Depth-based classification method underlain by a remote concentration measure for processing asymmetric data

DOI10.1007/s10559-016-9839-9zbMath1349.62265OpenAlexW2408422562MaRDI QIDQ334243

O. A. Galkin

Publication date: 1 November 2016

Published in: Cybernetics and Systems Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10559-016-9839-9

zbMATH Keywords

depth functionmulti-dimensional classificationremote concentration measure

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Cites Work

• Fast nonparametric classification based on data depth
• Wavelets in functional data analysis: estimation of multidimensional curves and their derivatives
• Smooth depth contours characterize the underlying distribution
• Characterizing angular symmetry and regression symmetry.
• High-dimensional computation of the deepest location.
• Structural properties and convergence results for contours of sample statistical depth functions.
• Continuity of halfspace depth contours and maximum depth estimators: Diagnostics of depth-related methods
• Optimal signed-rank tests based on hyperplanes
• Influence function of halfspace depth

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