IDEAS home Printed from https://ideas.repec.org/p/eca/wpaper/2013-304276.html
   My bibliography  Save this paper

Asymptotic Properties of Conditional Least-squares Estimators for Array Time Series

Author

Listed:
  • Rajae Azrak
  • Guy Melard

Abstract

The paper provides a kind of Klimko-Nelson theorems alternative in the case of conditional least-squares and M-estimators for array time series, when the assumptions of almost sure convergence cannot be established. We do not assume stationarity nor even local stationarity. In addition, we provide sufficient conditions for two of the assumptions and two theorems for the evaluation of the information matrix in array time series. In addition to time dependent models, illustrations to a threshold model and to a count data model are given.

Suggested Citation

  • Rajae Azrak & Guy Melard, 2020. "Asymptotic Properties of Conditional Least-squares Estimators for Array Time Series," Working Papers ECARES 2020-12, ULB -- Universite Libre de Bruxelles.
    • Handle: RePEc:eca:wpaper:2013/304276
    as

    Download full text from publisher

    File URL: https://dipot.ulb.ac.be/dspace/bitstream/2013/304276/3/2020-12-AZRAK_MELARD-asymptotic.pdf
    File Function: Full text for the whole work, or for a work part
    Download Restriction: no
    ---><---

    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:eca:wpaper:2013/304276. 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: Benoit Pauwels (email available below). General contact details of provider: https://edirc.repec.org/data/arulbbe.html .

    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.