Hypothesis testing on compound symmetric structure of high-dimensional covariance matrix
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Publication:6170542
DOI10.1016/j.csda.2023.107779WikidataQ122686192 ScholiaQ122686192MaRDI QIDQ6170542
Unnamed Author, Kaige Zhao, Shurong Zheng, Tingting Zou
Publication date: 13 July 2023
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
hypothesis testingrandom matrix theoryhigh-dimensional dataunbounded spectral normcompound symmetric structure
Cites Work
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- Testing the structure of the covariance matrix with fewer observations than the dimension
- Spectral analysis of large dimensional random matrices
- High-dimensional asymptotic expansion of LR statistic for testing intraclass correlation structure and its error bound
- On the exact non-null distribution of likelihood ratio criteria for covariance matrices
- CLT for linear spectral statistics of large-dimensional sample covariance matrices.
- Hypothesis tests for high-dimensional covariance structures
- Approximate normality in testing an exchangeable covariance structure under large- and high-dimensional settings
- Hypothesis testing on linear structures of high-dimensional covariance matrix
- High-Dimensional Edgeworth Expansion of LR Statistic for Testing Circular Symmetric Covariance Structure and Its Error Bound
- On Tests for Equicorrelation Coefficient of a Standard Symmetric Multivariate Normal Distribution
- Testing sphericity and intraclass covariance structures under a growth curve model in high dimension
- A high-dimensional likelihood ratio test for circular symmetric covariance structure
- Testing and Estimation for a Circular Stationary Model
- Sample Criteria for Testing Equality of Means, Equality of Variances, and Equality of Covariances in a Normal Multivariate Distribution
- Estimation of Several Intraclass Correlation Coefficients
- A test for block circular symmetric covariance structure with divergent dimension
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