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:: Volume 22, Issue 2 (3-2018) ::
Andishe 2018, 22(2): 53-67 Back to browse issues page
Fuzzy Robust Regression Analysis with Fuzzy Response Variable and Fuzzy Parameters Based on the Ranking of Fuzzy Sets
Abstract:   (435 Views)

‎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. ‎Finally‎, ‎we compare this proposed method with ordinal least squares method using the goodness of fit indices‎.

Keywords: ‎Robust regression‎, ‎outlier‎, ‎fuzzy regression‎, ‎OM index‎.
Full-Text [PDF 487 kb]   (361 Downloads)    
Type of Study: Research | Subject: Special
Received: 2016/09/28 | Accepted: 2017/04/20 | Published: 2017/04/20
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Fuzzy Robust Regression Analysis with Fuzzy Response Variable and Fuzzy Parameters Based on the Ranking of Fuzzy Sets. Andishe. 2018; 22 (2) :53-67
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Volume 22, Issue 2 (3-2018) Back to browse issues page
مجله اندیشه آماری Andishe _ye Amari
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