Choosing an appropriate number of factors in factor analysis with incomplete data

DOI10.1016/j.csda.2007.11.011zbMath1452.62420OpenAlexW2046539208MaRDI QIDQ1023692

Thomas R. Belin, Juwon Song

Publication date: 12 June 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2007.11.011

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Factor analysis and principal components; correspondence analysis (62H25)

Related Items (2)

Automated learning of factor analysis with complete and incomplete data ⋮ Simulation smoothing for state-space models: a computational efficiency analysis

Cites Work

• Factor analysis and AIC
• Estimating the dimension of a model
• Inference and missing data
• Parameter expansion to accelerate EM: the PX-EM algorithm
• Bayes Factors
• Unnamed Item
• Unnamed Item

This page was built for publication: Choosing an appropriate number of factors in factor analysis with incomplete data