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 )

Showing results 441 to 460 of 482.
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  1. Srivastava, Ashok N.: Greener aviation with virtual sensors: a case study (2012) ioport
  2. Städler, Nicolas; Bühlmann, Peter: Missing values: sparse inverse covariance estimation and an extension to sparse regression (2012)
  3. Taylor, Julian D.; Verbyla, Arūnas P.; Cavanagh, Colin; Newberry, Marcus: Variable selection in linear mixed models using an extended class of penalties (2012)
  4. van de Geer, Sara; Müller, Patric: Quasi-likelihood and/or robust estimation in high dimensions (2012)
  5. Wang, Tao; Xu, Pei-Rong; Zhu, Li-Xing: Non-convex penalized estimation in high-dimensional models with single-index structure (2012)
  6. Wei, Fengrong; Zhu, Hongxiao: Group coordinate descent algorithms for nonconvex penalized regression (2012)
  7. Wu, Tong Tong; He, Xin: Coordinate ascent for penalized semiparametric regression on high-dimensional panel count data (2012)
  8. Xue, Lingzhou; Zou, Hui; Cai, Tianxi: Nonconcave penalized composite conditional likelihood estimation of sparse Ising models (2012)
  9. Xu, Jinfeng: High-dimensional Cox regression analysis in genetic studies with censored survival outcomes (2012)
  10. Yuan, Guo-Xun; Ho, Chia-Hua; Lin, Chih-Jen: An improved GLMNET for L1-regularized logistic regression (2012)
  11. Zahid, Faisal M.; Ramzan, Shahla: Ordinal ridge regression with categorical predictors (2012)
  12. Becker, Stephen; Bobin, Jérôme; Candès, Emmanuel J.: NESTA: A fast and accurate first-order method for sparse recovery (2011)
  13. Becker, Stephen R.; Candès, Emmanuel J.; Grant, Michael C.: Templates for convex cone problems with applications to sparse signal recovery (2011)
  14. Bien, Jacob; Tibshirani, Robert: Prototype selection for interpretable classification (2011)
  15. 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)
  16. Bradic, Jelena; Fan, Jianqing; Jiang, Jiancheng: Regularization for Cox’s proportional hazards model with NP-dimensionality (2011)
  17. Breheny, Patrick; Huang, Jian: Coordinate descent algorithms for nonconvex penalized regression, with applications to biological feature selection (2011)
  18. Chen, Jun; Xie, Jichun; Li, Hongzhe: A penalized likelihood approach for bivariate conditional normal models for dynamic co-expression analysis (2011)
  19. McShane, Blakeley B.; Wyner, Abraham J.: Rejoinder: “A statistical analysis of multiple temperature proxies: are reconstructions of surface temperatures over the last 1000 years reliable?” (2011)
  20. Noah Simon; Jerome Friedman; Trevor Hastie; Rob Tibshirani: Regularization Paths for Cox’s Proportional Hazards Model via Coordinate Descent (2011) not zbMATH

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