Robust conditional nonparametric independence screening for ultrahigh-dimensional data

DOI10.1016/j.spl.2018.08.003zbMath1414.62140OpenAlexW2885946079MaRDI QIDQ1726739

Jing Pan, Shucong Zhang, Yong Zhou

Publication date: 20 February 2019

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2018.08.003

zbMATH Keywords

sure screening propertyfeature screeningsemivarying coefficient modelsultrahigh-dimensional models

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Factor analysis and principal components; correspondence analysis (62H25) Nonparametric robustness (62G35)

Uses Software

• KernSmooth

Cites Work

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• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Sure Independence Screening Adjusted for Confounding Covariates with Ultrahigh-dimensional Data
• Sure Independence Screening for Ultrahigh Dimensional Feature Space
• Feature Screening via Distance Correlation Learning
• Feature Selection for Varying Coefficient Models With Ultrahigh-Dimensional Covariates
• Nonparametric Independence Screening in Sparse Ultra-High-Dimensional Varying Coefficient Models