IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v124y2003i1p69-7910.1023-banor.0000004763.39347.bb.html
   My bibliography  Save this article

Multiple Neutral Data Fitting

Author

Listed:
  • Chris Tofallis

Abstract

A method is proposed for estimating the relationship between a number of variables; this differs from regression where the emphasis is on predicting one of the variables. Regression assumes that only one of the variables has error or natural variability, whereas our technique does not make this assumption; instead, it treats all variables in the same way and produces models which are units invariant – this is important for ensuring physically meaningful relationships. It is thus superior to orthogonal regression in that it does not suffer from being scale-dependent. We show that the solution to the estimation problem is a unique and global optimum. For two variables the method has appeared under different names in various disciplines, with two Nobel laureates having published work on it. Copyright Kluwer Academic Publishers 2003

Suggested Citation

  • Chris Tofallis, 2003. "Multiple Neutral Data Fitting," Annals of Operations Research, Springer, vol. 124(1), pages 69-79, November.
    • Handle: RePEc:spr:annopr:v:124:y:2003:i:1:p:69-79:10.1023/b:anor.0000004763.39347.bb
    DOI: 10.1023/B:ANOR.0000004763.39347.bb
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1023/B:ANOR.0000004763.39347.bb
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1023/B:ANOR.0000004763.39347.bb?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mark H Holmes & Michael Caiola, 2018. "Invariance properties for the error function used for multilinear regression," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-25, December.
    2. Chris Tofallis, 2024. "Fitting an Equation to Data Impartially," Papers 2409.02573, arXiv.org.
    3. Chris Tofallis, 2023. "Fitting an Equation to Data Impartially," Mathematics, MDPI, vol. 11(18), pages 1-14, September.
    4. Tofallis, Chris, 2008. "Investment volatility: A critique of standard beta estimation and a simple way forward," European Journal of Operational Research, Elsevier, vol. 187(3), pages 1358-1367, June.
    5. Chris Tofallis, 2011. "Investment Volatility: A Critique of Standard Beta Estimation and a Simple Way Forward," Papers 1109.4422, arXiv.org.

    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:annopr:v:124:y:2003:i:1:p:69-79:10.1023/b:anor.0000004763.39347.bb. 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.