REPPlab: An R package for detecting clusters and outliers using exploratory projection pursuit

DOI10.1080/03610918.2019.1626880zbMath1497.62007arXiv1612.06518OpenAlexW2561304564WikidataQ109772893 ScholiaQ109772893MaRDI QIDQ5082787

Anne Ruiz-Gazen, Daniel Fischer, Alain Berro, Klaus Nordhausen

Publication date: 21 June 2022

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1612.06518

zbMATH Keywords

genetic algorithmskurtosisparticle swarm optimizationprojection matrixprojection indextribesunsupervised data analysis

Mathematics Subject Classification ID

Multivariate analysis (62H99) Software, source code, etc. for problems pertaining to statistics (62-04)

Related Items (2)

REPPlab ⋮ Large-sample properties of unsupervised estimation of the linear discriminant using projection pursuit

Uses Software

• GGobi
• R
• ICS
• tourr
• tourrGui
• EPP-lab

Cites Work

• Unnamed Item
• Invariant Co-Ordinate Selection
• Genetic algorithms and particle swarm optimization for exploratory projection pursuit
• A projection pursuit algorithm for anomaly detection in hyperspectral imagery
• Projection pursuit
• Detecting Multivariate Outliers Using Projection Pursuit with Particle Swarm Optimization
• Exploratory Projection Pursuit
• A Projection Pursuit Algorithm for Exploratory Data Analysis
• The Behavior of the Stahel-Donoho Robust Multivariate Estimator
• Visualizing statistical models: Removing the blindfold
• Beyond multidimensional data in model visualization: High‐dimensional and complex nonnumeric data
• Authors' response to discussants
• Analysis of Multivariate and High-Dimensional Data

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