Fuzzy data analysis by possibilistic linear models
Fuzzy Sets and Systems - Fuzzy Numbers
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
Multiobjective fuzzy linear regression analysis for fuzzy input-output data
Fuzzy Sets and Systems
On assessing the H value in fuzzy linear regression
Fuzzy Sets and Systems
Fuzzy linear regression with fuzzy intervals
Fuzzy Sets and Systems
Further examination of fuzzy linear regression
Fuzzy Sets and Systems
Introduction to Linear Regression Analysis, Solutions Manual (Wiley Series in Probability and Statistics)
Design of adaptive fuzzy model for classification problem
Engineering Applications of Artificial Intelligence
Real-time fuzzy switching regression analysis: a convex hull approach
Proceedings of the 11th International Conference on Information Integration and Web-based Applications & Services
Fuzzy goal programming for solving fuzzy regression equations
ICS'06 Proceedings of the 10th WSEAS international conference on Systems
A novel nonlinear programming approach for estimating CAPM beta of an asset using fuzzy regression
Expert Systems with Applications: An International Journal
Kernel based nonlinear fuzzy regression model
Engineering Applications of Artificial Intelligence
Fuzzy linear regression-based detection of earnings management
Expert Systems with Applications: An International Journal
Fuzzy regression analysis: An application on tensile strength of materials and hardness scales
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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Fuzzy regression, a nonparametric method, can be quite useful in estimating the relationships among variables where the available data are very limited and imprecise, and variables are interacting in an uncertain, qualitative, and fuzzy way. Thus, it may have considerably practical applications in many management and engineering problems. But there is still lack of proper interpretation about fuzzy regression. In this paper, we provide an insight into regression intervals so that regression interval analysis, data type analysis and variable selections can be analytically performed. Numerical examples are provided for illustration.