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Statistical Modeling, Analysis and Management of Fuzzy Data pp 282–305Cite as

Linear regression with random fuzzy observations

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Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 87))

Abstract

In this paper, on the basis of the concept of fuzzy random variable a kind of (though not strict) linear estimation theory is developed. Modified linear estimators are presented and discussed, and the least squares approximation principle is used for constructing estimators.

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Author information

Authors and Affiliations

  1. Faculty of Mathematics and Computer Sciences, Freiberg University of Mining and Technology, 09596, Freiberg, Germany

    Wolfgang Näther & Ralf Körner

Authors
  1. Wolfgang Näther
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  2. Ralf Körner
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Editor information

Editors and Affiliations

  1. Dipartimento di Informatica e Sistemistica, Università degli Studi di Pavia, Via Ferrata 1, 27100, Pavia, Italy

    Carlo Bertoluzza

  2. Departamento de Estadística e I.O. y D.M., Universidad de Oviedo, C/Calvo Sotelo, s/n, 33007, Oviedo, Spain

    María-Ángeles Gil

  3. Department of Mathematical Sciences, University of Cincinnati, 45221-0025, Cincinnati, OH, USA

    Dan A. Ralescu

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© 2002 Springer-Verlag Berlin Heidelberg

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Näther, W., Körner, R. (2002). Linear regression with random fuzzy observations. In: Bertoluzza, C., Gil, MÁ., Ralescu, D.A. (eds) Statistical Modeling, Analysis and Management of Fuzzy Data. Studies in Fuzziness and Soft Computing, vol 87. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1800-0_18

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  • DOI: https://doi.org/10.1007/978-3-7908-1800-0_18

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-2501-5

  • Online ISBN: 978-3-7908-1800-0

  • eBook Packages: Springer Book Archive

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