Two-sample test for high-dimensional covariance matrices: a normal-reference approach
From MaRDI portal
Publication:6615372
DOI10.1016/j.jmva.2024.105354MaRDI QIDQ6615372
Jingyi Wang, Jin-Ting Zhang, Tianming Zhu
Publication date: 8 October 2024
Published in: Journal of Multivariate Analysis (Search for Journal in Brave)
Cites Work
- Unnamed Item
- A test for the equality of covariance matrices when the dimension is large relative to the sample sizes
- Two sample tests for high-dimensional covariance matrices
- Multiperiod corporate default prediction -- a forward intensity approach
- Two-sample Behrens-Fisher problems for high-dimensional data: a normal reference approach
- High-dimensional covariance matrices in elliptical distributions with application to spherical test
- A further study on Chen-Qin's test for two-sample Behrens-Fisher problems for high-dimensional data
- Testing high-dimensional mean vector with applications. A normal reference approach
- Estimations for some functions of covariance matrix in high dimension under non-normality and its applications
- On error bounds for high-dimensional asymptotic distribution of \(L_2\)-type test statistic for equality of means
- Equality tests of high-dimensional covariance matrices under the strongly spiked eigenvalue model
- A two-sample test for high-dimensional data with applications to gene-set testing
- Hypothesis testing for high-dimensional covariance matrices
- Two-sample tests for high-dimension, strongly spiked eigenvalue models
- Two-Sample Covariance Matrix Testing and Support Recovery in High-Dimensional and Sparse Settings
- A Simple Two-Sample Test in High Dimensions Based on L2-Norm
- Tests for high-dimensional covariance matrices using the theory ofU-statistics
- Tests for High-Dimensional Covariance Matrices
- Comparing large covariance matrices under weak conditions on the dependence structure and its application to gene clustering
- Approximate and Asymptotic Distributions of Chi-Squared–Type Mixtures With Applications
- An approximate randomization test for the high-dimensional two-sample Behrens–Fisher problem under arbitrary covariances
This page was built for publication: Two-sample test for high-dimensional covariance matrices: a normal-reference approach