IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-1-4757-3629-8_5.html
   My bibliography  Save this book chapter

Empirical Predictors

In: Predictions in Time Series Using Regression Models

Author

Listed:
  • František Štulajter

    (Comenius University, Department of Statistics, FMFI UK)

Abstract

In the preceding chapter we considered different predictors in models at which the mean value of X(.) was unknown and modeled by some regression models. The main assumption under which these predictors were derived was that the covariance characteristics of the models were known. This is a rather strong assumption which is fulfilled only rarely in practical problems when we have usually only time series data x consisting of a finite realization of an observation X of X(.) and nothing more. Thus it is necessary to model not only the mean value m(.) of X(.), but also the covariance function R(.,.) of X(.). The main models for covariance functions were considered in the preceding chapter and also the methods, giving the estimators, such as the DOOLSE, the DOWELSE, and the MLE, of parameters of covariance functions were derived.

Suggested Citation

  • František Štulajter, 2002. "Empirical Predictors," Springer Books, in: Predictions in Time Series Using Regression Models, chapter 5, pages 197-222, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4757-3629-8_5
    DOI: 10.1007/978-1-4757-3629-8_5
    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
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:spr:sprchp:978-1-4757-3629-8_5. 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: 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.