An exact approach to sparse principal component analysis

DOI10.1007/s00180-008-0147-3zbMath1234.62093OpenAlexW2085359512WikidataQ59397202 ScholiaQ59397202MaRDI QIDQ638039

Alessio Farcomeni

Publication date: 8 September 2011

Published in: Computational Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00180-008-0147-3

zbMATH Keywords

branch and bound algorithmdegree of sparsity

Mathematics Subject Classification ID

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

Related Items (6)

\(rs\)-sparse principal component analysis: a mixed integer nonlinear programming approach with VNS ⋮ A plug-in approach to sparse and robust principal component analysis ⋮ PCA Sparsified ⋮ Orthogonal simple component analysis: a new, exploratory approach ⋮ Least Squares Sparse Principal Component Analysis: A Backward Elimination Approach to Attain Large Loadings ⋮ Smart Alpha: active management with unstable and latent factors

Uses Software

• R
• DSPCA

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Projected gradient approach to the numerical solution of the SCoTLASS
• Hedonic housing prices and the demand for clean air
• On the convergence of interior-reflective Newton methods for nonlinear minimization subject to bounds
• Principal component analysis.
• A rationale and test for the number of factors in factor analysis
• 10.1162/153244303322753616
• Regularization and Variable Selection Via the Elastic Net
• A Direct Formulation for Sparse PCA Using Semidefinite Programming

This page was built for publication: An exact approach to sparse principal component analysis