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Least squares estimation of a linear regression model with LR fuzzy response
- R. Coppi, P. D'Urso, P. Giordani, Adriana Santoro
- Mathematics, Computer Science
- Comput. Stat. Data Anal.
- 1 November 2006
A general linear regression model for studying the dependence of a LR fuzzy response variable on a set of crisp explanatory variables, along with a suitable iterative least squares estimation procedure, is introduced. Expand
Robust fuzzy regression analysis
We propose a robust fuzzy linear regression model based on the Least Median Squares-Weighted Least Squares (LMS-WLS) estimation procedure to deal with data contaminated by outliers due to measurement errors. Expand
Goodness of fit and variable selection in the fuzzy multiple linear regression
We measure the goodness of fit of a fuzzy linear regression model with symmetrical fuzzy output variable by means of the coefficient of multiple determination R2, R ¯ 2 and the Mallows measure (Cp). Expand
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We introduce a class of fuzzy clusterwise regression models with LR fuzzy response variable and numeric explanatory variables, which embodies fuzzy clustering, into a fuzzy regression framework. Expand
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The traditional regression analysis is usually applied to homogeneous observations. Expand