平衡损失函数下James-Stein估计风险比的极小值和极限

IF 1 Q1 MATHEMATICS Kragujevac Journal of Mathematics Pub Date : 2023-01-01 DOI:10.46793/kgjmat2303.459h
Abdenour Hamdaoui, A. Benkhaled, M. Terbeche
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引用次数: 0

摘要

研究了用不同类型的收缩估计器估计多元正态分布均值的问题。在平衡损失函数下,我们建立了James-Stein估计量的极小值。当参数空间的维数和样本量趋于无穷时,我们研究了James-Stein估计量对极大似然估计量的风险比的渐近行为。本文还讨论了James-Stein估计量的正部分。
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On Minimaxity and Limit of Risks Ratio of James-Stein Estimator Under the Balanced Loss Function
The problem of estimating the mean of a multivariate normal distribution by different types of shrinkage estimators is investigated. Under the balanced loss function, we establish the minimaxity of the James-Stein estimator. When the dimension of the parameters space and the sample size tend to infinity, we study the asymptotic behavior of risks ratio of James-Stein estimator to the maximum likelihood estimator. The positive-part of James-Stein estimator is also treated.
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