Comparing Classical and Robust Sparse PCA

DOI10.1007/978-3-642-33042-1_31zbMath1341.62169OpenAlexW107071865MaRDI QIDQ2805799

Peter Filzmoser, Valentin Todorov

Publication date: 13 May 2016

Published in: Synergies of Soft Computing and Statistics for Intelligent Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-642-33042-1_31

zbMATH Keywords

robust statisticsprincipcal component analysis

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25)

Uses Software

• robustbase
• ROBPCA

Cites Work

• Unnamed Item
• High breakdown estimators for principal components: the projection-pursuit approach revis\-ited
• Improve robustness of sparse PCA by \(L_{1}\)-norm maximization
• Sparse principal component analysis via regularized low rank matrix approximation
• Robust Statistics

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