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01-04-2015 | Focus

The statistical inferences of fuzzy regression based on bootstrap techniques

Authors: Woo-Joo Lee, Hye Young Jung, Jin Hee Yoon, Seung Hoe Choi

Published in: Soft Computing | Issue 4/2015

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Abstract

In this paper, we estimate the parameters of fuzzy regression models and investigate a statistical inferences with crisp inputs and fuzzy outputs for each \(\alpha \)-cut. The proposed approaches of statistical inferences are fuzzy least squares (FLS) method and bootstrap technique. FLS is constructed on the basis of minimizing the sum of square of the total difference between observed and estimated outputs. Numerical examples are illustrated to perform the hypotheses test and to provide the percentile confidence regions by proposed approach.

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Title: The statistical inferences of fuzzy regression based on bootstrap techniques
Authors: Woo-Joo Lee
Hye Young Jung
Jin Hee Yoon
Seung Hoe Choi
Publication date: 01-04-2015
Publisher: Springer Berlin Heidelberg
Published in: Soft Computing / Issue 4/2015
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-014-1415-5

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