Fuzzy Rank Linear Regression Model

Authors:
Jin Hee Yoon;Seung Hoe Choi
Affiliations:
School of Economics, Yonsei University, Seoul, South Korea 120-749;School of Liberal Arts and Sciences, Korea Aerospace University, Koyang, South Korea 412-791
Venue:
AI '09 Proceedings of the 22nd Australasian Joint Conference on Advances in Artificial Intelligence
Year:
2009

Citing 8
Cited 0

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Abstract

In this paper, we construct a fuzzy rank linear regression model using the rank transform (RT) method and least absolute deviation (LAD) method based on the *** -level sets of fuzzy numbers. The rank transform method is known to be efficient when the error distribution does not satisfy the conditions for normality and the method is not sensitive to outliers in the regression analysis. Some examples are given to compare the effectiveness of the proposed method with other existing methods.