Stein's idea and minimax admissible estimation of a multivariate normal mean

Stein's idea and minimax admissible estimation of a multivariate normal mean
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斯坦因的想法和多元正态均值的极小极大容许估计

DOI:
10.1016/s0047-259x(03)00097-6
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发表时间:
2004
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影响因子:
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通讯作者:
Yuzo Maruyama
Yuzo Maruyama
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文献类型:
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作者:
Yuzo Maruyama

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本文考虑了方差损失下多元正态均值向量的估计,提出了一类新的Minimax可容许估计,它们是关于原点点先验和连续分层型先验混合的先验分布的广义Bayes估计。我们还研究了条件下,这些广义贝叶斯极大极小估计改善詹姆斯-斯坦估计和积极的部分詹姆斯-斯坦估计。
We consider estimation of a multivariate normal mean vector under sum of squared error loss.We propose a new class of minimax admissible estimator which are generalized Bayes with respect to a prior distribution which is a mixture of a point prior at the origin and a continuous hierarchical type prior. We also study conditions under which these generalized Bayes minimax estimators improve on the James–Stein estimator and on the positive-part James–Stein estimator.