Reducing data dimension for cluster detection

DOI10.1080/00949655.2012.679032zbMath1453.62547OpenAlexW1968683741MaRDI QIDQ5218933

Nicola Torelli, Giovanna Menardi

Publication date: 6 March 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2012.679032

zbMATH Keywords

dimension reductioncluster analysiskernel estimatorprojection pursuitcritical bandwidth

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items (2)

A Review on Modal Clustering ⋮ An advancement in clustering via nonparametric density estimation

Uses Software

• R
• pdfCluster

Cites Work

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• Estimating the Number of Clusters in a Data Set Via the Gap Statistic
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• Projection pursuit exploratory data analysis
• Clustering and disjoint principal component analysis
• Pair-perturbation influence functions of nongaussianity by projection pursuit
• Projection pursuit
• Principal component analysis.
• Influence analysis of non-Gaussianity by applying projection pursuit
• On polynomial-based projection indices for exploratory projection pursuit
• On Using Principal Components Before Separating a Mixture of Two Multivariate Normal Distributions
• What is Projection Pursuit?
• Exploratory Projection Pursuit
• On the Use of Discriminant Functions in Taxonomy
• Three-Dimensional Projection Pursuit
• Model-Based Clustering, Discriminant Analysis, and Density Estimation
• Nonlinear Dimensionality Reduction
• Factorial \(k\)-means analysis for two-way data.

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