IDEAS home Printed from https://ideas.repec.org/a/wly/apsmbi/v22y2006i1p17-39.html
   My bibliography  Save this article

Automatic detection and identification of shocks in Gaussian state‐space models: a Bayesian approach

Author

Listed:
  • Manuel Salvador
  • Pilar Gargallo

Abstract

An automatic monitoring and intervention algorithm that permits the supervision of very general aspects in an univariate linear Gaussian state–space model is proposed. The algorithm makes use of a model comparison and selection approach within a Bayesian framework. In addition, this algorithm incorporates the possibility of eliminating earlier interventions when subsequent evidence against them comes to light. Finally, the procedure is illustrated with two empirical examples taken from the literature. Copyright © 2005 John Wiley & Sons, Ltd.

Suggested Citation

  • Manuel Salvador & Pilar Gargallo, 2006. "Automatic detection and identification of shocks in Gaussian state‐space models: a Bayesian approach," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 22(1), pages 17-39, January.
    • Handle: RePEc:wly:apsmbi:v:22:y:2006:i:1:p:17-39
    DOI: 10.1002/asmb.608
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/asmb.608
    Download Restriction: no
    File URL: https://libkey.io/10.1002/asmb.608?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
    ---><---

    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:wly:apsmbi:v:22:y:2006:i:1:p:17-39. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1002/(ISSN)1526-4025 .

    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.