Pages that link to "Item:Q2477058"

The following pages link to Regularized estimation of large covariance matrices (Q2477058):

Displaying 50 items.

• Ultrahigh dimensional precision matrix estimation via refitted cross validation (Q2295804) (← links)
• Compressed covariance estimation with automated dimension learning (Q2300095) (← links)
• Robust estimator of the correlation matrix with sparse Kronecker structure for a high-dimensional matrix-variate (Q2306279) (← links)
• Bayesian discriminant analysis using a high dimensional predictor (Q2316972) (← links)
• A new semiparametric estimation approach for large dynamic covariance matrices with multiple conditioning variables (Q2323372) (← links)
• Greedy Gaussian segmentation of multivariate time series (Q2324258) (← links)
• Testing for independence of large dimensional vectors (Q2328066) (← links)
• High-dimensional autocovariance matrices and optimal linear prediction (Q2340876) (← links)
• Linear estimating equations for exponential families with application to Gaussian linear concentration models (Q2341892) (← links)
• Optimal estimation and rank detection for sparse spiked covariance matrices (Q2343031) (← links)
• Independence test for high dimensional data based on regularized canonical correlation coefficients (Q2343952) (← links)
• Substitution principle for CLT of linear spectral statistics of high-dimensional sample covariance matrices with applications to hypothesis testing (Q2343955) (← links)
• Detecting positive correlations in a multivariate sample (Q2345119) (← links)
• On the sample covariance matrix estimator of reduced effective rank population matrices, with applications to fPCA (Q2348740) (← links)
• Spectrum estimation: a unified framework for covariance matrix estimation and PCA in large dimensions (Q2350071) (← links)
• Innovated interaction screening for high-dimensional nonlinear classification (Q2352740) (← links)
• Do semidefinite relaxations solve sparse PCA up to the information limit? (Q2352742) (← links)
• Sparse regularized discriminant analysis with application to microarrays (Q2359339) (← links)
• Mixture ensemble Kalman filters (Q2361189) (← links)
• SURE-tuned tapering estimation of large covariance matrices (Q2361207) (← links)
• Vast volatility matrix estimation for high-frequency financial data (Q2380093) (← links)
• Optimal properties of centroid-based classifiers for very high-dimensional data (Q2380097) (← links)
• Self-learning \(K\)-means clustering: a global optimization approach (Q2392762) (← links)
• High-dimensional change-point estimation: combining filtering with convex optimization (Q2397167) (← links)
• Inferences in panel data with interactive effects using large covariance matrices (Q2398975) (← links)
• Multiscale geometric methods for data sets. I: Multiscale SVD, noise and curvature. (Q2402490) (← links)
• Large covariance estimation through elliptical factor models (Q2413594) (← links)
• D-trace estimation of a precision matrix using adaptive lasso penalties (Q2418368) (← links)
• Fixed support positive-definite modification of covariance matrix estimators via linear shrinkage (Q2418516) (← links)
• Sparse covariance matrix estimation in high-dimensional deconvolution (Q2419664) (← links)
• Optimal classification in sparse Gaussian graphic model (Q2438761) (← links)
• Refining genetically inferred relationships using treelet covariance smoothing (Q2443132) (← links)
• Covariance and precision matrix estimation for high-dimensional time series (Q2443210) (← links)
• Asymptotic theory for maximum deviations of sample covariance matrix estimates (Q2447660) (← links)
• Regularized multivariate regression models with skew-\(t\) error distributions (Q2448807) (← links)
• Design-free estimation of variance matrices (Q2451793) (← links)
• Random matrix theory in statistics: a review (Q2453609) (← links)
• Sparse estimation of large covariance matrices via a nested Lasso penalty (Q2482977) (← links)
• Strong oracle optimality of folded concave penalized estimation (Q2510819) (← links)
• Posterior contraction in sparse Bayesian factor models for massive covariance matrices (Q2510828) (← links)
• High dimensional covariance matrix estimation using multi-factor models from incomplete information (Q2515313) (← links)
• Sparse and low-rank covariance matrix estimation (Q2516376) (← links)
• Bayesian sparse covariance decomposition with a graphical structure (Q2631381) (← links)
• Asymptotically independent U-statistics in high-dimensional testing (Q2656592) (← links)
• Differentially private precision matrix estimation (Q2663280) (← links)
• An approach to the distributionally robust shortest path problem (Q2668652) (← links)
• Limited memory BFGS method for least squares semidefinite programming with banded structure (Q2674941) (← links)
• Matrix means and a novel high-dimensional shrinkage phenomenon (Q2676932) (← links)
• Testing and support recovery of correlation structures for matrix-valued observations with an application to stock market data (Q2682965) (← links)
• Multilevel ensemble Kalman filtering (Q2814458) (← links)