Pages that link to "Item:Q2786367"

The following pages link to A new approach to Cholesky-based covariance regularization in high dimensions (Q2786367):

Displaying 50 items.

• A Cluster Elastic Net for Multivariate Regression (Q63195) (← links)
• Robust estimation of the correlation matrix of longitudinal data (Q139142) (← links)
• Two sample tests for high-dimensional covariance matrices (Q150754) (← links)
• Testing super-diagonal structure in high dimensional covariance matrices (Q308372) (← links)
• Minimax optimal estimation of general bandable covariance matrices (Q391515) (← links)
• Covariance estimation: the GLM and regularization perspectives (Q449843) (← links)
• On the existence of the weighted bridge penalized Gaussian likelihood precision matrix estimator (Q485922) (← links)
• Test for bandedness of high-dimensional covariance matrices and bandwidth estimation (Q693724) (← links)
• Partial estimation of covariance matrices (Q714954) (← links)
• Ensemble sparse estimation of covariance structure for exploring genetic disease data (Q830118) (← links)
• Gaussian variational approximation with sparse precision matrices (Q1702005) (← links)
• Hierarchical sparse modeling: a choice of two group Lasso formulations (Q1704702) (← links)
• Posterior graph selection and estimation consistency for high-dimensional Bayesian DAG models (Q1731759) (← links)
• A multiple testing approach to the regularisation of large sample correlation matrices (Q1739875) (← links)
• A scalable sparse Cholesky based approach for learning high-dimensional covariance matrices in ordered data (Q2008637) (← links)
• Bayesian cumulative logit random effects models with ARMA random effects covariance matrix (Q2131882) (← links)
• Parsimony inducing priors for large scale state-space models (Q2155306) (← links)
• Consistent Bayesian sparsity selection for high-dimensional Gaussian DAG models with multiplicative and beta-mixture priors (Q2196119) (← links)
• Conditionally structured variational Gaussian approximation with importance weights (Q2209703) (← links)
• A Stein's approach to covariance matrix estimation using regularization of Cholesky factor and log-Cholesky metric (Q2216965) (← links)
• Computationally efficient banding of large covariance matrices for ordered data and connections to banding the inverse Cholesky factor (Q2252883) (← links)
• Minimax posterior convergence rates and model selection consistency in high-dimensional DAG models based on sparse Cholesky factors (Q2284379) (← links)
• New formulation of the logistic-Gaussian process to analyze trajectory tracking data (Q2291532) (← links)
• Regularized estimation of precision matrix for high-dimensional multivariate longitudinal data (Q2293546) (← links)
• Ultrahigh dimensional precision matrix estimation via refitted cross validation (Q2295804) (← links)
• A two-stage sequential conditional selection approach to sparse high-dimensional multivariate regression models (Q2304238) (← links)
• A variable selection approach in the multivariate linear model: an application to LC-MS metabolomics data (Q2324950) (← links)
• SURE-tuned tapering estimation of large covariance matrices (Q2361207) (← links)
• Regularized estimation in sparse high-dimensional multivariate regression, with application to a DNA methylation study (Q2406186) (← links)
• A moving average Cholesky factor model in joint mean-covariance modeling for longitudinal data (Q2441146) (← links)
• New sequence spaces and function spaces on interval \([0, 1]\) (Q2443731) (← links)
• Maximum likelihood degree of the two-dimensional linear Gaussian covariance model (Q2659089) (← links)
• Robust sparse precision matrix estimation for high-dimensional compositional data (Q2667613) (← links)
• Testing and support recovery of correlation structures for matrix-valued observations with an application to stock market data (Q2682965) (← links)
• Covariance-regularized regression and classification for high dimensional problems (Q2920259) (← links)
• A profile likelihood approach for longitudinal data analysis (Q3119827) (← links)
• Likelihood-Based Selection and Sharp Parameter Estimation (Q4916454) (← links)
• A Cholesky-based estimation for large-dimensional covariance matrices (Q5037036) (← links)
• (Q5053276) (← links)
• A dual active-set proximal Newton algorithm for sparse approximation of correlation matrices (Q5058396) (← links)
• Bayesian analysis of joint mean and covariance models for longitudinal data (Q5130547) (← links)
• Tuning-parameter selection in regularized estimations of large covariance matrices (Q5222349) (← links)
• Graph-Guided Banding of the Covariance Matrix (Q5231506) (← links)
• A DC Programming Approach for Sparse Estimation of a Covariance Matrix (Q5356977) (← links)
• An improved banded estimation for large covariance matrix (Q5875206) (← links)
• Covariance estimation via fiducial inference (Q5880096) (← links)
• Cholesky-based model averaging for covariance matrix estimation (Q5880164) (← links)
• Covariance prediction via convex optimization (Q6050386) (← links)
• On variable ordination of Cholesky‐based estimation for a sparse covariance matrix (Q6059504) (← links)
• On variable ordination of modified Cholesky decomposition for estimating time‐varying covariance matrices (Q6064131) (← links)