Regression shrinkage and selection via the lasso: a retrospective

Regression shrinkage and selection via the lasso: a retrospective Summary. In the paper I give a brief review of the basic idea and some history and then discuss some developments since the original paper on regression shrinkage and selection via the lasso. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of the Royal Statistical Society: Series B (Statistical Methodology) Wiley

Regression shrinkage and selection via the lasso: a retrospective

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Publisher
Wiley
Copyright
© 2011 Royal Statistical Society
ISSN
1369-7412
eISSN
1467-9868
DOI
10.1111/j.1467-9868.2011.00771.x
Publisher site
See Article on Publisher Site

Abstract

Summary. In the paper I give a brief review of the basic idea and some history and then discuss some developments since the original paper on regression shrinkage and selection via the lasso.

Journal

Journal of the Royal Statistical Society: Series B (Statistical Methodology)Wiley

Published: Jun 1, 2011

References

  • Sparsity and smoothness via the fused lasso
    Tibshirani, Tibshirani; Saunders, Saunders; Rosset, Rosset; Zhu, Zhu; Knight, Knight
  • A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis
    Witten, Witten; Tibshirani, Tibshirani; Hastie, Hastie
  • Model selection and estimation in regression with grouped variables
    Yuan, Yuan; Lin, Lin
  • Joint variable selection of fixed and random effects in linear mixed‐effects models
    Bondell, Bondell; Krishna, Krishna; Ghosh, Ghosh
  • The group lasso for logistic regression
    Meier, Meier; van de Geer, van de Geer; Bühlmann, Bühlmann
  • Model selection and estimation in regression with grouped variables
    Ming, Ming; Lin, Lin
  • Regression shrinkage and selection via the lasso
    Tibshirani, Tibshirani
  • Covariance‐regularized regression and classification for high dimensional problems
    Witten, Witten; Tibshirani, Tibshirani
  • Model selection and estimation in regression with grouped variables
    Yuan, Yuan; Lin, Lin

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