Projection sparse principal component analysis: An efficient least squares method
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DOI: 10.1016/j.jmva.2019.04.001
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References listed on IDEAS
- Shen, Haipeng & Huang, Jianhua Z., 2008. "Sparse principal component analysis via regularized low rank matrix approximation," Journal of Multivariate Analysis, Elsevier, vol. 99(6), pages 1015-1034, July.
- JOURNEE, Michel & NESTEROV, Yurii & RICHTARIK, Peter & SEPULCHRE, Rodolphe, 2010. "Generalized power method for sparse principal component analysis," LIDAM Reprints CORE 2232, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Li, Baibing & Martin, Elaine B. & Morris, A. Julian, 2002. "On principal component analysis in L1," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 471-474, September.
- Carl Eckart & Gale Young, 1936. "The approximation of one matrix by another of lower rank," Psychometrika, Springer;The Psychometric Society, vol. 1(3), pages 211-218, September.
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Cited by:
- Jolliffe, Ian, 2022. "A 50-year personal journey through time with principal component analysis," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
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Keywords
Dimension reduction; Power method; SPCA; Variable selection;All these keywords.
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