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Fuzzy linear regression using rank transform method
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DOI：10.1016/j.fss.2014.11.004.png)
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In regression analysis, the rank transform (RT) method is known to be neither dependent on the shape of the error distribution nor sensitive to outliers. In this paper, we construct a so-called a-level fuzzy regression model based on the resolution identity theorem and apply RT method to this model. Fuzzy regression models with crisp input/fuzzy output and fuzzy input/fuzzy output are investigated to show the effectiveness of the proposed method. To compare its effectiveness with existing methods, we introduce a new performance measure. In addition, we propose a method to obtain a predicted output with respect to a specific target value and show that our model is more robust compared with other methods when the data contain some outliers. (C) 2014 Elsevier B.V. All rights reserved.
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