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V-mask Type Criterion for Identification of Outliers in Logistic RegressionV-mask Type Criterion for Identification of Outliers in Logistic Regression

Other Titles
V-mask Type Criterion for Identification of Outliers in Logistic Regression
Authors
김부용
Issue Date
Dec-2005
Publisher
한국통계학회
Keywords
logistic model; outlier; robust distance; clustering; V-mask; logistic model; outlier; robust distance; clustering; V-mask
Citation
Communications for Statistical Applications and Methods, v.12, no.3, pp 625 - 634
Pages
10
Journal Title
Communications for Statistical Applications and Methods
Volume
12
Number
3
Start Page
625
End Page
634
URI
https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/15751
ISSN
2287-7843
Abstract
A procedure is proposed to identify multiple outliers in the logistic regression. It detects the leverage points by means of hierarchical clustering of the robust distances based on the minimum covariance determinant estimator, and then it employs a V-mask criterion on the scatter plot of robust residuals against robust distances to classify the observations into vertical outliers, bad leverage points, good leverage points, and regular points. Efectiveness of the proposed procedure is evaluated on the basis of the clasic and artificial data sets, and it is shown that the procedure deals very well with the masking and swamping effects.
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