The FastHCS algorithm for robust PCA

DOI10.1007/s11222-015-9602-5zbMath1505.62359OpenAlexW1954130270MaRDI QIDQ341142

Eric Schmitt, Kaveh Vakili

Publication date: 16 November 2016

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11222-015-9602-5

zbMATH Keywords

high-dimensional dataexploratory data analysisoutlier detectioncomputational statistics

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Factor analysis and principal components; correspondence analysis (62H25) Estimation in multivariate analysis (62H12) Robustness and adaptive procedures (parametric inference) (62F35)

Related Items (1)

Modal Principal Component Analysis

Uses Software

• R
• lattice
• robustbase
• ROBPCA
• rrcov
• FastPCS

Cites Work

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• Finding multivariate outliers with FastPCS
• The finite sample breakdown point of PCS
• High breakdown estimators for principal components: the projection-pursuit approach revis\-ited
• The influence function of the Stahel-Donoho covariance estimator of smallest outlyingness
• Robust principal component analysis for functional data. (With comments)
• Finite sample breakdown points of projection based multivariate location and scatter statistics
• Principal component analysis.
• Shape bias of robust covariance estimators: an empirical study
• Projection-Pursuit Approach to Robust Dispersion Matrices and Principal Components: Primary Theory and Monte Carlo
• The Structure of Ellipsoidal Distributions, II. Principal Components
• Between-Groups Comparison of Principal Components
• The maximum bias of robust covariances
• Numerical Methods for Computing Angles Between Linear Subspaces
• The Behavior of the Stahel-Donoho Robust Multivariate Estimator
• Robust Statistics

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