Linear regression analysis for fuzzy/crisp input and fuzzy/crisp output data

In order to estimate fuzzy regression models, possibilistic and least-squares procedures can be considered. By taking into account a least-squares approach, regression models with crisp or fuzzy inputs and crisp or fuzzy output are suggested. In particular, for these fuzzy regression models, unconstrained and constrained (with inequality restrictions) least-squares estimation procedures are developed. Furthermore, for the various models presented, explanatory examples are shown and some concluding remarks are also included. (C) 2002 Elsevier Science B.V. All rights reserved.