Pages that link to "Item:Q2477058"

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

Displaying 50 items.

• Innovated higher criticism for detecting sparse signals in correlated noise (Q90256) (← links)
• Estimating sufficient reductions of the predictors in abundant high-dimensional regressions (Q116954) (← links)
• Geometric median and robust estimation in Banach spaces (Q122792) (← links)
• Latent variable graphical model selection via convex optimization (Q132216) (← links)
• Non-asymptotic error controlled sparse high dimensional precision matrix estimation (Q145307) (← links)
• Nonlinear shrinkage estimation of large-dimensional covariance matrices (Q149570) (← links)
• Two sample tests for high-dimensional covariance matrices (Q150754) (← links)
• Asymptotic normality and optimalities in estimation of large Gaussian graphical models (Q152845) (← links)
• Signal extraction approach for sparse multivariate response regression (Q153109) (← links)
• Higher criticism for large-scale inference, especially for rare and weak effects (Q254401) (← links)
• A reweighted \(\ell^2\) method for image restoration with Poisson and mixed Poisson-Gaussian noise (Q256075) (← links)
• Testing for jumps in the presence of smooth changes in trends of nonstationary time series (Q262694) (← links)
• Estimating sparse precision matrix: optimal rates of convergence and adaptive estimation (Q282440) (← links)
• Estimation of inverse autocovariance matrices for long memory processes (Q282527) (← links)
• Gaussian and robust Kronecker product covariance estimation: existence and uniqueness (Q290708) (← links)
• More powerful tests for sparse high-dimensional covariances matrices (Q290714) (← links)
• Nonparametric eigenvalue-regularized precision or covariance matrix estimator (Q292867) (← links)
• High dimensional covariance matrix estimation using a factor model (Q299275) (← links)
• Model selection for factorial Gaussian graphical models with an application to dynamic regulatory networks (Q306638) (← links)
• Testing super-diagonal structure in high dimensional covariance matrices (Q308372) (← links)
• Robust inference of risks of large portfolios (Q308377) (← links)
• Implied basket correlation dynamics (Q308412) (← links)
• Sharp minimax tests for large covariance matrices and adaptation (Q309553) (← links)
• Testing a single regression coefficient in high dimensional linear models (Q311657) (← links)
• Linear shrinkage estimation of large covariance matrices using factor models (Q321913) (← links)
• Asymptotic theory for large volatility matrix estimation based on high-frequency financial data (Q326850) (← links)
• A regularized profile likelihood approach to covariance matrix estimation (Q334313) (← links)
• Minimax bounds for sparse PCA with noisy high-dimensional data (Q366956) (← links)
• Estimating summary statistics in the spike-train space (Q385299) (← links)
• Optimal sparse volatility matrix estimation for high-dimensional Itô processes with measurement errors (Q385765) (← links)
• Tests for covariance matrix with fixed or divergent dimension (Q385784) (← links)
• Minimax optimal estimation of general bandable covariance matrices (Q391515) (← links)
• Adjusting for high-dimensional covariates in sparse precision matrix estimation by \(\ell_1\)-penalization (Q391559) (← links)
• PCA consistency for the power spiked model in high-dimensional settings (Q391897) (← links)
• Model selection and estimation in the matrix normal graphical model (Q413758) (← links)
• A probabilistic model for image representation via multiple patterns (Q437785) (← links)
• Covariance estimation: the GLM and regularization perspectives (Q449843) (← links)
• High-dimensional covariance matrix estimation in approximate factor models (Q450002) (← links)
• Covariance matrix estimation for stationary time series (Q450046) (← links)
• Posterior convergence rates for estimating large precision matrices using graphical models (Q470497) (← links)
• Estimation of high-dimensional partially-observed discrete Markov random fields (Q470504) (← links)
• Bayesian sparse graphical models for classification with application to protein expression data (Q484003) (← links)
• Semiparametric model building for regression models with time-varying parameters (Q494386) (← links)
• On high-dimensional change point problem (Q525890) (← links)
• Estimation of high-dimensional low-rank matrices (Q548539) (← links)
• Estimation of (near) low-rank matrices with noise and high-dimensional scaling (Q548547) (← links)
• On the limiting spectral distribution of the covariance matrices of time-lagged processes (Q604359) (← links)
• High-dimensionality effects in the Markowitz problem and other quadratic programs with linear constraints: risk underestimation (Q620558) (← links)
• Mean-variance portfolio optimization when means and covariances are unknown (Q641134) (← links)
• Eigenvectors of some large sample covariance matrix ensembles (Q644783) (← links)