EconPapers    
Economics at your fingertips  
 

A method for detecting outliers in fuzzy regression

Barbara Gładysz

Operations Research and Decisions, 2010, vol. 20, issue 2, 25-40

Abstract: In this article we propose a method for identifying outliers in fuzzy regression. Outliers in a sample may have an important influence on the form of the regression equation. For this reason there is great scientific interest in this issue. The method presented is analogous to the method of finding outliers based on the studentized distribution of residuals. In order to identify outliers, regression models are constructed with an additional explanatory variable for each observation. Next, the significance of a fuzzy regression coefficient is analysed considering this additional explanatory variable. Illustrative examples are presented.

Keywords: fuzzy regression; outliers; possibility theory (search for similar items in EconPapers)
Date: 2010
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://ord.pwr.edu.pl/assets/papers_archive/160%20-%20published.pdf (application/pdf)

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:wut:journl:v:2:y:2010:p:25-40

Access Statistics for this article

More articles in Operations Research and Decisions from Wroclaw University of Science and Technology, Faculty of Management Contact information at EDIRC.
Bibliographic data for series maintained by Adam Kasperski ().

 
Page updated 2025-03-20
Handle: RePEc:wut:journl:v:2:y:2010:p:25-40