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Quantile Fuzzy Varying Coefficient Regression based on kernel function
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DOI：10.1016/j.asoc.2021.107313.png)
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Abstract
En 中文
The fuzzy varying coefficient regression model is a generalized version of fuzzy linear regression model. This kind of model is flexible and adaptable than fuzzy linear regression model. In this paper, we introduce a fuzzy varying coefficient regression model based on the quantile loss function and under the kernel function. Based on the presented goodness of fit indices, we show that the proposed approach is robust under the outlier data. Some applications of this approach are studied on some data sets and a simulated data set. (C) 2021 Elsevier B.V. All rights reserved.
Keywords:
Fuzzy data
Fuzzy varying coefficient regression
Goodness of fit
Kernel function
Robust regression
Quantile loss function
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