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A method of variable selection for fuzzy regression – the possibility approach

100%
GŁADYSZ B., KUCHTA D.
Operations Research and Decisions
|
2011
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vol. 21
|
issue 2
5-15
EN
A method of variable selection for fuzzy regression has been proposed. Using the method, the significance of fuzzy regression coefficients has been examined. The method presented is equivalent to the method of variable selection for classical regression based on an analysis of the confidence intervals for their coefficients. Illustrative examples are presented.
2
Content available remote

A method for detecting outliers in fuzzy regression

100%
GŁADYSZ B.
Operations Research and Decisions
|
2010
|
vol. 20
|
issue 2
25-39
EN
In this article we propose a method for identifying outliers in fuzzy regression. Outliers in a sample may have an important influence on the form of the regression equation. For this reason there is great scientific interest in this issue. The method presented is analogous to the method of finding outliers based on the studentized distribution of residuals. In order to identify outliers, regression models are constructed with an additional explanatory variable for each observation. Next, the significance of a fuzzy regression coefficient is analysed considering this additional explanatory variable. Illustrative examples are presented.
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