Fuzzy robust regression analysis

Since a fuzzy linear regression model was proposed in 1987, its possibilistic model was employed to analyze data. From viewpoints of fuzzy linear regression, data are understood to express the possibilities of a latent system. When data have error or data are very irregular, the obtained regression model has an unnaturally wide possibility range. We propose a fuzzy robust linear regression which is not influenced by data with error. The model is built as rigid a model as possible to minimize the total error between the model and the data. The robustness of the proposed model is shown using numerical examples.<>