Singular value decomposition of design matrices in ANOVA with balanced data

DOI10.1016/0167-7152(91)90173-OzbMath0712.62064OpenAlexW2061128576MaRDI QIDQ749124

Tom Wansbeek

Publication date: 1991

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

Full work available at URL: https://doi.org/10.1016/0167-7152(91)90173-o

zbMATH Keywords

regression analysisfixed effectsspectral decompositionMoore-Penrose inversebalanced datasingular value decomposition of design matrices

Mathematics Subject Classification ID

Eigenvalues, singular values, and eigenvectors (15A18) Analysis of variance and covariance (ANOVA) (62J10) Basic linear algebra (15A99)

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Cites Work

• A note on spectral decomposition and maximum likelihood estimation in ANOVA models with balanced data
• A note on isomorphic characterizations of the dispersion matrix in error- component models
• Block Kronecker Products and Block Norm Matrices in Large-Scale Systems Analysis
• Dispersion Matrices for Variance Components Models
• Necessary and sufficient conditions for explicit solutions in the multivariate normal estimation problem for patterned means and covariances