On the Computation of Symmetrized M-Estimators of Scatter

DOI10.1007/978-81-322-3643-6_8zbMath1356.62067OpenAlexW2549610843WikidataQ109744134 ScholiaQ109744134MaRDI QIDQ2963612

Sara Taskinen, Klaus Nordhausen, Jari Petteri Miettinen, David E. Tyler

Publication date: 15 February 2017

Published in: Recent Advances in Robust Statistics: Theory and Applications (Search for Journal in Brave)

Full work available at URL: http://urn.fi/URN:NBN:fi:jyu-201611224716

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Nonparametric robustness (62G35) Characterization and structure theory for multivariate probability distributions; copulas (62H05)

Related Items (2)

Approximating symmetrized estimators of scatter via balanced incomplete \(U\)-statistics ⋮ Non-Gaussian Component Analysis: Testing the Dimension of the Signal Subspace

Cites Work

• Invariant Co-Ordinate Selection
• New algorithms for \(M\)-estimation of multivariate scatter and location
• On the relation between S-estimators and M-estimators of multivariate location and covariance
• Multivariate generalized S-estimators
• A distribution-free M-estimator of multivariate scatter
• Asymptotic behaviour of S-estimates of multivariate location parameters and dispersion matrices
• Redescending \(M\)-estimates of multivariate location and scatter
• Robust m-estimators of multivariate location and scatter
• Reduced U-statistics and the Hodges-Lehmann estimator
• On Tyler's \(M\)-functional of scatter in high dimension
• \(M\)-functionals of multivariate scatter
• Symmetrised M-estimators of multivariate scatter
• A cautionary note on robust covariance plug-in methods
• Some properties of incomplete U-statistics
• Generalized S-Estimators
• Robust Statistics

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