Cross-Validated Loss-Based Covariance Matrix Estimator Selection in High Dimensions

Orchestrating single-cell analysis with Bioconductor

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Robust covariance estimation for approximate factor models

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Projected principal component analysis in factor models

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Adult mouse cortical cell taxonomy revealed by single cell transcriptomics

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Spectrum estimation: A unified framework for covariance matrix estimation and PCA in large dimensions

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Tuning-parameter selection in regularized estimations of large covariance matrices

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Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq

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Large covariance estimation by thresholding principal orthogonal complements

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Nonlinear shrinkage estimation of large-dimensional covariance matrices

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Asymptotics of the principal components estimator of large factor models with weakly influential factors

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Adaptive Thresholding for Sparse Covariance Matrix Estimation

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Optimal rates of convergence for covariance matrix estimation

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Covariance regularization by thresholding

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Sparsistency and rates of convergence in large covariance matrix estimation

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On Consistency and Sparsity for Principal Components Analysis in High Dimensions

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Generalized Thresholding of Large Covariance Matrices

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Regularized estimation of large covariance matrices

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High dimensional covariance matrix estimation using a factor model

(2008) Jianqing Fan et al.   JOURNAL OF ECONOMETRICS