Covariance structure regularization via Frobenius-norm discrepancy

DOI10.1016/j.laa.2016.08.013zbMath1352.62090OpenAlexW2508422113MaRDI QIDQ501226

Jine Zhao, Li Zeng, Xiangzhao Cui, Defei Zhang, Chun Li, Jian-Xin Pan

Publication date: 29 December 2016

Published in: Linear Algebra and its Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.laa.2016.08.013

zbMATH Keywords

regularizationcovariance structurecovariance estimationF-norm

Mathematics Subject Classification ID

Multivariate analysis (62H99) Measures of association (correlation, canonical correlation, etc.) (62H20) Numerical linear algebra (65F99)

Related Items (9)

Regularization for high-dimensional covariance matrix ⋮ Correlation structure regularization via entropy loss function for high-dimension and low-sample-size data ⋮ The comparison of the estimators of banded toeplitz covariance structure under the high-dimensional multivariate model ⋮ Block matrix approximation via entropy loss function. ⋮ Approximation with a Kronecker product structure with one component as compound symmetry or autoregression via entropy loss function ⋮ Estimation and optimal structure selection of high-dimensional Toeplitz covariance matrix ⋮ Approximation with a Kronecker product structure with one component as compound symmetry or autoregression ⋮ Unnamed Item ⋮ Unnamed Item

Uses Software

• mctoolbox

Cites Work

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• Joint mean-covariance models with applications to longitudinal data: unconstrained parameterisation
• Least-Squares Approximation of Structured Covariances
• An overview of the estimation of large covariance and precision matrices
• High‐Dimensional Covariance Estimation

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