On sufficient variable screening using log odds ratio filter

DOI10.1214/21-EJS1951zbMath1493.62181OpenAlexW4206183683MaRDI QIDQ2136614

Wenbo Wu, Xiangrong Yin, Baoying Yang

Publication date: 11 May 2022

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/journals/electronic-journal-of-statistics/volume-16/issue-1/On-sufficient-variable-screening-using-log-odds-ratio-filter/10.1214/21-EJS1951.full

zbMATH Keywords

dependence measuresfeature screeningsufficient variable screening

Mathematics Subject Classification ID

Nonparametric estimation (62G05) General nonlinear regression (62J02) Sufficiency and information (62B99)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Measuring and testing dependence by correlation of distances
• 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
• Marginal empirical likelihood and sure independence feature screening
• Robust rank correlation based screening
• Successive direction extraction for estimating the central subspace in a multiple-index regres\-sion
• High-dimensional classification using features annealed independence rules
• Quantile-adaptive model-free variable screening for high-dimensional heterogeneous data
• Sufficient variable selection using independence measures for continuous response
• The cumulative Kolmogorov filter for model-free screening in ultrahigh dimensional data
• The fused Kolmogorov filter: a nonparametric model-free screening method
• Nonparametric Independence Screening in Sparse Ultra-High-Dimensional Additive Models
• On varying-coefficient independence screening for high-dimensional varying-coefficient models
• Graphics for Regressions With a Binary Response
• 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
• Fused Estimators of the Central Subspace in Sufficient Dimension Reduction
• Nonparametric Independence Screening in Sparse Ultra-High-Dimensional Varying Coefficient Models
• Model-Free Feature Screening for Ultrahigh Dimensional Discriminant Analysis
• Sequential Sufficient Dimension Reduction for Large p, Small n Problems
• The Kolmogorov filter for variable screening in high-dimensional binary classification
• Sufficient Dimension Reduction via Inverse Regression

This page was built for publication: On sufficient variable screening using log odds ratio filter