Model selection for factor analysis: Some new criteria and performance comparisons

DOI10.1080/07474938.2017.1382763zbMath1490.62146OpenAlexW1833443108MaRDI QIDQ5860948

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Publication date: 4 March 2022

Published in: Econometric Reviews (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/07474938.2017.1382763

zbMATH Keywords

Akaike information criterionBayesian information criterionfactor modelcorrected Akaike information criterionHannan and Quinn's (1979) information criterion

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Factor analysis and principal components; correspondence analysis (62H25) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Bayesian inference (62F15) Statistical aspects of information-theoretic topics (62B10)

Related Items (6)

A criterion for the number of factors ⋮ Determining the number of factors in constrained factor models via Bayesian information criterion ⋮ Canonical correlation-based model selection for the multilevel factors ⋮ Information criteria for latent factor models: a study on factor pervasiveness and adaptivity ⋮ Mental health and abortions among young women: time-varying unobserved heterogeneity, health behaviors, and risky decisions ⋮ Factor Extraction in Dynamic Factor Models: Kalman Filter Versus Principal Components

Cites Work

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• Model Selection and Multimodel Inference
• Determining the Number of Factors in the General Dynamic Factor Model
• EFFICIENT ESTIMATION OF FACTOR MODELS
• Inferential Theory for Factor Models of Large Dimensions
• Determining the Number of Factors in Approximate Factor Models
• Some Comments on C P

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