数学
协方差矩阵
统计
渐近分布
协方差矩阵的估计
特征向量
正态性
背景(考古学)
协方差
应用数学
维数(图论)
基质(化学分析)
样本量测定
组合数学
古生物学
物理
材料科学
量子力学
估计员
复合材料
生物
作者
Jiaxin Qiu,Li Zeng,Jianfeng Yao
摘要
The asymptotic normality for a large family of eigenvalue statistics of a general sample covariance matrix is derived under the ultrahigh-dimensional setting, that is, when the dimension to sample size ratio p/n→∞. Based on this CLT result, we extend the covariance matrix test problem to the new ultra-high-dimensional context, and apply it to test a matrix-valued white noise. Simulation experiments are conducted for the investigation of finite-sample properties of the general asymptotic normality of eigenvalue statistics, as well as the two developed tests.
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