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

Authors:
Pierpaolo D'Urso
Affiliations:
Dipartimento di Statistica, Probabilità e Statistiche Applicate, Università degli Studi di Roma "La Sapienza", P.le Aldo Moro, 5, I-00185 Roma, Italy
Venue:
Computational Statistics & Data Analysis
Year:
2003

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Abstract

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.