Two generalizations of the common principal component model

DOI10.1093/biomet/74.1.59zbMath0613.62076OpenAlexW1968463597MaRDI QIDQ4720583

Bernhard K. Flury

Publication date: 1987

Published in: Biometrika (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1093/biomet/74.1.59

zbMATH Keywords

eigenvectordiagonalizationcommon principal component modelnormal theory maximum likelihood estimatorspartial common principal component model

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25)

Related Items (16)

Regularized generalized canonical correlation analysis for multiblock or multigroup data analysis ⋮ A link-free approach for testing common indices for three or more multi-index models ⋮ Raw data maximum likelihood estimation for common principal component models: a state space approach ⋮ Unnamed Item ⋮ Reduced-rank estimation of the difference between two covariance matrices ⋮ Test of linear trend in eigenvalues of k covariance matrices with applications in common principal components analysis ⋮ Estimating correlation matrices that have common eigenvectors. ⋮ Reducing subspace models for large‐scale covariance regression ⋮ Semiparametric partial common principal component analysis for covariance matrices ⋮ Optimal rank-based tests for common principal components ⋮ Unconstrained representation of orthogonal matrices with application to common principal components ⋮ Testing for Common Principal Components under Heterokurticity ⋮ Efficient computation for differential network analysis with applications to quadratic discriminant analysis ⋮ An approximate test for common principal component subspaces in two groups ⋮ A Comparison of Some Methods for the Selection of a Common Eigenvector Model for the Covariance Matrices of Two Groups ⋮ A test of the hypothesis of partial common principal components

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