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https://www.tandfonline.com/doi/abs/10.1080/01621459.2012.758041
Jan 15, 2016 · In the high-dimensional setting, this article considers three interrelated problems: (a) testing the equality of two covariance matrices and ; (b) recovering the support of ; and (c) testing the equality of and row by row. We propose a new test for testing the hypothesis H 0: and investigate its theoretical and numerical properties. The limiting null distribution of the test statistic is ...Cited by: 168
http://www-stat.wharton.upenn.edu/~xiayin/test_cov.pdf
Two-Sample Covariance Matrix Testing and Support Recovery in High-Dimensional and Sparse Settings Tony C AI, Weidong LIU, and Yin XIA In the high-dimensional setting, this article considers three interrelated problems: (a) testing the equality of two covariance matrices 1 and
http://math.sjtu.edu.cn/faculty/weidongl/Publication/003.pdf
Two-Sample Covariance Matrix Testing And Support Recovery ∗ Tony Cai, Weidong Liu and Yin Xia Abstract This paper proposes a new test for testing the equality of two covariance matrices 1 and 2 in the high-dimensional setting and investigates its the-oretical and numerical properties. The limiting null distribution of the test statistic is ...
https://amstat.tandfonline.com/doi/full/10.1080/01621459.2012.758041
Sep 26, 2017 · (2013). Two-Sample Covariance Matrix Testing and Support Recovery in High-Dimensional and Sparse Settings. Journal of the American …Cited by: 168
http://www-stat.wharton.upenn.edu/~tcai/paper/Testing-2-Covariance-Matrices.pdf
Cai, Liu, and Xia: Two-Sample Covariance Matrix Testing and Support Recovery in High-Dimensional and Sparse Settings 267 by $ α = I(M n ≥ q α +4logp −loglogp), (4) where q α is the 1−α quantile of the Type I extreme value distribution with the cumulative distribution function
https://ideas.repec.org/a/taf/jnlasa/v108y2013i501p265-277.html
Downloadable (with restrictions)! In the high-dimensional setting, this article considers three interrelated problems: (a) testing the equality of two covariance matrices and ; (b) recovering the support of ; and (c) testing the equality of and row by row. We propose a new test for testing the hypothesis H 0 : and investigate its theoretical and numerical properties.
https://www.researchgate.net/publication/263063665_Two-Sample_Covariance_Matrix_Testing_and_Support_Recovery_in_High-Dimensional_and_Sparse_Settings
Two-Sample Covariance Matrix Testing and Support Recovery in High-Dimensional and Sparse Settings Article in Journal of the American Statistical Association 108(501) · March 2013 with 38 Reads
https://repository.upenn.edu/statistics_papers/487/
Nov 27, 2017 · Motivated by applications in genomics, we also consider two related problems, recovering the support of Σ1 − Σ2 and testing the equality of the two covariance matrices row by row. New testing procedures are introduced and their properties are studied. …Cited by: 168
http://math.sjtu.edu.cn/faculty/weidongl/Publication/supplement.pdf
Supplement to \Two-Sample Covariance Matrix Testing And Support Recovery" Tony Cai1, Weidong Liu1;2 and Yin Xia1 Abstract In this supplement we prove Proposition 1 and the technical results, Lem-mas 3, 4 and 5, which are used in the proofs of the main results. We also present more extensive simulation results comparing the numerical perfor-
https://link.springer.com/article/10.1007%2Fs11749-017-0533-7
Mar 27, 2017 · Testing and support recovery of multiple high-dimensional covariance matrices with false discovery rate control. Authors; ... Two-sample covariance matrix testing and support recovery in high-dimensional and sparse settings. J Am Stat Assoc 108(501):265–277 MathSciNet …Cited by: 2
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