IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-1-4612-2856-1_103.html
   My bibliography  Save this book chapter

Estimating Optimal Transformations for Correlation and Coherence

In: Computing Science and Statistics

Author

Listed:
  • Martin R. Young

    (University of Michigan)

Abstract

Coherency is a frequency domain measure of the linear association between two time series X(t) and Y(t). Since association between time series can in general be nonlinear, it may be useful to nonlinearly transform the time series prior to the coherency analysis. A broad class of nonlinear transformations of time series is proposed, and a procedure is described for estimating the transformations in this class which maximize the coherency between the transformed series. An efficient and numerically robust procedure for computing these optimal transformations is described, and the connection between this technique and Breiman and Friedman’s (1985) ACE technique for estimating optimal transformations of random variables is explored.

Suggested Citation

  • Martin R. Young, 1992. "Estimating Optimal Transformations for Correlation and Coherence," Springer Books, in: Connie Page & Raoul LePage (ed.), Computing Science and Statistics, pages 571-575, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4612-2856-1_103
    DOI: 10.1007/978-1-4612-2856-1_103
    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:978-1-4612-2856-1_103. 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.