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广义岭型主成分估计优良性研究
引用本文:张拓,李胜起,徐坤哲. 广义岭型主成分估计优良性研究[J]. 佳木斯工学院学报, 2014, 0(6): 939-940
作者姓名:张拓  李胜起  徐坤哲
作者单位:渤海大学数理学院,辽宁锦州121013
基金项目:国家自然科学基金(11371030).
摘    要:对有偏估计中的广义岭型主成分估计的优良性进行了较深入的研究。证明了广义岭型主成分估计优于最小二乘估计的充要条件,并在此基础上对几类常见的有偏估计在均方误差(阵)条件下优于最小二乘估计的充要条件进行了拓展。

关 键 词:广义岭型主成分估计  最小二乘估计  均方误差  有偏估计

Study of Generalized Ridge Principal Component Estimation
ZHANG Tuo,LI Sheng-qi,XU Kun-zhe. Study of Generalized Ridge Principal Component Estimation[J]. , 2014, 0(6): 939-940
Authors:ZHANG Tuo  LI Sheng-qi  XU Kun-zhe
Affiliation:( College of Mathematics and Physics, Bohai University, Jinzhou 121013, China)
Abstract:In the paper , the choiceness of the generalized ridge principal component estimation in biased estimation was studied .In the process, the necessary and sufficient condition that the generalized ridge principal component estimation is superior to least square estimation was proved .In the light of this demonstration , the necessary and sufficient condition of a few common biased estimations was expanded , that is, they are superior to least square estimation under the condition of mean square error .
Keywords:generalized ridge principal component estimation  least square estimation  mean square er-ror  biased estimation
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