Feature Selection by Canonical Correlation Search in High-Dimensional Multiresponse Models With Complex Group Structures

DOI10.1080/01621459.2019.1609972zbMath1441.62142OpenAlexW2943399556WikidataQ127945736 ScholiaQ127945736MaRDI QIDQ5120660

Zehua Chen, Shan Luo

Publication date: 15 September 2020

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

Full work available at URL: https://doi.org/10.1080/01621459.2019.1609972

zbMATH Keywords

group structurecanonical correlationfeature selectionsequential procedurehigh-dimensionalmultiresponse model

Mathematics Subject Classification ID

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

Related Items

Group linear algorithm with sparse principal decomposition: a variable selection and clustering method for generalized linear models, Conditional characteristic feature screening for massive imbalanced data, A sequential approach to feature selection in high-dimensional additive models, Interaction screening via canonical correlation

Uses Software

• glasso

Cites Work

• Unnamed Item
• Nearly unbiased variable selection under minimax concave penalty
• The Adaptive Lasso and Its Oracle Properties
• A stepwise regression method and consistent model selection for high-dimensional sparse linear models
• Group variable selection via a hierarchical lasso and its oracle property
• Regularized multivariate regression for identifying master predictors with application to integrative genomics study of breast cancer
• Least angle regression. (With discussion)
• Interaction pursuit in high-dimensional multi-response regression via distance correlation
• Support union recovery in high-dimensional multivariate regression
• Boosting for high-dimensional linear models
• Logistic Bayesian LASSO for Identifying Association with Rare Haplotypes and Application to Age-Related Macular Degeneration
• Forward Regression for Ultra-High Dimensional Variable Screening
• Extended Bayesian information criteria for model selection with large model spaces
• Multivariate sparse group lasso for the multivariate multiple linear regression with an arbitrary group structure
• Greed is Good: Algorithmic Results for Sparse Approximation
• A group bridge approach for variable selection
• Penalized logistic regression for detecting gene interactions
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Feature Screening via Distance Correlation Learning
• Sparse Reduced-Rank Regression for Simultaneous Dimension Reduction and Variable Selection
• Sequential Lasso Cum EBIC for Feature Selection With Ultra-High Dimensional Feature Space
• Dimension Reduction and Coefficient Estimation in Multivariate Linear Regression
• Orthogonal Matching Pursuit for Sparse Signal Recovery With Noise
• Model Selection and Estimation in Regression with Grouped Variables