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 415 articles , 1 standard article )

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  1. Bertsimas, Dimitris; van Parys, Bart: Sparse high-dimensional regression: exact scalable algorithms and phase transitions (2020)
  2. Boehmke, Brad; Greenwell, Brandon M.: Hands-on machine learning with R (2020)
  3. Cao, Xuan; Khare, Kshitij; Ghosh, Malay: High-dimensional posterior consistency for hierarchical non-local priors in regression (2020)
  4. Choiruddin, Achmad; Cuevas-Pacheco, Francisco; Coeurjolly, Jean-François; Waagepetersen, Rasmus: Regularized estimation for highly multivariate log Gaussian Cox processes (2020)
  5. Fan, Jianqing; Ke, Yuan; Wang, Kaizheng: Factor-adjusted regularized model selection (2020)
  6. Feng, Yang; Liu, Qingfeng; Okui, Ryo: On the sparsity of Mallows model averaging estimator (2020)
  7. Furmańczyk, Konrad; Rejchel, Wojciech: High-dimensional linear model selection motivated by multiple testing (2020)
  8. Huang, Yimin; Kong, Xiangshun; Ai, Mingyao: Optimal designs in sparse linear models (2020)
  9. Lai, Yuanhao; McLeod, Ian: Ensemble quantile classifier (2020)
  10. Liu, Wenchen; Tang, Yincai; Wu, Xianyi: Separating variables to accelerate non-convex regularized optimization (2020)
  11. Oda, Ryoya; Yanagihara, Hirokazu: A fast and consistent variable selection method for high-dimensional multivariate linear regression with a large number of explanatory variables (2020)
  12. Pang, Tongyao; Wu, Chunlin; Liu, Zhifang: A cubic spline penalty for sparse approximation under tight frame balanced model (2020)
  13. Pan, Yuqing; Mai, Qing: Efficient computation for differential network analysis with applications to quadratic discriminant analysis (2020)
  14. Posch, Konstantin; Arbeiter, Maximilian; Pilz, Juergen: A novel Bayesian approach for variable selection in linear regression models (2020)
  15. Rachael C. Aikens, Joseph Rigdon, Justin Lee, Michael Baiocchi, Jonathan Chen: Stratified Pilot Matching in R: The stratamatch Package (2020) arXiv
  16. Ren, Sheng; Kang, Emily L.; Lu, Jason L.: MCEN: a method of simultaneous variable selection and clustering for high-dimensional multinomial regression (2020)
  17. Sayan Putatunda, Dayananda Ubrangala, Kiran Rama, Ravi Kondapalli: DriveML: An R Package for Driverless Machine Learning (2020) arXiv
  18. Schmid, Matthias; Welchowski, Thomas; Wright, Marvin N.; Berger, Moritz: Discrete-time survival forests with Hellinger distance decision trees (2020)
  19. Tang, Lu; Zhou, Ling; Song, Peter X.-K.: Distributed simultaneous inference in generalized linear models via confidence distribution (2020)
  20. Tardivel, Patrick J. C.; Servien, Rémi; Concordet, Didier: Simple expressions of the Lasso and SLOPE estimators in low-dimension (2020)

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