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JCSE, vol. 7, no. 4, pp.263-271, December, 2013

DOI: http://dx.doi.org/10.5626/JCSE.2013.7.4.263

Robust Fuzzy Varying Coefficient Regression Analysis with Crisp Inputs and Gaussian Fuzzy Output

Zhihui Yang and Yunqiang Yin, Yizeng Chen
College of Sciences, East China Institute of Technology, Fuzhou, Jiangxi, China/ School of Management, Shanghai University, Shanghai, China

Abstract: This study presents a fuzzy varying coefficient regression model after deleting the outliers to improve the feasibility and effectiveness of the fuzzy regression model. The objective of our methodology is to allow the fuzzy regression coefficients to vary with a covariate, and simultaneously avoid the impact of data contaminated by outliers. In this paper, fuzzy regression coefficients are represented by Gaussian fuzzy numbers. We also formulate suitable goodness of fit to evaluate the performance of the proposed methodology. An example is given to demonstrate the effectiveness of our methodology.

Keyword: Gaussian fuzzy number; Goodness of fit; Outlier; Fuzzy varying coefficient regression

Full Paper:   148 Downloads, 1907 View

 
 
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