R package ncvreg: Regularization paths for SCAD- and MCP-penalized regression models. Efficient algorithms for fitting regularization paths for linear or logistic regression models penalized by MCP or SCAD, with optional additional L2 penalty (”Mnet”).
Keywords for this software
References in zbMATH (referenced in 9 articles )
Showing results 1 to 9 of 9.
- Belli, Edoardo: Smoothly adaptively centered ridge estimator (2022)
- Dubey, Paromita; Chen, Yaqing; Gajardo, Álvaro; Bhattacharjee, Satarupa; Carroll, Cody; Zhou, Yidong; Chen, Han; Müller, Hans-Georg: Learning delay dynamics for multivariate stochastic processes, with application to the prediction of the growth rate of COVID-19 cases in the United States (2022)
- Amato, Umberto; Antoniadis, Anestis; De Feis, Italia; Gijbels, Irene: Penalised robust estimators for sparse and high-dimensional linear models (2021)
- Chen, Yao; Gao, Qingyi; Liang, Faming; Wang, Xiao: Nonlinear variable selection via deep neural networks (2021)
- Drosou, K.; Koukouvinos, C.; Lappa, A.: Sure independence screening for real medical Poisson data (2019)
- Diego Saldana; Yang Feng: SIS: An R Package for Sure Independence Screening in Ultrahigh-Dimensional Statistical Models (2018) not zbMATH
- Adriano Zambom and Michael Akritas: NonpModelCheck: An R Package for Nonparametric Lack-of-Fit Testing and Variable Selection (2017) not zbMATH
- Daniel F. Schmidt, Enes Makalic: High-Dimensional Bayesian Regularised Regression with the BayesReg Package (2016) arXiv
- Wand, M. P.; Ormerod, J. T.: Penalized wavelets: embedding wavelets into semiparametric regression (2011)