IDEAS home Printed from https://ideas.repec.org/p/sce/scecf9/311.html
   My bibliography  Save this paper

Fast Estimation of Parameters in State Space Models

Author

Listed:
  • Siem Jan Koopman

    (CentER, Tilburg)

Abstract

This paper discusses computationally efficient methods for exact maximum-likelihood estimation of parameters in state-space models. The proposed strategy is based on direct maximisation of the likelihood function, and it can be applied to a wide range of practical univariate and multivariate models. Almost no extra computing is required to deal with diffuse initial conditions. Practical problems, such as missing values and non-equal spacing, are dealt with in a straightforward fashion. Applications are given for structural time-series models, nonparametric splines, and models for heteroskedasticity.

Suggested Citation

  • Siem Jan Koopman, 1999. "Fast Estimation of Parameters in State Space Models," Computing in Economics and Finance 1999 311, Society for Computational Economics.
    • Handle: RePEc:sce:scecf9:311
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:sce:scecf9:311. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Christopher F. Baum (email available below). General contact details of provider: https://edirc.repec.org/data/sceeeea.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.