LIMITING BEHAVIOR OF RECURSIVE M-ESTIMATORS IN MULTIVARIATE LINEAR REGRESSION MODELS AND THEIR ASYMPTOTIC EFFICIENCIES

作者：Miao Baiqi^*; Wu Yuehua; Liu Donghai

来源：Acta Mathematica Scientia, 2010, 30(1): 319-329.

• asymptotic efficiency
• asymptotic normality
• asymptotic relative efficiency
• least absolute deviation
• least squares
• M-estimation
• multivariate linear
• optimal estimator
• recursive algorithm
• regression coefficients
• robust estimation
• regression model

Recursive algorithms are very useful for computing M-estimators of regression coefficients and scatter parameters. In this article, it is shown that for a nondecreasing u(1)(t), under some mild conditions the recursive M-estimators of regression coefficients and scatter parameters are strongly consistent and the recursive M-estimator of the regression coefficients is also asymptotically normal distributed. Furthermore, optimal recursive M-estimators, asymptotic efficiencies of recursive M-estimators and asymptotic relative efficiencies between recursive M-estimators of regression coefficients are studied.

• 出版日期2010-1
• 单位中国人民武装警察部队学院