Robust partial residuals estimation in semiparametric partially linear model

被引:7
|
作者
Reda Abonazel, Mohamed [1 ]
Gad, Ahmed Abd-Elfatah [2 ]
机构
[1] Cairo Univ, Dept Appl Stat & Econometr, Inst Stat Studies & Res, Giza, Egypt
[2] Zagazig Univ, Dept Stat & Insurance, Fac Commerce, Zagazig, Egypt
关键词
Outliers; penalized M-estimator; penalized regression spline; pseudo data; robustness; REGRESSION ESTIMATOR; RIDGE ESTIMATION; PARAMETERS; SELECTION;
D O I
10.1080/03610918.2018.1494279
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
This paper presents a robust version of partial residuals technique to estimate parametric and nonparametric components in semiparametric partially linear model. The robust estimation of the parametric component is constructed by using an M-estimation after eliminating the effect of the nonparametric component on both the response and covariates based on the pseudo data. Finally, the nonparametric component is estimated robustly by using the residuals from the obtained M-estimation of the parametric component. Simulation studies and a real data analysis illustrate that the proposed estimator performs better than the existing estimations when outliers in the dataset or errors with heavy tails.
引用
收藏
页码:1223 / 1236
页数:14
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