IDEAS home Printed from https://ideas.repec.org/a/oup/biomet/v98y2011i4p1007-1014.html
   My bibliography  Save this article

Generalized linear time series regression

Author

Listed:
  • Enno Mammen
  • Jens Perch Nielsen
  • Bernd Fitzenberger

Abstract

We consider a cross-section model that contains an individual component, a deterministic time trend and an unobserved latent common time series component. We show the following oracle property: the parameters of the latent time series and the parameters of the deterministic time trend can be estimated with the same asymptotic accuracy as if the parameters of the individual component were known. We consider this model in two settings: least squares fits of linear specifications of the individual component and the parameters of the deterministic time trend and, more generally, quasilikelihood estimation in a generalized linear time series model. Copyright 2011, Oxford University Press.

Suggested Citation

  • Enno Mammen & Jens Perch Nielsen & Bernd Fitzenberger, 2011. "Generalized linear time series regression," Biometrika, Biometrika Trust, vol. 98(4), pages 1007-1014.
    • Handle: RePEc:oup:biomet:v:98:y:2011:i:4:p:1007-1014
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/biomet/asr044
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    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:oup:biomet:v:98:y:2011:i:4:p:1007-1014. 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: Oxford University Press (email available below). General contact details of provider: https://academic.oup.com/biomet .

    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.