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arXiv 2201.00230stat.MLcs.LGstat.CO
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恢复协方差阵谱的非渐近迭代方法

Recover the spectrum of covariance matrix: a non-asymptotic iterative method

Georgia Institute of Technology(佐治亚理工学院);University of Bucharest(布加勒斯特大学);Institute of Mathematics of the Romanian Academy(罗马尼亚科学院数学研究所)

Juntao Duan, Ionel Popescu, Heinrich Matzinger

摘要:

众所周知,样本协方差在谱中具有一致性偏差,例如Wishart矩阵的谱服从Marchenko-Pastur定律。在这项工作中,我们引入了一个迭代算法“浓度”,积极消除这种偏见,并恢复真正的光谱小,中等尺寸。

英文摘要:

It is well known the sample covariance has a consistent bias in the spectrum, for example spectrum of Wishart matrix follows the Marchenko-Pastur law. We in this work introduce an iterative algorithm 'Concent' that actively eliminate this bias and recover the true spectrum for small and moderate dimensions.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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