The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
On the “degrees of freedom” of the lasso
Open accessAbstract
We study the effective degrees of freedom of the lasso in the framework of Stein’s unbiased risk estimation (SURE). We show that the number of nonzero coefficients is an unbiased estimate for the degrees of freedom of the lasso—a conclusion that requires no special assumption on the predictors. In addition, the unbiased estimator is shown to be asymptotically consistent. With these results on hand, various model selection criteria—Cp, AIC and BIC—are available, which, along with the LARS algorithm, provide a principled and efficient approach to obtaining the optimal lasso fit with the computational effort of a single ordinary least-squares fit.
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Citations
Cites
Regression shrinkage and selection via the lasso
Tibshirani, R. (1996) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1996.tb02080.x · Cited by 51,482
Self-citationThe Elements of Statistical Learning
Hastie, T., Tibshirani, R., & Friedman, J. (2009) · Springer Series in Statistics · doi:10.1007/978-0-387-84858-7 · Cited by 25,970
Self-citationThe Elements of Statistical Learning
Hastie, T., Friedman, J., & Tibshirani, R. (2001) · Springer Series in Statistics · doi:10.1007/978-0-387-21606-5 · Cited by 24,162
Self-citation
Cited by
Gentzkow, M., Kelly, B., & Taddy, M. (2019) · Journal of Economic Literature · doi:10.1257/jel.20181020 · Cited by 1,236
On the adaptive elastic-net with a diverging number of parameters
Zou, H., & Zhang, H. H. (2009) · The Annals of Statistics · doi:10.1214/08-aos625 · Cited by 847
Self-citationL1Penalized Estimation in the Cox Proportional Hazards Model
Goeman, J. J. (2010) · Biometrical Journal · doi:10.1002/bimj.200900028 · Cited by 816
Partial Correlation Estimation by Joint Sparse Regression Models
Peng, J., Wang, P., Zhou, N., & Zhu, J. (2009) · Journal of the American Statistical Association · doi:10.1198/jasa.2009.0126 · Cited by 688
The composite absolute penalties family for grouped and hierarchical variable selection
Zhao, P., Rocha, G., & Yu, B. (2009) · The Annals of Statistics · doi:10.1214/07-aos584 · Cited by 631
Metadata
- Authors
- Zou, H., Hastie, T., & Tibshirani, R.
- Venue
- The Annals of Statistics
- Publisher
- Institute of Mathematical Statistics
- Published
- 2007-10-01
- Volume
- 35
- Issue
- 5
- Pages
- 2173-2192
- ISSN
- 0090-5364 (ISSN-L)
- OpenAlex
- W1995691260
- Cited by
- 947
- References
- 3
- FWCI
- 36.64
- Type
- journal article
- Language
- en
- Open access
- bronze
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