Inference for high-dimensional differential correlation matrices
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Publication:900795
DOI10.1016/j.jmva.2015.08.019zbMath1328.62328arXiv1408.5907OpenAlexW1419241926WikidataQ43211194 ScholiaQ43211194MaRDI QIDQ900795
Publication date: 23 December 2015
Published in: Journal of Multivariate Analysis (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1408.5907
covariance matrixthresholdingoptimal rate of convergenceadaptive thresholdingdifferential co-expression analysisdifferential correlation matrixsparse correlation matrix
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Cites Work
- 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
- Optimal rates of convergence for sparse covariance matrix estimation
- Testing the equality of several covariance matrices with fewer observations than the dimension
- Optimal rates of convergence for covariance matrix estimation
- Covariance regularization by thresholding
- Adaptive covariance matrix estimation through block thresholding
- Adaptive Thresholding for Sparse Covariance Matrix Estimation
- Two-Sample Covariance Matrix Testing and Support Recovery in High-Dimensional and Sparse Settings
- Generalized Thresholding of Large Covariance Matrices
