ASYMPTOTICS FOR REDESCENDING M-ESTIMATORS IN LINEAR MODELS WITH INCREASING DIMENSION

被引：2

作者：

Smucler, Ezequiel ^{[1
]}

机构：

[1] Univ Buenos Aires, CONICET, Ciudad Univ,Pabellon 2, RA-1426 Buenos Aires, DF, Argentina

来源：

STATISTICA SINICA | 2019年 / 29卷 / 02期

关键词：

Dimension asymptotics; M-estimators; MM-estimators; robust regression; S-estimators; P-REGRESSION PARAMETERS; ROBUST REGRESSION; LIMITING BEHAVIOR; DIVERGING NUMBER; COEFFICIENTS; EFFICIENCY; P2/N;

D O I：

10.5705/ss.202016.0549

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 deals with the asymptotic statistical properties of a class of redescending M-estimators in linear models with increasing dimension. This class is large enough to include popular high breakdown point estimators such as S-estimators and MM-estimators, which were not covered by existing results in the literature. We prove consistency assuming only that p/n -> 0 and asymptotic normality essentially if p(3)/n -> 0, where p is the number of covariates and n is the sample size.

引用

页码：1065 / 1081

页数：17

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