Un critère de choix de variables en analyse en composantes principales fondé sur des modèles graphiques gaussiens particuliers

DOI10.2307/3315750zbMath0785.62062OpenAlexW2147675536MaRDI QIDQ4275241

Said Jmel, Antoine de Falguerolles

Publication date: 26 January 1994

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2307/3315750

zbMATH Keywords

Akaike's information criterionprincipal components analysisvariables selectionconditional independence graphsgraphical Gaussian models

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Graphical methods in statistics (62A09)

Related Items (4)

Exact methods for variable selection in principal component analysis: guide functions and pre-selection ⋮ Variable selection in multivariate methods using global score estimation ⋮ Computational aspects of algorithms for variable selection in the context of principal components ⋮ Dimension reduction via principal variables

Cites Work

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• Gaussian Markov distributions over finite graphs
• Factor analysis and AIC
• Graphical models for associations between variables, some of which are qualitative and some quantitative
• How Biased is the Apparent Error Rate of a Prediction Rule?
• Corrigenda to Leone, White, Narula and Narula

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