Honest confidence regions and optimality in high-dimensional precision matrix estimation

Worst possible sub-directions in high-dimensional models

(2016) Sara van de Geer   JOURNAL OF MULTIVARIATE ANALYSIS

Asymptotic normality and optimalities in estimation of large Gaussian graphical models

(2015) Zhao Ren et al.   ANNALS OF STATISTICS

Confidence intervals for high-dimensional inverse covariance estimation

(2015) Jana Janková et al.   Electronic Journal of Statistics

On asymptotically optimal confidence regions and tests for high-dimensional models

(2014) Sara van de Geer et al.   ANNALS OF STATISTICS

Rates of convergence of the Adaptive LASSO estimators to the Oracle distribution and higher order refinements by the bootstrap

(2013) A. Chatterjee et al.   ANNALS OF STATISTICS

Confidence intervals for low dimensional parameters in high dimensional linear models

(2013) Cun-Hui Zhang et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY

The graphical lasso: New insights and alternatives

(2012) Rahul Mazumder et al.   Electronic Journal of Statistics

Square-root lasso: pivotal recovery of sparse signals via conic programming

(2011) A. Belloni et al.   BIOMETRIKA

Bootstrapping Lasso Estimators

(2011) A. Chatterjee et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

A Constrainedℓ1Minimization Approach to Sparse Precision Matrix Estimation

(2011) Tony Cai et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

High-dimensional covariance estimation by minimizing ℓ1-penalized log-determinant divergence

(2011) Pradeep Ravikumar et al.   Electronic Journal of Statistics

Covariance regularization by thresholding

(2009) Peter J. Bickel et al.   ANNALS OF STATISTICS

Sparse permutation invariant covariance estimation

(2008) Adam J. Rothman et al.   Electronic Journal of Statistics