A consistent variable selection method in high-dimensional canonical discriminant analysis

DOI10.1016/j.jmva.2019.104561zbMath1435.62240OpenAlexW2981985559MaRDI QIDQ2293390

Yuya Suzuki, Hirokazu Yanagihara, Ryoya Oda, Yasunori Fujikoshi

Publication date: 5 February 2020

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2019.104561

zbMATH Keywords

consistencyvariable selectioncanonical discriminant analysis

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics in engineering and industry; control charts (62P30)

Related Items (3)

Simultaneous confidence regions and weighted hypotheses on parameter arrays ⋮ Kick-one-out-based variable selection method for Euclidean distance-based classifier in high-dimensional settings ⋮ High-dimensional consistencies of KOO methods in multivariate regression model and discriminant analysis

Uses Software

• msda
• MGSDA

Cites Work

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• High-dimensional consistency of rank estimation criteria in multivariate linear model
• Consistency of log-likelihood-based information criteria for selecting variables in high-dimensional canonical correlation analysis under nonnormality
• Robust rank screening for ultrahigh dimensional discriminant analysis
• A criterion for variable selection in multiple discriminant analysis
• A test for additional information in canonical correlation analysis
• Strong consistency of the information criterion for model selection in multivariate analysis
• Estimating the dimension of a model
• On detection of the number of signals in presence of white noise
• Consistency of test-based method for selection of variables in high-dimensional two-group discriminant analysis
• Support union recovery in high-dimensional multivariate regression
• Conditions for Consistency of a Log-Likelihood-Based Information Criterion in Normal Multivariate Linear Regression Models under the Violation of the Normality Assumption
• Selection of Variables in Multivariate Regression Models for Large Dimensions
• A direct approach to sparse discriminant analysis in ultra-high dimensions
• Multiclass Sparse Discriminant Analysis
• Linear Statistical Inference and its Applications
• A Road to Classification in High Dimensional Space: The Regularized Optimal Affine Discriminant
• TESTS OF SIGNIFICANCE IN MULTIVARIATE ANALYSIS
• Multivariate Statistics
• A new look at the statistical model identification

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