IDEAS home Printed from
MyIDEAS: Log in (now much improved!) to save this article

Forecast covariances in the linear multiregression dynamic model

Listed author(s):
  • Catriona M. Queen

    (The Open University, Milton Keynes, UK)

  • Ben J. Wright

    (The Open University, Milton Keynes, UK)

  • Casper J. Albers

    (The Open University, Milton Keynes, UK)

Registered author(s):

    The linear multiregression dynamic model (LMDM) is a Bayesian dynamic model which preserves any conditional independence and causal structure across a multivariate time series. The conditional independence structure is used to model the multivariate series by separate (conditional) univariate dynamic linear models, where each series has contemporaneous variables as regressors in its model. Calculating the forecast covariance matrix (which is required for calculating forecast variances in the LMDM) is not always straightforward in its current formulation. In this paper we introduce a simple algebraic form for calculating LMDM forecast covariances. Calculation of the covariance between model regression components can also be useful and we shall present a simple algebraic method for calculating these component covariances. In the LMDM formulation, certain pairs of series are constrained to have zero forecast covariance. We shall also introduce a possible method to relax this restriction. Copyright © 2008 John Wiley & Sons, Ltd.

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL:
    File Function: Link to full text; subscription required
    Download Restriction: no

    Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

    Volume (Year): 27 (2008)
    Issue (Month): 2 ()
    Pages: 175-191

    in new window

    Handle: RePEc:jof:jforec:v:27:y:2008:i:2:p:175-191
    DOI: 10.1002/for.1050
    Contact details of provider: Web page:

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

    in new window

    1. Tebaldi, Claudia & West, Mike & Karr, Alan F, 2002. "Statistical Analyses of Freeway Traffic Flows," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(1), pages 39-68, January.
    2. Queen, Catriona M. & Smith, Jim Q. & James, David M., 1994. "Bayesian forecasts in markets with overlapping structures," International Journal of Forecasting, Elsevier, vol. 10(2), pages 209-233, September.
    Full references (including those not matched with items on IDEAS)

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:jof:jforec:v:27:y:2008:i:2:p:175-191. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing)

    or (Christopher F. Baum)

    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.

    If references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link to it, you can help with 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 profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.