Regression with fuzzy random data

Authors:
Wolfgang Näther
Affiliations:
Department of Mathematics and Computer Science, Technical University Bergakademie Freiberg, D-09596 Freiberg, Germany
Venue:
Computational Statistics & Data Analysis
Year:
2006

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Abstract

Different approaches to deal with regression analysis when the data are fuzzy are presented. It summarizes recent results and considers them in a more general context which allows to evaluate the different methods. Starting with necessary notions on regression and on fuzzy sets, three approaches are presented: at first a pure descriptive statistical approach, secondly statistical regression when the output is modeled by a fuzzy random variable (FRV) and finally regression between two FRVs.