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Applications of Peter Hall's martingale limit theory to estimating and testing high dimensional covariance matrices

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Publication:4558606
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DOI10.5705/ss.202017.0060zbMath1406.62057OpenAlexW2765386395MaRDI QIDQ4558606

Danning Li, Hui Zou, Lingzhou Xue

Publication date: 22 November 2018

Published in: Statistica Sinica (Search for Journal in Brave)

Full work available at URL: https://semanticscholar.org/paper/74c9343925270286396f2f31d6f6d990f82c7f9c


zbMATH Keywords

hypothesis testinglarge covariance matrixdegenerate U-statisticsStein's unbiased risk estimationmartingale limit theory


Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Martingales with discrete parameter (60G42) Nonparametric estimation (62G05) Hypothesis testing in multivariate analysis (62H15) Strong limit theorems (60F15)


Related Items (3)

Power enhancement for testing multi-factor asset pricing models via Fisher's method ⋮ Power-Enhanced Simultaneous Test of High-Dimensional Mean Vectors and Covariance Matrices with Application to Gene-Set Testing ⋮ Fisher’s Combined Probability Test for High-Dimensional Covariance Matrices







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