Testing proportionality of two large-dimensional covariance matrices

Testing proportionality of two large-dimensional covariance matrices
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DOI：
10.1016/j.csda.2014.03.014
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发表时间：
2014-10
期刊：
Comput. Stat. Data Anal.
影响因子：
--
通讯作者：
Lin Xu;Baisen Liu;Shu-rong Zheng;Shaokun Bao
Lin Xu;Baisen Liu;Shu-rong Zheng;Shaokun Bao
中科院分区：
其他
文献类型：
--
作者：
Lin Xu;Baisen Liu;Shu-rong Zheng;Shaokun Bao

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研究了两个高维协方差矩阵的比例检验问题。基于现代随机矩阵理论，提出了一种伪似然比统计量，并证明了当维和样本量成比例趋于无穷大时，伪似然比统计量的渐近正态分布。
Testing the proportionality of two large-dimensional covariance matrices is studied. Based on modern random matrix theory, a pseudo-likelihood ratio statistic is proposed and its asymptotic normality is proved as the dimension and sample sizes tend to infinity proportionally.