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 α-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. © Springer-Verlag Berlin Heidelberg 2009.
Cite
CITATION STYLE
Yoon, J. H., & Choi, S. H. (2009). Fuzzy rank linear regression model. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5866 LNAI, pp. 617–626). https://doi.org/10.1007/978-3-642-10439-8_62
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