SELECTING AN ADAPTIVE SEQUENCE FOR COMPUTING RECURSIVE M-ESTIMATORS IN MULTIVARIATE LINEAR REGRESSION MODELS

被引：0

作者：

MIAO Baiqi ^{[1
]}

TONG Qian ^{[2
]}

WU Yuehua ^{[2
]}

JIN Baisuo ^{[1
]}

机构：

[1] Department of Statistics and Finance,University of Science and Technology of China

[2] Department of Mathematics and Statistics,York University,Toronto,Ontario,M3J1P3,Canada

来源：

Journal of Systems Science & Complexity | 2013年 / 26卷 / 04期

基金：

加拿大自然科学与工程研究理事会;

关键词：

Adaptive sequence; M-estimation; multivariate linear model; recursive algorithm; scatter parameters;

D O I：

暂无

中图分类号：

O212.1 [一般数理统计];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In this paper,the authors consider an adaptive recursive algorithm by selecting an adaptive sequence for computing M-estimators in multivariate linear regression models.Its asymptotic property is investigated.The recursive algorithm given by Miao and Wu(1996)is modified accordingly.Simulation studies of the algorithm is also provided.In addition,the Newton-Raphson iterative algorithm is considered for the purpose of comparison.

引用

页码：583 / 594

页数：12

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