A robust least squares fuzzy regression model based on kernel function

Document Type: Research Paper


Department of Statistics, Faculty of Mathematical Sciences and Statistics, University of Birjand, Birjand, Iran



In this paper, a new approach is presented to fit a
robust fuzzy regression model based on some fuzzy quantities. In
this approach, we first introduce a new distance between two fuzzy
numbers using the kernel function, and then, based on the least
squares method, the parameters of fuzzy regression model is
estimated. The proposed approach has a suitable performance to
present the robust fuzzy model in the presence of different types
of outliers. Using some simulated data sets and some real data
sets, the application of the proposed approach in modeling some
characteristics with outliers, is studied.