Model-free conditional independence feature screening for ultrahigh dimensional data

DOI10.1007/s11425-016-0186-8OpenAlexW2561010651WikidataQ38709602 ScholiaQ38709602MaRDI QIDQ1702189

LuHeng Wang, Yong Li, Run-Ze Li, Jingyuan Liu

Publication date: 28 February 2018

Published in: Science China. Mathematics (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc5480220

zbMATH Keywords

high-dimensional datavariable selectionfeature screeningconditional feature screening

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Measures of association (correlation, canonical correlation, etc.) (62H20)

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Model-free survival conditional feature screening, Robust Feature Screening via Distance Correlation for Ultrahigh Dimensional Data With Responses Missing at Random, Conditional-quantile screening for ultrahigh-dimensional survival data via martingale difference correlation, Quantile screening for ultra-high-dimensional heterogeneous data conditional on some variables

Cites Work

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• Model-Free Feature Screening for Ultrahigh-Dimensional Data
• Sure independence screening in generalized linear models with NP-dimensionality
• The Adaptive Lasso and Its Oracle Properties
• Robust rank correlation based screening
• A selective overview of feature screening for ultrahigh-dimensional data
• Weak convergence and empirical processes. With applications to statistics
• Asymptotic properties of bridge estimators in sparse high-dimensional regression models
• The Dantzig selector: statistical estimation when \(p\) is much larger than \(n\). (With discussions and rejoinder).
• Nonparametric Independence Screening in Sparse Ultra-High-Dimensional Additive Models
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Sure Independence Screening for Ultrahigh Dimensional Feature Space
• Feature Screening via Distance Correlation Learning
• Feature Selection for Varying Coefficient Models With Ultrahigh-Dimensional Covariates
• The Sparse MLE for Ultrahigh-Dimensional Feature Screening
• Nonparametric Independence Screening in Sparse Ultra-High-Dimensional Varying Coefficient Models
• Regularization and Variable Selection Via the Elastic Net
• Probability Inequalities for Sums of Bounded Random Variables
• Model-Free Feature Screening for Ultrahigh Dimensional Discriminant Analysis
• The Kolmogorov filter for variable screening in high-dimensional binary classification