Communications of the
Korean Mathematical Society
CKMS

ISSN(Print) 1225-1763 ISSN(Online) 2234-3024

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Commun. Korean Math. Soc. 2016; 31(1): 185-198

Printed January 31, 2016

https://doi.org/10.4134/CKMS.2016.31.1.185

Copyright © The Korean Mathematical Society.

On Theil's method in fuzzy linear regression models

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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