Maximum likelihood factor analysis with rank-deficient sample covariance matrices

DOI10.1016/j.jmva.2006.11.012zbMath1123.62042OpenAlexW2083665881MaRDI QIDQ2370530

Donald Robertson, James Symons

Publication date: 26 June 2007

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2006.11.012

zbMATH Keywords

maximum likelihoodfactor analysis

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Estimation in multivariate analysis (62H12)

Related Items (9)

Exploratory factor analysis -- parameter estimation and scores prediction with high-dimensional data ⋮ Estimation of the proportion of true null hypotheses in high-dimensional data under dependence ⋮ Cross-Sectional Dependence in Panel Data Analysis ⋮ Computation of the maximum likelihood estimator in low-rank factor analysis ⋮ Independent exploratory factor analysis with application to atmospheric science data ⋮ Separable factor analysis with applications to mortality data ⋮ Large panels with common factors and spatial correlation ⋮ A Matrix-Free Likelihood Method for Exploratory Factor Analysis of High-Dimensional Gaussian Data ⋮ Factor Analysis as Data Matrix Decomposition: A New Approach for Quasi-Sphering in Noisy ICA

Cites Work

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• A note on the parameter set for factor analysis models
• Some contributions to maximum likelihood factor analysis
• VI.—The Estimation of Factor Loadings by the Method of Maximum Likelihood

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