Variable selection via generalized SELO-penalized linear regression models
From MaRDI portal
Publication:1640691
DOI10.1007/s11766-018-3496-xzbMath1399.62050OpenAlexW2806704369MaRDI QIDQ1640691
Ji-Chang Yu, Yu Ling Jiao, Yue-Yong Shi, Yong-Xiu Cao
Publication date: 14 June 2018
Published in: Applied Mathematics. Series B (English Edition) (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11766-018-3496-x
Asymptotic properties of parametric estimators (62F12) Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05)
Related Items
A primal dual active set with continuation algorithm for high-dimensional nonconvex SICA-penalized regression, Variable selection via generalized SELO-penalized Cox regression models
Uses Software
Cites Work
- Coordinate descent algorithms for nonconvex penalized regression, with applications to biological feature selection
- The group exponential lasso for bi-level variable selection
- Nearly unbiased variable selection under minimax concave penalty
- A unified approach to model selection and sparse recovery using regularized least squares
- The Adaptive Lasso and Its Oracle Properties
- SICA for Cox's proportional hazards model with a diverging number of parameters
- Smoothing methods for nonsmooth, nonconvex minimization
- Enhancing sparsity by reweighted \(\ell _{1}\) minimization
- A primal dual active set with continuation algorithm for the \(\ell^0\)-regularized optimization problem
- Model selection in high-dimensional quantile regression with seamless \(L_0\) penalty
- One-step sparse estimates in nonconcave penalized likelihood models
- Superlinear convergence of smoothing quasi-Newton methods for nonsmooth equations
- Nonconcave penalized likelihood with a diverging number of parameters.
- Calibrating nonconvex penalized regression in ultra-high dimension
- Variable selection and estimation for multivariate panel count data via the seamless-${\it L}_{{\rm 0}}$ penalty
- Variable selection and estimation in generalized linear models with the seamless ${\it L}_{{\rm 0}}$ penalty
- SparseNet: Coordinate Descent With Nonconvex Penalties
- A Selective Overview of Variable Selection in High Dimensional Feature Space (Invited Review Article)
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Local Strong Homogeneity of a Regularized Estimator
- High-Dimensional Sparse Additive Hazards Regression
- Regularization and Variable Selection Via the Elastic Net
- The elements of statistical learning. Data mining, inference, and prediction
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item