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 461 articles , 1 standard article )

Showing results 1 to 20 of 461.
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  1. Augugliaro, Luigi; Sottile, Gianluca; Vinciotti, Veronica: The conditional censored graphical Lasso estimator (2020)
  2. Bertsimas, Dimitris; van Parys, Bart: Sparse high-dimensional regression: exact scalable algorithms and phase transitions (2020)
  3. Boehmke, Brad; Greenwell, Brandon M.: Hands-on machine learning with R (2020)
  4. Canhong Wen, Aijun Zhang, Shijie Quan, Xueqin Wang: BeSS: An R Package for Best Subset Selection in Linear, Logistic and Cox Proportional Hazards Models (2020) not zbMATH
  5. Cao, Xuan; Khare, Kshitij; Ghosh, Malay: High-dimensional posterior consistency for hierarchical non-local priors in regression (2020)
  6. Chavez, Gordon V.: Dynamic tail inference with log-Laplace volatility (2020)
  7. Chen, Kedong; Li, William; Wang, Sijian: An easy-to-implement hierarchical standardization for variable selection under strong heredity constraint (2020)
  8. Choiruddin, Achmad; Cuevas-Pacheco, Francisco; Coeurjolly, Jean-François; Waagepetersen, Rasmus: Regularized estimation for highly multivariate log Gaussian Cox processes (2020)
  9. Dai, Yutong; Weng, Yang: Synchronous parallel block coordinate descent method for nonsmooth convex function minimization (2020)
  10. Fan, Jianqing; Ke, Yuan; Wang, Kaizheng: Factor-adjusted regularized model selection (2020)
  11. Feng, Yang; Liu, Qingfeng; Okui, Ryo: On the sparsity of Mallows model averaging estimator (2020)
  12. Furmańczyk, Konrad; Rejchel, Wojciech: High-dimensional linear model selection motivated by multiple testing (2020)
  13. García-Portugués, Eduardo; Álvarez-Liébana, Javier; Álvarez-Pérez, Gonzalo; González-Manteiga, Wenceslao: Goodness-of-fit tests for functional linear models based on integrated projections (2020)
  14. Gold, David; Lederer, Johannes; Tao, Jing: Inference for high-dimensional instrumental variables regression (2020)
  15. Guo, Xiao; Zhang, Hai: Sparse directed acyclic graphs incorporating the covariates (2020)
  16. Huang, Yimin; Kong, Xiangshun; Ai, Mingyao: Optimal designs in sparse linear models (2020)
  17. James, Gareth M.; Paulson, Courtney; Rusmevichientong, Paat: Penalized and constrained optimization: an application to high-dimensional website advertising (2020)
  18. Jeon, Jong-June; Kim, Yongdai; Won, Sungho; Choi, Hosik: Primal path algorithm for compositional data analysis (2020)
  19. Lai, Yuanhao; McLeod, Ian: Ensemble quantile classifier (2020)
  20. Liu, Wenchen; Tang, Yincai; Wu, Xianyi: Separating variables to accelerate non-convex regularized optimization (2020)

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