Estimation of Large-Dimensional Covariance Matrices via Second-Order Stein-Type Regularization

• Published in: Entropy (Basel, Switzerland) Vol. 25; no. 1; p. 53
• Main Authors: Zhang, Bin, Huang, Hengzhen, Chen, Jianbin
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 27.12.2022; MDPI
• Subjects: Convexity; Covariance matrix; covariance matrix estimation; Data analysis; Eigenvalues; Eigenvectors; Estimation; Estimators; Mathematical analysis; Mathematical models; Normal distribution; Optimization; Polynomials; Regularization; Stein-type regularization; unbiased estimate; Stein-type regularization; unbiased estimate; covariance matrix estimation

This paper tackles the problem of estimating the covariance matrix in large-dimension and small-sample-size scenarios. Inspired by the well-known linear shrinkage estimation, we propose a novel second-order Stein-type regularization strategy to generate well-conditioned covariance matrix estimators....