摘要
本文提出了回归系数的一种新的改进估计——岭型组合主成分估计。讨论了它的可容许性、约束条件下的可容许性和相合性问题。分别在均方误差意义下和Pitman接近原则下,证明了在一定条件下,它优于最小二乘估计和岭估计,并且证明了它有比它们更好的抗干扰能力和稳健性。
In this paper, We propose a ridge combined principal Component estimator for the regression coefficients. And the admissibility, restricted admissibility and consiste-pcy of the estimator are discussed. We show the regions preferable to OLS, OER, under mean square error and Pitman's clossness respectively, and also that it can improve the resistance and sensitivity to data.
出处
《应用概率统计》
CSCD
北大核心
1995年第1期52-59,共8页
Chinese Journal of Applied Probability and Statistics
关键词
可容许性
相合性
主成分估计
岭估计
Admissibility, Relative efficiency, Numerical stability, Consistency, Influential function. Pitman's clossnees.
