2006 | OriginalPaper | Chapter
Fuzzy Regression Approaches and Applications
Authors: Cengiz Kahraman, Ahmet Beşkese, F. Tunç Bozbura
Publisher: Springer Berlin Heidelberg
Fuzzy regression is a fuzzy variation of classical regression analysis. It has beenstudied and applied to various areas. Two types of fuzzy regression models are Tanaka’s linear programming approach and the fuzzy least-squares approach. In this chapter, a wide literature review including both theoretical and application papers on fuzzy regression has been given. Fuzzy regression models for nonfuzzy input/nonfuzzy output, nonfuzzy input/fuzzy output, and possibilistic regression model have been summarized. An illustrative example has been given. Fuzzy hypothesis testing for the coefficients of a linear regression function has been explained with two numerical examples.
