An empirical estimator for the sparsity of a large covariance matrix under multivariate normal assumptions

DOI10.1007/S10463-014-0447-ZzbMath1341.62121OpenAlexW1967941384MaRDI QIDQ2352445

Binyan Jiang

Publication date: 1 July 2015

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10463-014-0447-z

zbMATH Keywords

thresholdingsimple random samplingsparsitylarge covariance matrixadaptive thresholdinglarge correlation matrix

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Estimation in multivariate analysis (62H12)

Related Items (1)

Sample size determination for high dimensional parameter estimation with application to biomarker identification

Cites Work

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• Covariance regularization by thresholding
• Operator norm consistent estimation of large-dimensional sparse covariance matrices
• Covariance selection by thresholding the sample correlation matrix
• Positive definite estimators of large covariance matrices
• Adaptive Thresholding for Sparse Covariance Matrix Estimation
• On the sparsity of signals in a random sample
• On Gamma Function Inequalities
• Generalized Thresholding of Large Covariance Matrices

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