Screen then select: a strategy for correlated predictors in high-dimensional quantile regression

Computational methods for problems pertaining to statistics (62-08) Nonparametric regression and quantile regression (62G08) Ridge regression; shrinkage estimators (Lasso) (62J07)

Cites Work

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Model-Free Feature Screening for Ultrahigh-Dimensional Data
Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
Nearly unbiased variable selection under minimax concave penalty
Statistics for high-dimensional data. Methods, theory and applications.
Robust model-free feature screening via quantile correlation
A strongly consistent information criterion for linear model selection based on \(M\)-estimation
Quantile-adaptive model-free variable screening for high-dimensional heterogeneous data
Quantile regression feature selection and estimation with grouped variables using Huber approximation
A general framework for ADMM acceleration
Screening and selection for quantile regression using an alternative measure of variable importance
An extended variable inclusion and shrinkage algorithm for correlated variables
Adaptive robust variable selection
Generalized alternating direction method of multipliers: new theoretical insights and applications
Forward Regression for Ultra-High Dimensional Variable Screening
Regression Quantiles
Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
Goodness of Fit and Related Inference Processes for Quantile Regression
Sure Independence Screening for Ultrahigh Dimensional Feature Space
Feature Screening via Distance Correlation Learning
Model Selection via Bayesian Information Criterion for Quantile Regression Models
Prior Knowledge Guided Ultra-High Dimensional Variable Screening With Application to Neuroimaging Data
Model-Free Forward Screening Via Cumulative Divergence
Conditional quantile screening in ultrahigh-dimensional heterogeneous data
Regularization and Variable Selection Via the Elastic Net
High Dimensional Ordinary Least Squares Projection for Screening Variables
Ridge Regression: Biased Estimation for Nonorthogonal Problems
Model-Free Feature Screening and FDR Control With Knockoff Features
Forward variable selection for ultra-high dimensional quantile regression models
Ridge Regularization: An Essential Concept in Data Science

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