IDEAS home Printed from https://ideas.repec.org/a/bla/jtsera/v25y2004i4p443-448.html
   My bibliography  Save this article

On the closed form of the covariance matrix and its inverse of the causal ARMA process

Author

Listed:
  • John N. Haddad

Abstract

. Derivation of the theoretical autocovariance function of a causal autoregressive moving‐average process of order (p, q), ARMA(p, q), when q ≥ 1 is considered. A recursive relationship is established between the covariance matrices of an ARMA(p, q) process and its associated ARMA(p, q−1) process. The obtained recursion is shown to produce the inverse of the covariance matrix and its determinant. Moreover, the introduced method can be easily implemented in any programming environment.

Suggested Citation

  • John N. Haddad, 2004. "On the closed form of the covariance matrix and its inverse of the causal ARMA process," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(4), pages 443-448, July.
  • Handle: RePEc:bla:jtsera:v:25:y:2004:i:4:p:443-448
    DOI: 10.1111/j.1467-9892.2004.01454.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1467-9892.2004.01454.x
    Download Restriction: no

    File URL: https://libkey.io/10.1111/j.1467-9892.2004.01454.x?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
    ---><---

    References listed on IDEAS

    as
    1. Anderson, T. W. & Mentz, Raúl P., 1977. "The generalized variance of a stationary autoregressive process," Journal of Multivariate Analysis, Elsevier, vol. 7(4), pages 584-588, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Serge B. Provost & John N. Haddad, 2019. "A recursive approach for determining matrix inverses as applied to causal time series processes," METRON, Springer;Sapienza Università di Roma, vol. 77(1), pages 53-62, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Beach, Charles M. & Yeo, Stephen, 1979. "Exact Maximum Likelihood Estimation of Regression Equations with a General Stationary Auto-Regressive Disturbance," Queen's Institute for Economic Research Discussion Papers 275148, Queen's University - Department of Economics.

    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:bla:jtsera:v:25:y:2004:i:4:p:443-448. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc 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 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: http://www.blackwellpublishing.com/journal.asp?ref=0143-9782 .

    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.