IDEAS home Printed from https://ideas.repec.org/a/eee/spapps/v73y1998i2p151-172.html
   My bibliography  Save this article

On the recursive parameter estimation in the general discrete time statistical model

Author

Listed:
  • Sharia, Teo

Abstract

The consistency and asymptotic linearity of recursive maximum likelihood estimator is proved under some regularity and ergodicity assumptions on the logarithmic derivative of a transition density for a general statistical model. © 1998 Elsevier Science B.V.

Suggested Citation

  • Sharia, Teo, 1998. "On the recursive parameter estimation in the general discrete time statistical model," Stochastic Processes and their Applications, Elsevier, vol. 73(2), pages 151-172, March.
    • Handle: RePEc:eee:spapps:v:73:y:1998:i:2:p:151-172
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304-4149(97)00098-7
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Englund, Jan-Eric & Holst, Ulla & Ruppert, David, 1989. "Recursive estimators for stationary, strong mixing processes--a representation theorem and asymptotic distributions," Stochastic Processes and their Applications, Elsevier, vol. 31(2), pages 203-222, April.
    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. Abdelhamid Ouakasse & Guy Mélard, 2017. "A New Recursive Estimation Method for Single Input Single Output Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(3), pages 417-457, May.
    2. Teo Sharia, 2014. "Truncated stochastic approximation with moving bounds: convergence," Statistical Inference for Stochastic Processes, Springer, vol. 17(2), pages 163-179, July.
    3. Teo Sharia, 2008. "Recursive parameter estimation: convergence," Statistical Inference for Stochastic Processes, Springer, vol. 11(2), pages 157-175, June.

    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. Teo Sharia, 2008. "Recursive parameter estimation: convergence," Statistical Inference for Stochastic Processes, Springer, vol. 11(2), pages 157-175, June.
    2. Teo Sharia, 2014. "Truncated stochastic approximation with moving bounds: convergence," Statistical Inference for Stochastic Processes, Springer, vol. 17(2), pages 163-179, July.

    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:eee:spapps:v:73:y:1998:i:2:p:151-172. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/505572/description#description .

    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.