[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/ulb/ulbeco/2013-13844.html
   My bibliography  Save this paper

On-line estimation of ARMA models using Fisher-scoring

Author

Listed:
  • Abdelhamid Ouakasse
  • Guy Melard
Abstract
Recursive estimation methods for time series models usually make use of recurrences for the vector of parameters, the modelerror and its derivatives with respect to the parameters, plus a recurrence for the Hessian of the model error. An alternativemethod is proposed in the case of an autoregressive-moving average model, where the Hessian is not updated but is replaced,at each time, by the inverse of the Fisher information matrix evaluated at the current parameter. The asymptotic properties,consistency and asymptotic normality, of the new estimator are obtained. Monte Carlo experiments indicate that the estimatesmay converge faster to the true values of the parameters than when the Hessian is updated. The paper is illustrated by anexample on forecasting the speed of wind.

Suggested Citation

  • Abdelhamid Ouakasse & Guy Melard, 2014. "On-line estimation of ARMA models using Fisher-scoring," ULB Institutional Repository 2013/13844, ULB -- Universite Libre de Bruxelles.
    • Handle: RePEc:ulb:ulbeco:2013/13844
    Note: SCOPUS: ar.j
    as

    Download full text from publisher

    File URL: https://dipot.ulb.ac.be/dspace/bitstream/2013/13844/3/21642583_2E2014_2E912572.pdf
    File Function: 21642583_2E2014_2E912572
    Download Restriction: no
    File URL: https://dipot.ulb.ac.be/dspace/bitstream/2013/13844/1/Ouakasse_Melard_2014.pdf
    File Function: Ouakasse_Melard_2014
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. André Klein & Guy Melard, 1989. "On algorithms for computing the covariance matrix of estimates in autoregresive-moving average processes," ULB Institutional Repository 2013/13710, ULB -- Universite Libre de Bruxelles.
    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. Vladim'ir Hol'y & Petra Tomanov'a, 2020. "Streaming Approach to Quadratic Covariation Estimation Using Financial Ultra-High-Frequency Data," Papers 2003.13062, arXiv.org, revised Dec 2021.

    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. André Klein & Guy Melard, 1994. "The information matrix of multiple input single output time series models," ULB Institutional Repository 2013/13732, ULB -- Universite Libre de Bruxelles.
    2. André Klein & Guy Mélard, 2004. "An algorithm for computing the asymptotic fisher information matrix for seasonal SISO models," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(5), pages 627-648, September.
    3. André Klein & Guy Melard & Toufik Zahaf, 1998. "Computation of the exact information matrix of Gaussian dynamic regression time series models," ULB Institutional Repository 2013/13738, ULB -- Universite Libre de Bruxelles.
    4. André Klein & Guy Melard, 1995. "Computation of the Fisher information matrix for time series models," ULB Institutional Repository 2013/13736, ULB -- Universite Libre de Bruxelles.
    5. Abdelhamid Ouakasse & Guy Melard, 2002. "Estimation en ligne pour le modèle ARMA," ULB Institutional Repository 2013/13826, ULB -- Universite Libre de Bruxelles.
    6. André Klein & Guy Melard, 2004. "An algorithm for computing the asymptotic Fisher information matrix for seasonal SISO models," ULB Institutional Repository 2013/13746, ULB -- Universite Libre de Bruxelles.

    More about this item

    Keywords

    ARMA processes; Fisher information matrix; Recursive estimation; Time series;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ulb:ulbeco:2013/13844. 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: Benoit Pauwels (email available below). General contact details of provider: https://edirc.repec.org/data/ecsulbe.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.