References
- d'Aspremont , A. , Ghaoui , L. , Jordan , M. and Lanckriet , G. 2007 . A direct formulation for sparse PCA using semidefinite programming . SIAM Rev. , 49 : 434 – 448 . (doi:10.1137/050645506)
- Cadima , J. and Jolliffe , I. T. 1995 . Loadings and correlations in the interpretations of principal components . J. Appl. Stat. , 22 : 203 – 214 . (doi:10.1080/757584614)
- Cadima , J. and Jolliffe , I. T. 2001 . Variable selection and the interpretation of principal subspaces . J. Agri. Biol. Environ. Stat. , 6 : 62 – 79 . (doi:10.1198/108571101300325256)
- Chipman , H. A. and Gu , H. 2005 . Interpretable dimension reduction . J. Appl. Stat. , 32 : 969 – 987 . (doi:10.1080/02664760500168648)
- Hastie , T. , Tibshirani , R. , Eisen , M. B. , Alizadeh , A. , Levy , R. , Staudt , L. , Chan , W. C. , Botstein , D. and Brown , P. 2000 . ‘Gene shaving’ as a method for identifying distinct sets of genes with similar expression patterns . Genome Biol. , 1 pp. research0003.1–0003.21 (doi:10.1186/gb-2000-1-2-research0003)
- Hausman , R. E. 1982 . “ Constrained multivariate analysis ” . In Optimization in Statistics , Edited by: Zanakis , S. H. and Rustagi , J. S. 137 – 151 . North-Holland : Amsterdam .
- Izenman , A. J. 2008 . Modern Multivariate Statistical Techniques , New York : Springer .
- Jeffers , J. N.R. 1967 . Two case studies in the application of principal component analysis . Appl. Stat. , 16 : 225 – 236 . (doi:10.2307/2985919)
- Jolliffe , I. T. 1972 . Discarding variables in a principal component analysis I: Artificial data . Appl. Stat. , 21 : 160 – 173 . (doi:10.2307/2346488)
- Jolliffe , I. T. 1973 . Discarding variables in a principal component analysis II: Real data . Appl. Stat. , 22 : 21 – 31 . (doi:10.2307/2346300)
- Jolliffe , I. T. 2002 . Principal Component Analysis , New York : Springer-Verlag .
- Jolliffe , I. T. , Trendafilov , N. T. and Uddin , M. 2003 . A modified principal component technique based on the LASSO . J. Comput. Graph. Statist. , 12 : 531 – 547 . (doi:10.1198/1061860032148)
- G.P. McCabe, Principal variables, Tech. Rep. 82-3, Purdue University, 1982.
- McCabe , G. P. 1984 . Principal variables . Technometrics , 26 : 137 – 144 . (doi:10.1080/00401706.1984.10487939)
- Moghaddam , B. , Weiss , Y. and Avidan , S. 2006 . Spectral bounds for sparse PCA: Exact and greedy algorithms . Adv. Neur. Inform. Process. Syst. , 18 : 915 – 922 .
- Rousson , V. and Gasser , T. 2004 . Simple component analysis . Appl. Stat. , 53 : 539 – 555 .
- Seber , G. A.F. 2004 . Multivariate Observations , Hoboken , NJ : Wiley .
- Vichi , M. and Saporta , G. 2009 . Clustering and disjoint principal component analysis . Comput. Statist. Data Anal. , 53 : 3194 – 3208 . (doi:10.1016/j.csda.2008.05.028)
- Vigneau , E. and Qannari , E. M. 2003 . Clustering of variables around latent components . Comm. Statist. Simulation Comput. , 32 : 1131 – 1150 . (doi:10.1081/SAC-120023882)
- Yeung , K. Y. and Ruzzo , W. L. 2001 . Principal component analysis for clustering gene expression data . Bioinformatics , 17 : 763 – 774 . (doi:10.1093/bioinformatics/17.9.763)
- Zou , H. , Hastie , T. and Tibshirani , R. 2006 . Sparse principal component analysis . J. Comput. Graph. Statist. , 15 : 265 – 286 . (doi:10.1198/106186006X113430)