A Cholesky-based estimation for large-dimensional covariance matrices
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Publication:5037036
DOI10.1080/02664763.2019.1664424OpenAlexW2973217738MaRDI QIDQ5037036
Xiaoning Kang, Mingqiu Wang, Chaoping Xie
Publication date: 25 February 2022
Published in: Journal of Applied Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/02664763.2019.1664424
Related Items (4)
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Cites Work
- Unnamed Item
- Sparse estimation of a covariance matrix
- A well-conditioned estimator for large-dimensional covariance matrices
- Cholesky-GARCH models with applications to finance
- Simultaneous modelling of the Cholesky decomposition of several covariance matrices
- Covariance regularization by thresholding
- Sparsistency and rates of convergence in large covariance matrix estimation
- Estimation of a covariance matrix under Stein's loss
- A supplement on CLT for LSS under a large dimensional generalized spiked covariance model
- Some theory for Fisher's linear discriminant function, `naive Bayes', and some alternatives when there are many more variables than observations
- On the distribution of the largest eigenvalue in principal components analysis
- Sparse permutation invariant covariance estimation
- Best permutation analysis
- Regularized estimation of large covariance matrices
- Sparse estimation of large covariance matrices via a nested Lasso penalty
- A new approach to Cholesky-based covariance regularization in high dimensions
- Nonparametric estimation of large covariance matrices of longitudinal data
- Adaptive Thresholding for Sparse Covariance Matrix Estimation
- Forward adaptive banding for estimating large covariance matrices
- Joint estimation of multiple graphical models
- A moving average Cholesky factor model in covariance modelling for longitudinal data
- Positive-Definite ℓ1-Penalized Estimation of Large Covariance Matrices
- Joint mean-covariance models with applications to longitudinal data: unconstrained parameterisation
- Partial Correlation Estimation by Joint Sparse Regression Models
- A Joint Modelling Approach for Longitudinal Studies
- Covariance matrix selection and estimation via penalised normal likelihood
- Condition-Number-Regularized Covariance Estimation
- Cholesky-based model averaging for covariance matrix estimation
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