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On Theil's method in fuzzy linear regression modelsopen access

Authors
Choi, Seung HoeJUNG, HYE YOUNGLee, Woo-JooYoon, Jin Hee
Issue Date
Jan-2016
Publisher
대한수학회
Keywords
Fuzzy outlier; Fuzzy regression model; Theil' s method
Citation
Communications of the KMS, v.31, no.1, pp.185 - 198
Indexed
SCOPUS
KCI
Journal Title
Communications of the KMS
Volume
31
Number
1
Start Page
185
End Page
198
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/14569
DOI
https://doi.org/10.4134/CKMS.2016.31.1.185
ISSN
1225-1763
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 α -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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COLLEGE OF SCIENCE AND CONVERGENCE TECHNOLOGY > ERICA 수리데이터사이언스학과 > 1. Journal Articles

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ERICA 과학기술융합대학 (ERICA 수리데이터사이언스학과)
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