FITTING OF ROBUST FUZZY REGRESSION ESTIMATOR

Abstract

According to Bang Yong Sohn (1997) is used in M estimator for finding the robust linear regression. The deficiency of robust M estimation is that it does not consider data distribution and is not a function of the whole data because it utilises the median as the weight value. This paper is mainly focus on to detect (Identified) and eliminate the irregular data with the help of a robust estimator concept. It is known as the Robust Fuzzy Regression Estimator (RFRE). A numerical example indicates that utilising residuals based on RFRE-estimators, irregular data may be recognised, and the suggested robust fuzzy regression is most resistant to these spots. The accuracy of the proposed method has been studied through simulation study with existing algorithms.