Multiple Neutral Data Fitting

Chris Tofallis ()

Annals of Operations Research, 2003, vol. 124, issue 1, 69-79

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

Keywords: functional relation; data fitting; regression; model fitting (search for similar items in EconPapers)
Date: 2003
References: Add references at CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://hdl.handle.net/10.1023/B:ANOR.0000004763.39347.bb (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:annopr:v:124:y:2003:i:1:p:69-79:10.1023/b:anor.0000004763.39347.bb

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

DOI: 10.1023/B:ANOR.0000004763.39347.bb

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().