glmnet

R package glmnet: Lasso and elastic-net regularized generalized linear models. Extremely efficient procedures for fitting the entire lasso or elastic-net regularization path for linear regression, logistic and multinomial regression models, poisson regression and the Cox model. Two recent additions are the multiresponse gaussian, and the grouped multinomial. The algorithm uses cyclical coordinate descent in a pathwise fashion, as described in the paper listed below.


References in zbMATH (referenced in 482 articles , 1 standard article )

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  1. Percival, Daniel; Roeder, Kathryn; Rosenfeld, Roni; Wasserman, Larry: Structured, sparse regression with application to HIV drug resistance (2011)
  2. Radchenko, Peter; James, Gareth M.: Improved variable selection with forward-lasso adaptive shrinkage (2011)
  3. Schelldorfer, Jürg; Bühlmann, Peter; van de Geer, Sara: Estimation for high-dimensional linear mixed-effects models using (\ell_1)-penalization (2011)
  4. Tingley, Martin P.: Spurious predictions with random time series: the Lasso in the context of paleoclimatic reconstructions. Discussion of: “A statistical analysis of multiple temperature proxies: are reconstructions of surface temperatures over the last 1000 years reliable?” (2011)
  5. van de Geer, Sara; Bühlmann, Peter; Zhou, Shuheng: The adaptive and the thresholded Lasso for potentially misspecified models (and a lower bound for the Lasso) (2011)
  6. Wand, M. P.; Ormerod, J. T.: Penalized wavelets: embedding wavelets into semiparametric regression (2011)
  7. Wang, Pei; Chao, Dennis L.; Hsu, Li: Learning oncogenic pathways from binary genomic instability data (2011)
  8. Yen, Tso-Jung: A majorization-minimization approach to variable selection using spike and slab priors (2011)
  9. Zhou, Shuheng; Rütimann, Philipp; Xu, Min; Bühlmann, Peter: High-dimensional covariance estimation based on Gaussian graphical models (2011)
  10. Bunea, Florentina; Tsybakov, Alexandre B.; Wegkamp, Marten H.; Barbu, Adrian: SPADES and mixture models (2010)
  11. Caster, Ola; Norén, G. Niklas; Madigan, David; Bate, Andrew: Large-scale regression-based pattern discovery: the example of screening the who global drug safety database (2010)
  12. Jerome Friedman; Trevor Hastie; Rob Tibshirani: Regularization Paths for Generalized Linear Models via Coordinate Descent (2010) not zbMATH
  13. Kolar, Mladen; Song, Le; Ahmed, Amr; Xing, Eric P.: Estimating time-varying networks (2010)
  14. Peng, Jie; Zhu, Ji; Bergamaschi, Anna; Han, Wonshik; Noh, Dong-Young; Pollack, Jonathan R.; Wang, Pei: Regularized multivariate regression for identifying master predictors with application to integrative genomics study of breast cancer (2010)
  15. Schifano, Elizabeth D.; Strawderman, Robert L.; Wells, Martin T.: Majorization-minimization algorithms for nonsmoothly penalized objective functions (2010)
  16. Städler, Nicolas; Bühlmann, Peter; Geer, Sara Van de: (\ell_1)-penalization for mixture regression models (2010)
  17. Tseng, Paul: Approximation accuracy, gradient methods, and error bound for structured convex optimization (2010)
  18. Zhang, Zhihua; Wang, Gang; Yeung, Dit-Yan; Dai, Guang; Lochovsky, Frederick: A regularization framework for multiclass classification: a deterministic annealing approach (2010)
  19. Breheny, Patrick; Huang, Jian: Penalized methods for bi-level variable selection (2009)
  20. Höfling, Holger; Tibshirani, Robert: Estimation of sparse binary pairwise Markov networks using pseudo-likelihoods (2009)

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