An application of F-transform to a regression model based on Theil´s method

Regression Analysis is an analyzing method of regression model to explain the statistical relationship between explanatory variables and response variables. This paper propose a new regression analysis applying Theil´s method based on F-transform. The main advantage of Theil´s method in regression is the robustness, which means that it is not sensitive to outliers. The proposed method uses the median of rates of increments which are obtained from F-transform, based all possible pairs of F-transformed data in order to estimate the coefficients of fuzzy regression model. An example is given to show that the proposed regression analysis applying Theil´s method based on F-transform is more robust than the least squares estimation (LSE) and even more robust than the original Theil´s method.