OPTIMAL UNBIASED STATISTICAL ESTIMATING FUNCTIONS FOR HILBERT-SPACE VALUED PARAMETERS

被引:2
作者
SUBRAMANYAM, A
NAIKNIMBALKAR, UV
机构
[1] INDIAN INST TECHNOL,DEPT MATH,BOMBAY 400076,INDIA
[2] UNIV POONA,DEPT STAT,POONA 411007,MAHARASHTRA,INDIA
关键词
complete orthonormal basis; Cramér-Rao inequality; interesting and nuisance Hilbert space valued parameters; score function;
D O I
10.1016/0378-3758(90)90020-U
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
An extended Cramér-Rao type inequality is shown to hold for unbiased statistical estimating functions (USEFs) when the parameter space is a real separable Hilbert space. This enables a definition of an 'optimality criterion' for the USEFs. A definition of the score function is given in this set up and it is shown that the USEF based on it is optimal. A bound is also obtained in the presence of nuisance parameters. Finally some examples are given. © 1990.
引用
收藏
页码:95 / 105
页数:11
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