348/type/journal_article
    File Function: link to article abstract page
    Download Restriction: no
    ---><---

    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:cup:etheor:v:41:y:2025:i:2:p:391-420_5. 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: Kirk Stebbing (email available below). General contact details of provider: https://www.cambridge.org/ect .

    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.