On minimaxity of the normal precision matrix estimator of Krishnamoorthy and Gupta
On minimaxity of the normal precision matrix estimator of Krishnamoorthy and Gupta
复制标题
Krishnamoorthy 和 Gupta 的正态精度矩阵估计量的极小极大性
DOI：
10.1080/02331880310001598846
复制
发表时间：
2003
期刊：
影响因子：
1.9
通讯作者：
Y. Sheena
中科院分区：
文献类型：
--
作者：
Y. Sheena
考虑了Wishart分布尺度矩阵的逆矩阵在Stein损失（熵损失）下的正交不变估计问题。在这个问题中，Krishnamoorthy和Gupta [2]提出了一种估计器，并在Monte Carlo模拟中显示了其良好的性能。他们证明了他们的估计量是极小极大的。Perron [3]证明了p = 2时的极大极小性。本文用一种新的方法证明了p = 3的情形。
We consider the orthogonally invariant estimation problem of the inverse of the scale matrix of Wishart distribution using Stein's loss (entropy loss). In this problem Krishnamoorthy and Gupta [2] proposed an estimator and showed its good performance in a Monte Carlo simulation. They conjectured their estimator is minimax. Perron [3] proved its minimaxity for p = 2. In this paper we prove it for p = 3 by using a new method.