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

作　　者：MIAO Baiqi TONG Qian WU Yuehua JIN Baisuo 

机构地区：[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

出　　处：《Journal of Systems Science & Complexity》2013年第4期583-594,共12页系统科学与复杂性学报（英文版）

基　　金：supported by the National Natural Science Foundation for Young Scientists of China under Grant No.11101397;the Natural Sciences and Engineering Research Council of Canada

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. Simu- lation studies of the Mgorithm is also provided. In addition, the Newton-Raphson iterative algorithm is considered for the purpose of comparison.

关 键 词：Adaptive sequence M-ESTIMATION multivariate linear model recursive algorithm scatter parameters. 

分 类 号：O212.1[理学—概率论与数理统计]