The Mean-shift Outlier Model under Skew Normal Distribution

被引:3
作者
Mattos, Thalita Do Bem [1 ]
Ferreira, Clecio Da Silva [1 ]
机构
[1] Univ Fed Juiz de Fora, Dept Estat, Juiz De Fora, MG, Brazil
关键词
EM algorithm; Mean-shift; Outliers; Skew normal distributions; REGRESSION; DIAGNOSTICS;
D O I
10.1080/03610918.2014.882947
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Asymmetric models have been extensively studied in recent years, in situations where the normality assumption is not satisfied due to lack of symmetry of the data. Techniques for assessing the quality of fit and diagnostic analysis are important for model validation. This paper presents a study of the mean-shift method for detecting outliers in asymmetric normal regression models. Analytical solutions for the estimators of the parameters are obtained using the algorithm. Simulation studies and application to real data are presented, showing the efficiency of the method in detecting outliers.
引用
收藏
页码:1905 / 1917
页数:13
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