LIMITING BEHAVIOR OF M-ESTIMATORS OF REGRESSION-COEFFICIENTS IN HIGH-DIMENSIONAL LINEAR-MODELS .1. SCALE-DEPENDENT CASE

被引：31

作者：

BAI, ZD ^{[1
]}

WU, Y ^{[1
]}

机构：

[1] YORK UNIV,N YORK M3J 1P3,ON,CANADA

来源：

JOURNAL OF MULTIVARIATE ANALYSIS | 1994年 / 51卷 / 02期

关键词：

ASYMPTOTIC NORMALITY; CONSISTENCY; HIGH DIMENSIONAL REGRESSION MODEL; LINEAR APPROXIMATION; LINEAR MODELS; M-ESTIMATION; ROBUST ESTIMATION;

D O I：

10.1006/jmva.1994.1059

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：

Asymptotics of M-estimators of the regression coefficients in linear models (both scale-variant and scale-invariant) when the number of regression coefficients tends to infinity as the sample size increases are investigated The main purpose of this study is to establish the asymptotic properties under weaker conditions than usually assumed, especially to relax the restrictions on the order of the dimension. Also, the conditions assumed and the results obtained seem easy to be extended to the multivariate linear models. In the first part of the paper, the asymptotic behavior of the ordinary (i.e., not scale-invariant) M-estimates is considered. (C) 1994 Academic Press, Inc

引用

页码：211 / 239

页数：29

共 14 条

[1]

ANTILLE A, 1987, LINEAR REGRESSION MA

[2]

BAI ZD, 1989, GUJARAT STAT REV, V16, P13

[3] STRONG CONSISTENCY OF M-ESTIMATES IN LINEAR-MODELS [J].