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 495 articles , 1 standard article )

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  1. Wang, Zhaoran; Liu, Han; Zhang, Tong: Optimal computational and statistical rates of convergence for sparse nonconvex learning problems (2014)
  2. Wasserman, Larry: Discussion: “A significance test for the lasso” (2014)
  3. Wong, William W. L.; Griesman, Josh; Feng, Zeny Z.: Imputing genotypes using regularized generalized linear regression models (2014)
  4. Yang, Yi; Zou, Hui: A coordinate majorization descent algorithm for (\ell_1) penalized learning (2014)
  5. Yu, Yi; Feng, Yang: APPLE: approximate path for penalized likelihood estimators (2014)
  6. Zeng, Ping; Wei, Yongyue; Zhao, Yang; Liu, Jin; Liu, Liya; Zhang, Ruyang; Gou, Jianwei; Huang, Shuiping; Chen, Feng: Variable selection approach for zero-inflated count data via adaptive lasso (2014)
  7. Zhang, Zhihua; Chen, Cheng; Dai, Guang; Li, Wu-Jun; Yeung, Dit-Yan: Multicategory large margin classification methods: hinge losses vs. coherence functions (2014)
  8. Zhao, Weihua; Zhang, Riquan; Lv, Yazhao; Liu, Jicai: Variable selection for varying dispersion beta regression model (2014)
  9. Bien, Jacob; Taylor, Jonathan; Tibshirani, Robert: A lasso for hierarchical interactions (2013)
  10. Blondel, Mathieu; Seki, Kazuhiro; Uehara, Kuniaki: Block coordinate descent algorithms for large-scale sparse multiclass classification (2013)
  11. Bühlmann, Peter; Rütimann, Philipp; van de Geer, Sara; Zhang, Cun-Hui: Correlated variables in regression: clustering and sparse estimation (2013)
  12. Chu, Eric; Keshavarz, Arezou; Boyd, Stephen: A distributed algorithm for fitting generalized additive models (2013)
  13. Dai, Bin; Ding, Shilin; Wahba, Grace: Multivariate Bernoulli distribution (2013)
  14. Dupuis, Debbie J.; Victoria-Feser, Maria-Pia: Robust VIF regression with application to variable selection in large data sets (2013)
  15. Elliott, Graham; Gargano, Antonio; Timmermann, Allan: Complete subset regressions (2013)
  16. Evans, R. J.; Forcina, A.: Two algorithms for fitting constrained marginal models (2013)
  17. Fellinghauer, Bernd; Bühlmann, Peter; Ryffel, Martin; von Rhein, Michael; Reinhardt, Jan D.: Stable graphical model estimation with random forests for discrete, continuous, and mixed variables (2013)
  18. Gramacy, Robert B.; Taddy, Matt; Wild, Stefan M.: Variable selection and sensitivity analysis using dynamic trees, with an application to computer code performance tuning (2013)
  19. Hirose, Kei; Tateishi, Shohei; Konishi, Sadanori: Tuning parameter selection in sparse regression modeling (2013)
  20. Huang, Jian; Liu, Jin; Ma, Shuangge; Wang, Kai: Accounting for linkage disequilibrium in genome-wide association studies: a penalized regression method (2013)

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