Approximation with a Kronecker product structure with one component as compound symmetry or autoregression

DOI10.1016/j.laa.2018.08.031zbMath1402.62117OpenAlexW2888979121MaRDI QIDQ1794311

Katarzyna Filipiak, Daniel Klein

Publication date: 15 October 2018

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

Full work available at URL: https://doi.org/10.1016/j.laa.2018.08.031

zbMATH Keywords

estimationregularizationFrobenius normKronecker productcompound symmetryautoregression of order one

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Measures of association (correlation, canonical correlation, etc.) (62H20) Numerical solutions to overdetermined systems, pseudoinverses (65F20) Norms of matrices, numerical range, applications of functional analysis to matrix theory (15A60)

Related Items (3)

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 ⋮ Unnamed Item

Cites Work

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• Covariance structure regularization via Frobenius-norm discrepancy
• On implementation of a test for Kronecker product covariance structure for multivariate repeated measures data
• Score test for a separable covariance structure with the first component as compound symmetric correlation matrix
• The likelihood ratio test for a separable covariance matrix
• A comparison of likelihood ratio tests and Rao's score test for three separable covariance matrix structures

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