Dynamic linear discriminant analysis in high dimensional space

DOI10.3150/19-BEJ1154zbMath1466.62352arXiv1708.00205OpenAlexW3003536703MaRDI QIDQ2295032

Binyan Jiang, Chenlei Leng, Zi-Qi Chen

Publication date: 12 February 2020

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1708.00205

zbMATH Keywords

discriminant analysiskernel estimationhigh-dimensional datasparsityBayes ruledynamic linear programming

Mathematics Subject Classification ID

Density estimation (62G07) Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items

A self-calibrated direct approach to precision matrix estimation and linear discriminant analysis in high dimensions, Variable-dependent partial dimension reduction, Multiclass sparse discriminant analysis incorporating graphical structure among predictors, Varying coefficient linear discriminant analysis for dynamic data, Tuning selection for two-scale kernel density estimators

Uses Software

• penalizedLDA
• msda

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Two sample tests for high-dimensional covariance matrices
• High dimensional discrimination analysis via a semiparametric model
• Sparse linear discriminant analysis by thresholding for high dimensional data
• Choice of neighbor order in nearest-neighbor classification
• Optimal rates of convergence for covariance matrix estimation
• Some theory for Fisher's linear discriminant function, `naive Bayes', and some alternatives when there are many more variables than observations
• The location model for mixtures of categorical and continuous variables
• Confidence intervals for high-dimensional linear regression: minimax rates and adaptivity
• Innovated interaction screening for high-dimensional nonlinear classification
• Optimal classification in sparse Gaussian graphic model
• The Dantzig selector: statistical estimation when \(p\) is much larger than \(n\). (With discussions and rejoinder).
• QUADRO: a supervised dimension reduction method via Rayleigh quotient optimization
• Convergence of estimates under dimensionality restrictions
• Uniform in bandwidth consistency of kernel-type function estimators
• Bernstein inequality and moderate deviations under strong mixing conditions
• Penalized Classification using Fisher’s Linear Discriminant
• Joint estimation of multiple graphical models
• A direct approach to sparse discriminant analysis in ultra-high dimensions
• A Direct Estimation Approach to Sparse Linear Discriminant Analysis
• The Efficiency of Logistic Regression Compared to Normal Discriminant Analysis
• Choosing Between Logistic Regression and Discriminant Analysis
• Discriminant analysis through a semiparametric model
• A New Reduced-Rank Linear Discriminant Analysis Method and Its Applications
• Multiclass Sparse Discriminant Analysis
• Sparsifying the Fisher Linear Discriminant by Rotation
• A Road to Classification in High Dimensional Space: The Regularized Optimal Affine Discriminant
• Probability Inequalities
• Multivariate Local Polynomial Kernel Estimators: Leading Bias and Asymptotic Distribution
• Introduction to nonparametric estimation