On the mean squared error of the ridge estimator of the covariance and precision matrix

DOI10.1016/J.SPL.2016.12.002zbMath1463.62210OpenAlexW2559985623MaRDI QIDQ511555

Wessel N. van Wieringen

Publication date: 21 February 2017

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2016.12.002

zbMATH Keywords

multivariate normal\(\ell_2\)-penalizationinverse covariance matrix

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Ridge regression; shrinkage estimators (Lasso) (62J07)

Related Items (4)

HDBRR: a statistical package for high-dimensional Bayesian ridge regression without MCMC ⋮ Perturbation-based classifier ⋮ Updating of the Gaussian graphical model through targeted penalized estimation ⋮ The Generalized Ridge Estimator of the Inverse Covariance Matrix

Uses Software

• glasso
• mftoolbox

Cites Work

• Unnamed Item
• Sparse inverse covariance estimation with the graphical lasso
• Ridge estimation of inverse covariance matrices from high-dimensional data
• All Invariant Moments of the Wishart Distribution
• Functions of Matrices
• The Risk of James–Stein and Lasso Shrinkage

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