IDEAS home Printed from https://ideas.repec.org/a/spr/sistpr/v2y1999i1p57-68.html
   My bibliography  Save this article

Asymptotic Properties of the Maximum Likelihood Estimator for Stochastic PDEs Disturbed by Small Noise

Author

Listed:
  • M. Huebner

Abstract

No abstract is available for this item.

Suggested Citation

  • M. Huebner, 1999. "Asymptotic Properties of the Maximum Likelihood Estimator for Stochastic PDEs Disturbed by Small Noise," Statistical Inference for Stochastic Processes, Springer, vol. 2(1), pages 57-68, January.
  • Handle: RePEc:spr:sistpr:v:2:y:1999:i:1:p:57-68
    DOI: 10.1023/A:1009990504925
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1023/A:1009990504925
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1023/A:1009990504925?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
    ---><---

    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. Loges, Wilfried, 1984. "Girsanov's theorem in Hilbert space and an application to the statistics of Hilbert space- valued stochastic differential equations," Stochastic Processes and their Applications, Elsevier, vol. 17(2), pages 243-263, July.
    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. Igor Cialenco, 2018. "Statistical inference for SPDEs: an overview," Statistical Inference for Stochastic Processes, Springer, vol. 21(2), pages 309-329, July.

    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. Kim, Yoon Tae, 1999. "Parameter estimation in infinite-dimensional stochastic differential equations," Statistics & Probability Letters, Elsevier, vol. 45(3), pages 195-204, November.
    2. Igor Cialenco, 2018. "Statistical inference for SPDEs: an overview," Statistical Inference for Stochastic Processes, Springer, vol. 21(2), pages 309-329, July.
    3. Kazimierczyk, Piotr, 1992. "Explicit correction formulae for parametric identification of stochastic differential systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 34(5), pages 433-450.

    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:spr:sistpr:v:2:y:1999:i:1:p:57-68. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.