Classification based on depth transvariations

DOI10.1007/S00357-008-9015-7zbMath1276.62039OpenAlexW1999867028MaRDI QIDQ734376

Asuman Turkmen, Sai V. Nudurupati, Nedret Billor, Asheber Abebe

Publication date: 13 October 2009

Published in: Journal of Classification (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00357-008-9015-7

zbMATH Keywords

multivariate ranksdepth functionmisclassification error ratenonparametric classifiertransvariation probabilities

Mathematics Subject Classification ID

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

Related Items (1)

RR-classifier: a nonparametric classification procedure in multidimensional space based on relative ranks

Cites Work

• Multivariate dispersion, central regions and depth. The lift zonoid approach
• On a notion of data depth based on random simplices
• Fast and robust discriminant analysis
• Breakdown properties of location estimates based on halfspace depth and projected outlyingness
• Multivariate analysis by data depth: Descriptive statistics, graphics and inference. (With discussions and rejoinder)
• Linear discriminant analysis and transvariation
• General notions of statistical depth function.
• Comparison between various regression depth methods and the support vector machine to approximate the minimum number of misclassifications
• Clustering and classification based on the L\(_{1}\) data depth
• Projection pursuit discriminant analysis for two groups
• The multivariate L ₁ -median and associated data depth
• A Quality Index Based on Data Depth and Multivariate Rank Tests
• On Maximum Depth and Related Classifiers
• Measuring overlap in binary regression.
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