Unbiased Estimator for a Covariance Matrix Under Two-Step Monotone Incomplete Sample
Unbiased Estimator for a Covariance Matrix Under Two-Step Monotone Incomplete Sample
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DOI：
10.1080/03610926.2012.671881
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发表时间：
2014-03
期刊：
影响因子：
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通讯作者：
S. Tsukada
中科院分区：
文献类型：
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作者：
S. Tsukada
本文考虑了两步单调不完全样本下协方差阵的一个推断。均值向量的极大似然估计是无偏的，而协方差矩阵的极大似然估计是有偏的。我们推导出一个无偏估计的协方差矩阵使用Wishart矩阵的一些基本性质。估计的性质进行了研究，并通过数值模拟的精度进行了检查。
In this article, we consider an inference for a covariance matrix under two-step monotone incomplete sample. The maximum likelihood estimator of the mean vector is unbiased but that of the covariance matrix is biased. We derive an unbiased estimator for the covariance matrix using some fundamental properties of the Wishart matrix. The properties of the estimators are investigated and the accuracies are checked by a numerical simulation.