Pages that link to "Item:Q5326193"

The following pages link to High‐Dimensional Covariance Estimation (Q5326193):

Displaying 50 items.

• High-dimensional covariance matrix estimation with missing observations (Q395991) (← links)
• Covariance structure regularization via Frobenius-norm discrepancy (Q501226) (← links)
• Cleaning large correlation matrices: tools from random matrix theory (Q521794) (← links)
• Hypothesis testing for independence under blocked compound symmetric covariance structure (Q722082) (← links)
• The spectral condition number plot for regularization parameter evaluation (Q782639) (← links)
• Stable estimation of a covariance matrix guided by nuclear norm penalties (Q1623701) (← links)
• Testing independence in high dimensions using Kendall's tau (Q1662048) (← links)
• On the efficient low cost procedure for estimation of high-dimensional prediction error covariance matrices (Q1679123) (← links)
• Variable selection and joint estimation of mean and covariance models with an application to eQTL data (Q1734403) (← links)
• Variable selection in multivariate linear models with high-dimensional covariance matrix estimation (Q1749984) (← links)
• Test for high dimensional covariance matrices (Q1996783) (← links)
• Nonparametric estimation of large covariance matrices with conditional sparsity (Q2024473) (← links)
• High-dimensional correlation matrix estimation for general continuous data with Bagging technique (Q2102349) (← links)
• Mixture regression for longitudinal data based on joint mean-covariance model (Q2140854) (← links)
• Robust error density estimation in ultrahigh dimensional sparse linear model (Q2150677) (← links)
• Parsimony inducing priors for large scale state-space models (Q2155306) (← links)
• Inference on covariance-mean regression (Q2172004) (← links)
• A Stein's approach to covariance matrix estimation using regularization of Cholesky factor and log-Cholesky metric (Q2216965) (← links)
• Detecting granular time series in large panels (Q2224994) (← links)
• MSE bounds for estimators of matrix functions (Q2226459) (← links)
• Large rank-based models with common noise (Q2322620) (← links)
• Some recent work on multivariate Gaussian Markov random fields (Q2414872) (← links)
• Endogeneity in high dimensions (Q2510821) (← links)
• Time series graphical Lasso and sparse VAR estimation (Q2674503) (← links)
• Group-wise shrinkage estimation in penalized model-based clustering (Q2680189) (← links)
• Covariance-regularized regression and classification for high dimensional problems (Q2920259) (← links)
• High dimensional matrix estimation with unknown variance of the noise (Q2960507) (← links)
• (Q2990513) (← links)
• Covariance structure approximation via gLasso in high-dimensional supervised classification (Q3168288) (← links)
• A panorama of positivity. II: Fixed dimension (Q3295975) (← links)
• Large-Scale Estimation of Variance and Covariance Components (Q4325710) (← links)
• How to estimate the correlation dimension of high-dimensional signals? (Q4591604) (← links)
• Projected regression method for solving Fredholm integral equations arising in the analytic continuation problem of quantum physics (Q4597567) (← links)
• (Q5011497) (← links)
• ESTIMATION OF TIME-VARYING COVARIANCE MATRICES FOR LARGE DATASETS (Q5024496) (← links)
• High-dimensional realized covariance estimation: a parametric approach (Q5051983) (← links)
• An Explicit Mean-Covariance Parameterization for Multivariate Response Linear Regression (Q5066446) (← links)
• High‐dimensional covariance matrix estimation using a low‐rank and diagonal decomposition (Q5094335) (← links)
• HIGH DIMENSIONAL ESTIMATION VIA SUM-OF-SQUARES PROOFS (Q5122161) (← links)
• Ensemble Kalman Methods for High-Dimensional Hierarchical Dynamic Space-Time Models (Q5130628) (← links)
• (Q5142916) (← links)
• High dimensional semiparametric estimate of latent covariance matrix for matrix-variate (Q5226649) (← links)
• Some Statistical Problems with High Dimensional Financial data (Q5227362) (← links)
• Bayesian Regularization for Graphical Models With Unequal Shrinkage (Q5242470) (← links)
• Superresolution from Principal Component Models by RKHS Sampling (Q5350436) (← links)
• Multivariate Postprocessing Methods for High-Dimensional Seasonal Weather Forecasts (Q6044606) (← links)
• On variable ordination of Cholesky‐based estimation for a sparse covariance matrix (Q6059504) (← links)
• Assessment of Covariance Selection Methods in High-Dimensional Gaussian Graphical Models (Q6066549) (← links)
• Sparse principal component analysis for high‐dimensional stationary time series (Q6140347) (← links)
• The minimum weighted covariance determinant estimator for high-dimensional data (Q6161665) (← links)