A Generalized Maximum Entropy (GME) estimation approach to fuzzy regression model
We consider two fuzzy regression models from fuzzy least squares tradition. We rewrite these models within the Generalized Maximum Entropy Approach of estimation. We compare LS and GME approaches in the multicollinearity problem. Monte Carlo studies show increasing multicollinearity GME outperforms LS in efficiency. Empirical evidence shows some applicative advantages of GME.
generalized maximum entropy fuzzy regression models fuzzy statistics data mining