Robust skew-\(t\) factor analysis models for handling missing data

DOI10.1007/s10260-017-0388-9zbMath1441.62161OpenAlexW2734841333MaRDI QIDQ1689494

Wan-Lun Wang, Min Liu, Tsung I. Lin

Publication date: 12 January 2018

Published in: Statistical Methods and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10260-017-0388-9

zbMATH Keywords

asymmetryincomplete dataimputationECM algorithmrMST distributionSTFA model

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Estimation in multivariate analysis (62H12) Missing data (62D10)

Related Items

Automated learning of \(t\) factor analysis models with complete and incomplete data ⋮ A robust factor analysis model based on the canonical fundamental skew-\(t\) distribution ⋮ Flexible factor model for handling missing data in supervised learning ⋮ Density deconvolution for generalized skew-symmetric distributions ⋮ Asymmetric clusters and outliers: mixtures of multivariate contaminated shifted asymmetric Laplace distributions ⋮ Mixtures of restricted skew-\(t\) factor analyzers with common factor loadings ⋮ Finite mixture modeling of censored and missing data using the multivariate skew-normal distribution

Uses Software

• PGMM

Cites Work

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