Fuzzy Robust Regression Analysis with Fuzzy Response Variable and Fuzzy Parameters Based on the Ranking of Fuzzy Sets

Robust regression is an appropriate alternative for ordinal regression, when outliers exist in a given data set. If we have fuzzy observations, using ordinal regression methods can’t model them; In this case, using fuzzy regression is a good method. When observations are fuzzy and there are outliers in the data sets, using robust fuzzy regression methods are appropriate alternatives. In this paper, we propose a fuzzy least square regression analysis. When independent variables are crisp, the dependent variable is fuzzy number and outliers are present in the data set. In the proposed method, the residuals are ranked as the comparison of fuzzy sets. In the proposed method, the residuals are ranked as the comparison of fuzzy sets, and the weight matrix is defined by the membership function of the residuals. Weighted fuzzy least squares estimators (WFLSE) are obtained by using weight matrix. Two examples are discussed and results of these examples are presented.