Low-dimensional tracking of association structures in categorical data

DOI10.1007/s11222-014-9470-4zbMath1332.62191OpenAlexW2046189955MaRDI QIDQ261042

Alfonso Iodice D'Enza, Angelos Markos

Publication date: 22 March 2016

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11222-014-9470-4

zbMATH Keywords

visualizationsingular value decompositiondimensionality reductioncorrespondence analysisincremental methods

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items (1)

Online Principal Component Analysis in High Dimension: Which Algorithm to Choose?

Uses Software

• ggplot2
• vegan
• twitteR
• ca

Cites Work

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• 10.1162/153244301753683726
• Correspondence Analysis in Practice
• Probabilistic Principal Component Analysis
• A Stable and Efficient Algorithm for the Rank-One Modification of the Symmetric Eigenproblem
• Intensive Use of Correspondence Analysis for Large Scale Content-Based Image Retrieval
• Augmented Implicitly Restarted Lanczos Bidiagonalization Methods

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