Diagnostic plot for the identification of high leverage collinearity-influential observations

被引:0
|
作者
Bagheri, Arezoo [1 ]
Midi, Habshah [2 ]
机构
[1] Natl Populat Studies & Comprehens Management Inst, Tehran, Iran
[2] Univ Putra Malaysia, Fac Sci, Inst Math Res, Dept Math, Serdang 43400, Selangor, Malaysia
关键词
Collinearity influential observation; diagnostic robust generalized potential; high leverage points; multicollinearity; VARIANCE INFLATION FACTORS; LINEAR-REGRESSION; PERFORMANCE; OUTLIERS; POINTS;
D O I
暂无
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
High leverage collinearity influential observations are those high leverage points that change the multicollinearity pattern of a data. It is imperative to identify these points as they are responsible for misleading inferences on the fitting of a regression model. Moreover, identifying these observations may help statistics practitioners to solve the problem of multicollinearity, which is caused by high leverage points. A diagnostic plot is very useful for practitioners to quickly capture abnormalities in a data. In this paper, we propose new diagnostic plots to identify high leverage collinearity influential observations. The merit of our proposed diagnostic plots is confirmed by some well-known examples and Monte Carlo simulations.
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页码:51 / 69
页数:19
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