Communications of the Korean Mathematical Society (대한수학회논문집)

Korean Mathematical Society (대한수학회)
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ON THEIL'S METHOD IN FUZZY LINEAR REGRESSION MODELS

  • Choi, Seung Hoe (School of Liberal Arts and Science, Korea Aerospace University) ;
  • Jung, Hye-Young (Department of Statistics Seoul National University) ;
  • Lee, Woo-Joo (Department of Mathematics Yonsei University) ;
  • Yoon, Jin Hee (School of Mathematics and Statistics Sejong University)
  • Received : 2015.03.19
  • Published : 2016.01.31
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Abstract

Regression analysis is an analyzing method of regression 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.

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References

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