On Theil's method in fuzzy linear regression models
Commun. Korean Math. Soc. 2016 Vol. 31, No. 1, 185-198
Printed January 31, 2016
Seung Hoe Choi, Hye-Young Jung, Woo-Joo Lee, and Jin Hee Yoon
Korea Aerospace University, Seoul National University, Yonsei University, Sejong University
Abstract : Regression analysis is an analyzing method of regression \linebreak model to explain the statistical relationship between explanatory variable and response variables. This paper propose a fuzzy regression analysis applying Theils method which is not sensitive to outliers. This method use medians of rate of increment based on randomly chosen pairs of each components of $\alpha$-level sets of fuzzy data in order to estimate the coefficients of fuzzy regression model. An example and two simulation results are given to show fuzzy Theils estimator is more robust than the fuzzy least squares estimator.
Keywords : fuzzy regression model, Theil's method, fuzzy outlier
MSC numbers : Primary 62A86, 60A86
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