Variable selection using penalized empirical likelihood
type: Item
instance of: scholarly article
title: Variable selection using penalized empirical likelihood
zbMATH Open document ID: 1234.62030
published in: Science China. Mathematics
publication date: 2012-03-29T00:00:00Z
Mathematics Subject Classification ID: 62G05
Mathematics Subject Classification ID: 62F07
Mathematics Subject Classification ID: 65C60
zbMATH DE Number: 6019644
zbMATH Keywords: EmBIC
zbMATH Keywords: moment restrictions
zbMATH Keywords: oracle property
zbMATH Keywords: PEL
zbMATH Keywords: SCAD
zbMATH Keywords: tuning parameters
author: Yunwen Ren
author: Xinsheng Zhang
describes a project that uses: ElemStatLearn
MaRDI profile type: Publication
full work available at URL: s11425-011-4231-8
OpenAlex ID: W2009215228
cites work: Q4769776
cites work: Heuristics of instability and stabilization in model selection
cites work: Discussion: One-step sparse estimates in nonconcave penalized likelihood models
cites work: Variable selection for multivariate failure time data
cites work: The Dantzig selector: statistical estimation when \(p\) is much larger than \(n\). (With discussions and rejoinder).
cites work: Least angle regression. (With discussion)
cites work: Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
cites work: Variable selection for Cox's proportional hazards model and frailty model
cites work: New Estimation and Model Selection Procedures for Semiparametric Modeling in Longitudinal Data Analysis
cites work: Q5491004
cites work: Nonconcave penalized likelihood with a diverging number of parameters.
cites work: Q3125064
cites work: The risk inflation criterion for multiple regression
cites work: A Statistical View of Some Chemometrics Regression Tools
cites work: A decision-theoretic generalization of on-line learning and an application to boosting
cites work: The elements of statistical learning. Data mining, inference, and prediction
cites work: Least angle and \(\ell _{1}\) penalized regression: a review
cites work: Variable selection using MM algorithms
cites work: Variable Selection in Finite Mixture of Regression Models
cites work: Variable selection in semiparametric regression modeling
cites work: A unified approach to model selection and sparse recovery using regularized least squares
cites work: Empirical likelihood ratio confidence intervals for a single functional
cites work: Empirical likelihood ratio confidence regions
cites work: Empirical likelihood for linear models
cites work: Empirical likelihood and general estimating equations
cites work: Estimating the dimension of a model
cites work: Q4864293
cites work: Empirical likelihood based variable selection
cites work: Unified LASSO Estimation by Least Squares Approximation
cites work: Tuning parameter selectors for the smoothly clipped absolute deviation method
cites work: Weighted Wilcoxon‐Type Smoothly Clipped Absolute Deviation Method
cites work: Model Selection and Estimation in Regression with Grouped Variables
cites work: Nearly unbiased variable selection under minimax concave penalty
cites work: The Adaptive Lasso and Its Oracle Properties
cites work: Regularization and Variable Selection Via the Elastic Net
cites work: One-step sparse estimates in nonconcave penalized likelihood models
DOI: 10.1007/S11425-011-4231-8
description: scientific article; zbMATH DE number 6019644