Robust Variable and Interaction Selection for Logistic Regression and General Index Models

DOI10.1080/01621459.2017.1401541zbMath1478.62170arXiv1611.08649OpenAlexW2706069792WikidataQ99629429 ScholiaQ99629429MaRDI QIDQ5229910

Yang Li, Jun S. Liu

Publication date: 19 August 2019

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1611.08649

zbMATH Keywords

classificationsemiparametrichigh-dimensionalquadratic discriminant analysisstepwise selectionforward screening

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Generalized linear models (logistic models) (62J12) Robustness and adaptive procedures (parametric inference) (62F35)

Related Items (8)

Sparse Learning and Structure Identification for Ultrahigh-Dimensional Image-on-Scalar Regression ⋮ Robust variable selection in the logistic regression model ⋮ BOLT-SSI: A Statistical Approach to Screening Interaction Effects for Ultra-High Dimensional Data ⋮ RaSE: A Variable Screening Framework via Random Subspace Ensembles ⋮ Unified model-free interaction screening via CV-entropy filter ⋮ Unnamed Item ⋮ The Kendall interaction filter for variable interaction screening in high dimensional classification problems ⋮ Structure learning via unstructured kernel-based M-estimation

Uses Software

• rda
• hierNet
• penalizedLDA

Cites Work

• Regularized linear discriminant analysis and its application in microarrays
• A lasso for hierarchical interactions
• Fisher lecture: Dimension reduction in regression
• Variable selection for general index models via sliced inverse regression
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• Estimating the dimension of a model
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• Penalized Classification using Fisher’s Linear Discriminant
• Extended Bayesian information criteria for model selection with large model spaces
• A direct approach to sparse discriminant analysis in ultra-high dimensions
• A Direct Estimation Approach to Sparse Linear Discriminant Analysis
• Sliced Inverse Regression for Dimension Reduction
• Feature Screening via Distance Correlation Learning
• A Model Selection Approach for the Identification of Quantitative Trait Loci in Experimental Crosses
• Empirical Bayes Estimates for Large-Scale Prediction Problems
• Model-Free Variable Selection
• Regularization and Variable Selection Via the Elastic Net
• A Permutation Approach to Testing Interactions for Binary Response by Comparing Correlations Between Classes
• Sparse sufficient dimension reduction
• Correlation Pursuit: Forward Stepwise Variable Selection for Index Models
• Random forests
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