Sparse covariance matrix estimation for ultrahigh dimensional data
From MaRDI portal
Publication:6543937
DOI10.1002/sta4.479MaRDI QIDQ6543937
Wanfeng Liang, Yu'e Wu, Hui Chen
Publication date: 27 May 2024
Published in: Stat (Search for Journal in Brave)
Related Items (1)
Cites Work
- A well-conditioned estimator for large-dimensional covariance matrices
- High dimensional covariance matrix estimation using a factor model
- Covariance regularization by thresholding
- Lasso-type recovery of sparse representations for high-dimensional data
- Sparsistency and rates of convergence in large covariance matrix estimation
- On the distribution of the largest eigenvalue in principal components analysis
- Nonparametric estimation of large covariance matrices with conditional sparsity
- Ultrahigh dimensional precision matrix estimation via refitted cross validation
- Regularized estimation of large covariance matrices
- A new approach to Cholesky-based covariance regularization in high dimensions
- Positive definite estimators of large covariance matrices
- Local linear estimation of covariance matrices via Cholesky decomposition
- A Constrainedℓ1Minimization Approach to Sparse Precision Matrix Estimation
- Sure Independence Screening for Ultrahigh Dimensional Feature Space
- Variance Estimation Using Refitted Cross-Validation in Ultrahigh Dimensional Regression
- Joint mean-covariance models with applications to longitudinal data: unconstrained parameterisation
- An overview of the estimation of large covariance and precision matrices
- Estimation of error variance via ridge regression
- Tuning-parameter selection in regularized estimations of large covariance matrices
- Generalized Thresholding of Large Covariance Matrices
- Large Covariance Estimation by Thresholding Principal Orthogonal Complements
- Cholesky-based model averaging for covariance matrix estimation
- Estimating structured high-dimensional covariance and precision matrices: optimal rates and adaptive estimation
This page was built for publication: Sparse covariance matrix estimation for ultrahigh dimensional data