Generalized regression estimators with concave penalties and a comparison to lasso type estimators

Cites Work

Unnamed Item
Unnamed Item
Unnamed Item
Unnamed Item
Unnamed Item
Coordinate descent algorithms for nonconvex penalized regression, with applications to biological feature selection
A survey of bootstrap methods in finite population sampling
Nearly unbiased variable selection under minimax concave penalty
The Adaptive Lasso and Its Oracle Properties
Group coordinate descent algorithms for nonconvex penalized regression
Asymptotic normality and the bootstrap in stratified sampling
SCAD-penalized regression in high-dimensional partially linear models
Inference from stratified samples: Properties of the linearization, jackknife and balanced repeated replication methods
Model assisted survey sampling.
Local polynomial regresssion estimators in survey sampling.
Asymptotics for Lasso-type estimators.
Variable selection in linear mixed effects models
High-dimensional variable selection via low-dimensional adaptive learning
Asymptotic efficiency of the calibration estimator in a high-dimensional data setting
Penalized Generalized Estimating Equations for High-Dimensional Longitudinal Data Analysis
A Selective Overview of Variable Selection in High Dimensional Feature Space (Invited Review Article)
SCAD-Penalized Least Absolute Deviation Regression in High-Dimensional Models
An elimination procedure for unequal probability sampling without replacement
Some results on generalized difference estimation and generalized regression estimation for finite populations
Bootstrap Methods for Finite Populations
Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
Comments on «Wavelets in statistics: A review» by A. Antoniadis
Generalized Regression Estimators with High-Dimensional Covariates
Robust and consistent variable selection in high-dimensional generalized linear models
Variable Selection in Nonparametric Varying-Coefficient Models for Analysis of Repeated Measurements
Smoothly Clipped Absolute Deviation on High Dimensions
Asymptotic Theory of Rejective Sampling with Varying Probabilities from a Finite Population
A Generalization of Sampling Without Replacement From a Finite Universe
Group descent algorithms for nonconvex penalized linear and logistic regression models with grouped predictors
A selective review of group selection in high-dimensional models
Sparse and robust estimation with ridge minimax concave penalty
Spatial heterogeneity automatic detection and estimation

This page was built for publication: Generalized regression estimators with concave penalties and a comparison to lasso type estimators