A fast adaptive Lasso for the cox regression via safe screening rules
From MaRDI portal
Publication:3389652
DOI10.1080/00949655.2021.1914043OpenAlexW3154741497MaRDI QIDQ3389652
No author found.
Publication date: 23 March 2022
Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00949655.2021.1914043
Uses Software
Cites Work
- Unnamed Item
- The Adaptive Lasso and Its Oracle Properties
- Variable selection for survival data with a class of adaptive elastic net techniques
- Oracle inequalities for the lasso in the Cox model
- Robust rank correlation based screening
- Principled sure independence screening for Cox models with ultra-high-dimensional covariates
- Feature selection of ultrahigh-dimensional covariates with survival outcomes: a selective review
- Robust feature screening for ultra-high dimensional right censored data via distance correlation
- Conditional screening for ultra-high dimensional covariates with survival outcomes
- Variable selection for Cox's proportional hazards model and frailty model
- Safe feature screening rules for the regularized Huber regression
- On the robustness of the adaptive lasso to model misspecification
- Elastic net for Cox’s proportional hazards model with a solution path algorithm
- Sure Independence Screening for Ultrahigh Dimensional Feature Space
- Feature Screening via Distance Correlation Learning
- A Survey of L1 Regression
- Consistent Estimation of the Expected Brier Score in General Survival Models with Right‐Censored Event Times
- High-Dimensional Variable Selection for Survival Data
- Variable selection by ensembles for the Cox model
- Regularization and Variable Selection Via the Elastic Net
- High Dimensional Ordinary Least Squares Projection for Screening Variables
- Adaptive Lasso for Cox's proportional hazards model
This page was built for publication: A fast adaptive Lasso for the cox regression via safe screening rules
