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Linear regression with fuzzy variables. (English) Zbl 0982.62066
Sinčák, Peter (ed.) et al., The state of the art in computational intelligence. Proceedings of the European symposium on computational intelligence, Košice, Slovak Republic, August 30-September 1, 2000. With Forewords by Lotfi A. Zadeh, David E. Goldberg and Kunihiko Fukushima. Heidelberg: Physica-Verlag. Advances in Soft Computing. 99-103 (2000).
Summary: A method of estimation of unknown crisp parameters in a linear regression model with fuzzy variables and crisp parameters is suggested by minimizing the sum of the squares of the Diamond distances between the values from the model and the values from the observed data. The method is a generalization of the least squares estimation method from the classical linear regression model to the fuzzy regression model.
For the entire collection see [Zbl 0978.00038].

MSC:
62J05 Linear regression; mixed models
62J99 Linear inference, regression
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