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Soft Computing
Published in: Soft Computing 1/2020

29-10-2019 | Foundations

Quantile fuzzy regression based on fuzzy outputs and fuzzy parameters

Author: Mohsen Arefi

Published in: Soft Computing | Issue 1/2020

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Abstract

A new approach is investigated to the problem of quantile regression modeling based on the fuzzy response variable and the fuzzy parameters. In this approach, we first introduce a loss function between fuzzy numbers which it can present some quantiles of fuzzy data. Then, we fit a quantile regression model between the available data based on proposed loss function. To evaluate the goodness of fit of the optimal quantile fuzzy regression models, we introduce two indices. Inside, we study the application of the proposed approach in modeling some soil characteristics, based on a real data set.
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Metadata
Title
Quantile fuzzy regression based on fuzzy outputs and fuzzy parameters
Author
Mohsen Arefi
Publication date
29-10-2019
Publisher
Springer Berlin Heidelberg
Published in
Soft Computing / Issue 1/2020
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-019-04424-2

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