A Computational Perspective on Projection Pursuit in High Dimensions: Feasible or Infeasible Feature Extraction

DOI10.1111/insr.12517WikidataQ114080822 ScholiaQ114080822MaRDI QIDQ6089883

Jimin Ye, Chunming Zhang, Xiao-Mei Wang

Publication date: 15 December 2023

Published in: International Statistical Review (Search for Journal in Brave)

zbMATH Keywords

Gaussian mixturedensity estimationempirical distribution functionexploratory data analysisPCAICA

Mathematics Subject Classification ID

Statistics (62-XX) Multivariate analysis (62Hxx) Nonparametric inference (62Gxx)

Cites Work

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• Projection pursuit exploratory data analysis
• Projection pursuit
• A limit theorem for the norm of random matrices
• A multivariate Kolmogorov-Smirnov test of goodness of fit
• Model-based clustering of high-dimensional data: a review
• Skewness-based projection pursuit: a computational approach
• Bump hunting with non-Gaussian kernels
• Principal component analysis.
• Maximum independent component analysis with application to EEG data
• Asymptotics of graphical projection pursuit
• Principal component analysis: a review and recent developments
• A multivariate skew-garch model
• Projection pursuit for discrete data
• Smallest singular value of a random rectangular matrix
• What is Projection Pursuit?
• Exploratory Projection Pursuit
• Asymptotic Statistics
• Three-Dimensional Projection Pursuit
• A Projection Pursuit Algorithm for Exploratory Data Analysis
• Projection pursuit in high dimensions

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