Fisher’s Combined Probability Test for High-Dimensional Covariance Matrices-Reference-Cited by-同舟云学术

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Fisher’s Combined Probability Test for High-Dimensional Covariance Matrices

Published:2022-11-02 Issue: Volume: Page:1-14
ISSN:0162-1459
Container-title:Journal of the American Statistical Association
language:en
Short-container-title:Journal of the American Statistical Association

Author:

Yu Xiufan¹,Li Danning²,Xue Lingzhou³^ORCID

Affiliation:

1. Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN

2. KLAS and School of Mathematics & Statistics, Northeast Normal University, Changchun, China

3. Department of Statistics, Pennsylvania State University, University Park, PA

Funder

National Science Foundation

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/01621459.2022.2126781

Reference41 articles.

1. Limit Theorems for $U$-Processes

2. Corrections to LRT on large-dimensional covariance matrix by RMT

3. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

4. A Lyapunov-type Bound in Rd

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1. Two-sample test for high-dimensional covariance matrices: A normal-reference approach;Journal of Multivariate Analysis;2024-11

2. Double verification for two‐sample covariance matrices test;Stat;2024-04-07

3. Adaptive Testing for Alphas in Conditional Factor Models with High Dimensional Assets;Journal of Business & Economic Statistics;2024-03-06

4. Use of Random Integration to Test Equality of High Dimensional Covariance Matrices;Statistica Sinica;2024

5. PEtests: Power-Enhanced (PE) Tests for High-Dimensional Data;CRAN: Contributed Packages;2023-05-22

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