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

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

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- latio...

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Veröffentlicht in:Journal of systems science and complexity 2013-08, Vol.26 (4), p.583-594
Hauptverfasser: Miao, Baiqi, Tong, Qian, Wu, Yuehua, Jin, Baisuo
Format: Artikel
Sprache:eng
Schlagworte:
Complex Systems
Control
Mathematics
Mathematics and Statistics
Mathematics of Computing
M估计
Operations Research/Decision Theory
Statistics
Systems Theory
多元线性回归模型
序列
算法选择
自适应
计算
递归算法
递推
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Zusammenfassung: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.
ISSN:1009-6124
1559-7067
DOI:10.1007/s11424-013-1113-x