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V-mask Type Criterion for Identification of Outliers In Logistic Regression
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 Title & Authors
V-mask Type Criterion for Identification of Outliers In Logistic Regression
Kim Bu-Yong;
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 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 type 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. Effectiveness of the proposed procedure is evaluated on the basis of the classic and artificial data sets, and it is shown that the procedure deals very well with the masking and swamping effects.
 Keywords
logistic model;outlier;robust distance;clustering;V-mask;
 Language
English
 Cited by
1.
로지스틱회귀모형의 로버스트 추정을 위한 알고리즘,김부용;강명욱;최미애;

응용통계연구, 2007. vol.20. 3, pp.551-559 crossref(new window)
2.
로지스틱모형에서의 주성분회귀,김부용;강명욱;

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3.
로버스트추정에 바탕을 둔 주성분로지스틱회귀,김부용;강명욱;장혜원;

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