Fuzzy data analysis by possibilistic linear models
Fuzzy Sets and Systems - Fuzzy Numbers
Information Sciences: an International Journal
Possibilistic linear systems and their application to the linear regression model
Fuzzy Sets and Systems
Evaluation of fuzzy linear regression models
Fuzzy Sets and Systems
Fuzzy linear regression with fuzzy intervals
Fuzzy Sets and Systems
Fuzzy Sets and Systems
S-curve regression model in fuzzy environment
Fuzzy Sets and Systems
Multidimensional least-squares fitting with a fuzzy model
Fuzzy Sets and Systems
Fuzzy regression wiht radial basis function network
Fuzzy Sets and Systems
Fuzzy least-squares algorithms for interactive fuzzy linear regression models
Fuzzy Sets and Systems - Theme: Modeling and learning
Linear regression analysis for fuzzy/crisp input and fuzzy/crisp output data
Computational Statistics & Data Analysis
Support vector fuzzy regression machines
Fuzzy Sets and Systems - Theme: Learning and modeling
Extended fuzzy regression models using regularization method
Information Sciences—Informatics and Computer Science: An International Journal
Adaptive extended fuzzy basis function network
Neural Computing and Applications
Fuzzy nonparametric regression based on local linear smoothing technique
Information Sciences: an International Journal
Fuzzy polynomial neural networks for approximation of the compressive strength of concrete
Applied Soft Computing
Regularized least squares fuzzy support vector regression for financial time series forecasting
Expert Systems with Applications: An International Journal
Estimation of a simple linear regression model for fuzzy random variables
Fuzzy Sets and Systems
Least squares estimation of a linear regression model with LR fuzzy response
Computational Statistics & Data Analysis
Support vector machines for regression and applications to software quality prediction
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part IV
Fuzzy nonlinear regression with fuzzified radial basis function network
IEEE Transactions on Fuzzy Systems
Stabilization of uncertain fuzzy control systems via a new descriptor system approach
Computers & Mathematics with Applications
| Hi-index | 0.09 |
The fuzzy linear regression model has been a useful tool for analyzing relationships between a set of variables in a fuzzy environment and has been extensively studied in the literature. However, this model may fail to reflect the more complicated regression relationships that are usually found in practice because of its simple and predefined linear structure. In order to enhance the feasibility and adaptability of the fuzzy linear models, we propose in this paper a fuzzy varying coefficient model in which the fuzzy coefficients in the fuzzy linear models are allowed to vary with a covariate. A restricted weighted least-squares estimation is suggested for locally fitting the model. Furthermore, some real-world datasets are analyzed in order to evaluate the performance of the proposed method, and the results show that the proposed model with its estimation approach performs satisfactorily in predicting the fuzzy response even in the case where the regression relationship is complicated.