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 426 articles , 1 standard article )

Showing results 381 to 400 of 426.
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  1. Mai, Qing; Zou, Hui; Yuan, Ming: A direct approach to sparse discriminant analysis in ultra-high dimensions (2012)
  2. Michel, Vincent; Gramfort, Alexandre; Varoquaux, Gaël; Eger, Evelyn; Keribin, Christine; Thirion, Bertrand: A supervised clustering approach for fMRI-based inference of brain states (2012)
  3. Raheem, S. M. Enayetur; Ahmed, S. Ejaz; Doksum, Kjell A.: Absolute penalty and shrinkage estimation in partially linear models (2012)
  4. Rigollet, Philippe; Tsybakov, Alexandre B.: Sparse estimation by exponential weighting (2012)
  5. Santana, Roberto; Bielza, Concha; Larrañaga, Pedro: Regularized logistic regression and multiobjective variable selection for classifying MEG data (2012)
  6. She, Yiyuan: An iterative algorithm for fitting nonconvex penalized generalized linear models with grouped predictors (2012)
  7. Srivastava, Ashok N.: Greener aviation with virtual sensors: a case study (2012) ioport
  8. Städler, Nicolas; Bühlmann, Peter: Missing values: sparse inverse covariance estimation and an extension to sparse regression (2012)
  9. Taylor, Julian D.; Verbyla, Arūnas P.; Cavanagh, Colin; Newberry, Marcus: Variable selection in linear mixed models using an extended class of penalties (2012)
  10. van de Geer, Sara; Müller, Patric: Quasi-likelihood and/or robust estimation in high dimensions (2012)
  11. Wang, Tao; Xu, Pei-Rong; Zhu, Li-Xing: Non-convex penalized estimation in high-dimensional models with single-index structure (2012)
  12. Wei, Fengrong; Zhu, Hongxiao: Group coordinate descent algorithms for nonconvex penalized regression (2012)
  13. Wu, Tong Tong; He, Xin: Coordinate ascent for penalized semiparametric regression on high-dimensional panel count data (2012)
  14. Xue, Lingzhou; Zou, Hui; Cai, Tianxi: Nonconcave penalized composite conditional likelihood estimation of sparse Ising models (2012)
  15. Xu, Jinfeng: High-dimensional Cox regression analysis in genetic studies with censored survival outcomes (2012)
  16. Yuan, Guo-Xun; Ho, Chia-Hua; Lin, Chih-Jen: An improved GLMNET for L1-regularized logistic regression (2012)
  17. Becker, Stephen; Bobin, Jérôme; Candès, Emmanuel J.: NESTA: A fast and accurate first-order method for sparse recovery (2011)
  18. Becker, Stephen R.; Candès, Emmanuel J.; Grant, Michael C.: Templates for convex cone problems with applications to sparse signal recovery (2011)
  19. Bien, Jacob; Tibshirani, Robert: Prototype selection for interpretable classification (2011)
  20. Binder, Harald; Porzelius, Christine; Schumacher, Martin: An overview of techniques for linking high-dimensional molecular data to time-to-event endpoints by risk prediction models (2011)

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