Simple Search

Query:

Enter a query and click »Search«...

Format:

Display: entries per page entries

Zbl 0982.62066
Varga, Štefan; Šabo, Michal
Linear regression with fuzzy variables. (English)
[A] 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). ISBN 3-7908-1322-2

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.

MSC 2000:: *62J05 Linear regression
62J99 Linear statistical inference

Keywords: fuzzy numbers; fuzzy statistics; data analysis; fitted data; estimation; observed data; fuzzy regression

Comment on this Item PDF MathML XML ASCII DVI PS BibTeX Online Ordering

	Scientific prize winners of the ICM 2010
	Overhang
	Lie groups, physics and geometry. An introduction for physicists, engineers and chemists.

Simple Search

Zentralblatt MATH Berlin [Germany]