Sparse CCA using a lasso with positivity constraints

Computational Statistics and Data Analysis

Volumn 54, Issue 12, 2010, Pages 3144-3157

  Lykou, Anastasia ^a   Whittaker, Joe ^a  

^a LANCASTER UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL METHODS;

ALTERNATING LEAST SQUARES; CANONICAL CORRELATION ANALYSIS; DATA SET; LINEAR COMBINATIONS; MARKET BASKET ANALYSIS; MAXIMAL CORRELATION; SIMULATION STUDIES;

DATA HANDLING;

EID: 77955393837     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csda.2009.08.002     Document Type: Article

References (25)

1. Barlow, R.E., Bartholomew, D., Bremner, J.M., Brunk, H.D., 1972. Statistical Inference Under Order Restrictions: The Theory and Application of Isotonic Regression. Wiley, New York.
2. Branco, J., Croux, C., Filzmoser, P., Oliveira, M., 2005. Robust canonical correlations: A comparative study. Computational Statistics 20 (2), 203-229. (Pubitemid 44070753)
3. Breiman, L., 1995. Better subset regression using the nonnegative garotte. Technometrics 37, 373-384.
4. Culhane, A., Perriere, G., Higgins, D., 2003. Cross-platform comparison and visualisation of gene expression data using co-inertia analysis. BMC Bioinformatics 4.
5. Efron, B., Hastie, T., Johnstone, I., Tibshirani, R., 2004. Least angle regression. Annals of Statistics 32, 407-499.
6. Fan, J., Li, R., 2001. Variable selection via nonconcave penalized likelihood and its oracle properties, journal of the American Statistical Association 96 (456), 1348-1360. (Pubitemid 33695585)
7. Gill, P.E., Murray, W., Wright, M.H., 1981. Practical Optimization. Academic Press, London.
8. Gonzalez, I., Dejean, S., Martin, P., Baccini, A., 2008. Cca: An r package to extend canonical correlation analysis. Journal of Statistical Software 23 (12).
9. Hardoon, D.R., Shawe-Taylor, J.R., 2007. Sparse canonical correlation analysis. Technical Report, University College London.
10. Jolliffe, I., Trendafilov, N., Uddin, M., 2003. A modified principal component technique based on the lasso. Journal of Computational and Graphical Statistics 12 (3), 531-547. (Pubitemid 37239916)
11. Lai, P.L., Fyfe, C., 2000. Kernel and nonlinear canonical correlation analysis. International Journal of Neural Systems 10 (5), 365-377.
12. Lawson, C., Hanson, R., 1974. Solving Least Square Problems. Prentice Hall, Englewood Cliffs, NJ.
13. Le Cao, K., Martin, P., Robert-Grani, C., Besse, P., 2009a. Sparse canonical methods for biological data integration: Application to a cross-platform study. BMC Bioinformatics 10, 34.
14. Le Cao, K., Rossouw, D., Robert-Granie, C., Besse, P., 2009b. A sparse pis for variable selection when integratingomics data. Statistical Applications in Genetics and Molecular Biology 7(1).
15. Leurgans, S., Moyeed, R., Silverman, B., 1993. Canonical correlation analysis when the data are curves. Journal of the Royal Statistical Society B 55 (3), 725-740.
16. Mardia, K.V., Kent, J.T., M., B.J., 1979. Multivariate Statistics. Academic Press, London.
17. Parkhomenko, E., Tritchler, D., Beyene, J., 2009. Sparse canonical correlation analysis with application to genomic data integration. Statistical Applications in Genetics and Molecular Biology 7.
18. Tibshirani, R., 1996. Regression shrinkage and selection via the lasso. Journal of Royal Statistical Society B 58, 267-288.
19. Trendafilov, N., Jolliffe, I., 2006. Projected gradient approach to the numerical solution of the scotlass. Computational Statistics and Data Analysis 50, 242-253. (Pubitemid 41282704)
20. Vinof, H., 1976. Canonical ridge and econometrics of joint productions. Journal of Econometrics 4 (2), 147-166.
21. Waaijenborg, S., Verselewel de Witt Hamer, P., Zwinderman, A., 2008. Quantifying the association between gene expressions and dna-markers by penalized canonical correlation analysis. Statistical Applications in Genetics and Molecular Biology 7 (1).
22. Wiesel, A., Kliger, M., Hero, III. A.O., 2008. A greedy approach to sparse canonical correlation analysis. Technical Report, University of Michigan.
23. Witten, D., Tibshirani, R., Hastie, T., 2009. A penalized matrix decomposition, with application to sparse principal components and canonical correlation analysis. Biostatistics 1-20.
24. Zou, H., Hastie, T., Tibshirani, T., 2006. Sparse principal component analysis. Journal of Computational and Graphical Statistics 15(2), 265-286.
25. Zou, J., Hastie, T., 2005. Regularization and variable selection via the elastic net. Journal of the Royal Statistical Society Series B 67, 301-320. (Pubitemid 40465877)