Minimax rate-optimal estimation of high-dimensional covariance matrices with incomplete data
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Publication:739584
DOI10.1016/j.jmva.2016.05.002zbMath1347.62088arXiv1605.04358OpenAlexW2962988625WikidataQ36173580 ScholiaQ36173580MaRDI QIDQ739584
Publication date: 18 August 2016
Published in: Journal of Multivariate Analysis (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1605.04358
thresholdingmissing dataoptimal rate of convergencesparse covariance matrixadaptive thresholdingbandable covariance matrixgeneralized sample covariance matrix
Estimation in multivariate analysis (62H12) Minimax procedures in statistical decision theory (62C20) Analysis of variance and covariance (ANOVA) (62J10)
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Cites Work
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- High-dimensional covariance matrix estimation with missing observations
- Missing data methods in longitudinal studies: a review
- High-dimensional regression with noisy and missing data: provable guarantees with nonconvexity
- Optimal rates of convergence for sparse covariance matrix estimation
- Hanson-Wright inequality and sub-Gaussian concentration
- Optimal rates of convergence for covariance matrix estimation
- Covariance regularization by thresholding
- Operator norm consistent estimation of large-dimensional sparse covariance matrices
- Adaptive covariance matrix estimation through block thresholding
- Optimal estimation and rank detection for sparse spiked covariance matrices
- Regularized estimation of large covariance matrices
- Sparse Principal Component Analysis with Missing Observations
- Adaptive Thresholding for Sparse Covariance Matrix Estimation
- Tests for High-Dimensional Covariance Matrices
- Generalized Thresholding of Large Covariance Matrices
- Estimating structured high-dimensional covariance and precision matrices: optimal rates and adaptive estimation