RDELA -- a Delaunay-triangulation-based, location and covariance estimator with high breakdown point

DOI10.1007/s11222-012-9337-5zbMath1322.62152OpenAlexW2073263596MaRDI QIDQ746340

Steffen Liebscher, Claudia Becker, Thomas Kirschstein

Publication date: 16 October 2015

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

Full work available at URL: https://doi.org/10.1007/s11222-012-9337-5

zbMATH Keywords

Delaunay triangulationbreakdown pointrobust estimationminimum covariance determinant

Mathematics Subject Classification ID

Related Items (1)

Efficiency of the pMST and RDELA location and scatter estimators

Uses Software

• DeWall
• AS 78
• robustbase

Cites Work

• Robust estimation of location and scatter by pruning the minimum spanning tree
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• Asymptotic behaviour of S-estimates of multivariate location parameters and dispersion matrices
• The asymptotics of Rousseeuw's minimum volume ellipsoid estimator
• DeWall: a fast divide and conquer Delaunay triangulation algorithm in \(E^d\).
• Exploring multivariate data with the forward search.
• Asymptotics of reweighted estimators of multivariate location and scatter
• Robustness properties of \(S\)-estimators of multivariate location and shape in high dimension
• A comparison of sequential Delaunay triangulation algorithms.
• Addendum to the discussion of ``Breakdown and groups
• Breakdown and groups. (With discussions and rejoinder)
• Finding an Unknown Number of Multivariate Outliers
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• Complexity of the delaunay triangulation of points on surfaces the smooth case
• Robust Statistics
• The maximum numbers of faces of a convex polytope
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