Variable inclusion and shrinkage algorithms

Journal of the American Statistical Association

Volumn 103, Issue 483, 2008, Pages 1304-1315

  Radchenko, Peter ^a   James, Gareth M ^a  

^a UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

Dantzig selector; Generalized linear model; Lasso; Variable selection

Indexed keywords

EID: 54949144379     PISSN: 01621459     EISSN: None     Source Type: Journal    
DOI: 10.1198/016214508000000481     Document Type: Article

References (16)

1. Bennett, G. (1962), "Probability Inequalities for the Sum of Independent Random Variables," Journal of the American Statistical Association, 57, 33-45.
2. Candes, E., and Tao, T. (2007), "The Dantzig Selector: Statistical Estimation When p Is Much Larger Than n" (with discussion), The Annals of Statistics, 35, 2313-2351.
3. Chen, S., Donoho, D., and Saunders, M. (1998), "Atomic Decomposition by Basis Pursuit," SIAM Journal of Scientific Computing, 20, 33-61.
4. Efron, B., Hastie, T., Johnston, I., and Tibshirani, R. (2004), "Least Angle Regression" (with discussion), The Annals of Statistics, 32, 407-451.
5. Fan, J., and Li, R. (2001), "Variable Selection via Nonconcave Penalized Likelihood and Its Oracle Properties," Journal of the American Statistical Association, 96, 1348-1360.
6. Frank, I. E., and Friedman, J. H. (1993), "A Statistical View of Some Chemometrics Regression Tools," Technometrics, 35, 109-135.
7. James, G. M., and Radchenko, P. (2008), "A Generalized Dantzig Selector With Shrinkage Tuning," available at www-rcf.usc. edu/~gareth.
8. James, G. M., Radchenko, P., and Lv, J. (2008), "DASSO: Connections Between the Dantzig Selector and Lasso," Journal of the Royal Statistical Society, Ser. B, to appear.
9. McCullagh, P., and Nelder, J. (1989), "Generalized Linear Models (2nd ed.), London: Chapman & Hall.
10. Meinshausen, N. (2007), "Relaxed Lasso," Computational Statistics and Data Analysis, 52, 374-393.
11. Park, M., and Hastie, T. (2007), "An l1 Regularization-Path Algorithm for Generalized Linear Models," Journal of the Royal Statistical Society, Ser. B, 69, 659-677.
12. Tibshirani, R. (1996), "Regression Shrinkage and Selection via the Lasso," Journal of the Royal Statistical Society, Ser. B, 58, 267-288.
13. Van de Geer, S. (1999), "Empirical Processes in M-Estimation, Cambridge, U.K.: Cambridge University Press.
14. Zhao, P., Rocha, G., and Yu, B. (2006), "Grouped and Hierarchical Model Selection Through Composite Absolute Penalties," technical report, University of California at Berkeley, Dept. of Statistics.
15. Zou, H. (2006), "The Adaptive Lasso and Its Oracle Properties," Journal of the American Statistical Association, 101, 1418-1429.
16. Zou, H., and Hastie, T. (2005), "Regularization and Variable Selection via the Elastic Net," Journal of the Royal Statistical Society, Ser. B, 67, 301-320.