Adaptive Unified Biased Estimators of Parameters in Linear Model

作     者：Hu Yang~1 Li-xing Zhu~(2,3)1 College of Science,Chongqing University,chongqing 400044,China(E-mail:yh@***)2 Department of Statistics and Actuarial Science,The University of Hong Kong3 Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing 100080,China 

出 版 物：《Acta Mathematicae Applicatae Sinica》 (应用数学学报(英文版))

年 卷 期：2004年第3期

页      面：71-78页

核心收录：

学科分类：02[经济学] 0202[经济学-应用经济学] 020208[经济学-统计学] 07[理学] 0714[理学-统计学（可授理学、经济学学位）] 070103[理学-概率论与数理统计] 0701[理学-数学] 

基　　金：Supported by a grant from The Research Grants Council of Hong Kong HKU7181/02H.The authors wishes to thank the referees for the constructive comments 

主　　题：Least squares estimator linear model sufficient coadition adaptive unified biased estimator 

摘      要：To tackle multi collinearity or ill-conditioned design matrices in linear models,adaptive biasedestimators such as the time-honored Stein estimator,the ridge and the principal component estimators havebeen studied *** study when a biased estimator uniformly outperforms the least squares estimator,some sufficient conditions are proposed in the *** this paper,we propose a unified framework toformulate a class of adaptive biased *** class includes all existing biased estimators and some newones.A sufficient condition for outperforming the least squares estimator is *** terms of selectingparameters in the condition,we can obtain all double-type conditions in the literature.