An Extended Projection Data Depth and Its Applications to Discrimination

DOI10.1080/03610920701858396zbMath1143.62037OpenAlexW2018458007MaRDI QIDQ3526081

Guangren Yang, Xia Cui, Lu Lin

Publication date: 24 September 2008

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610920701858396

zbMATH Keywords

discriminant analysisBayes riskmisclassification ratebreakdown points

Mathematics Subject Classification ID

Nonparametric robustness (62G35) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Bayesian inference (62F15)

Related Items (10)

On maximum depth classifiers: depth distribution approach ⋮ Generalized Mahalanobis depth in the reproducing kernel Hilbert space ⋮ Tensor-based projection depth ⋮ On some classifiers based on multivariate ranks ⋮ Local mutual information for dissimilarity-based image segmentation ⋮ DD-Classifier: Nonparametric Classification Procedure Based onDD-Plot ⋮ On general notions of depth for regression ⋮ RR-classifier: a nonparametric classification procedure in multidimensional space based on relative ranks ⋮ On rank distribution classifiers for high-dimensional data ⋮ Nonparametrically consistent depth-based classifiers

Cites Work

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• General notions of statistical depth function.
• Structural properties and convergence results for contours of sample statistical depth functions.
• 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
• On the Stahel-Donoho estimator and depth-weighted means of multivariate data.
• Robust depth-weighted wavelet for nonparametric regression models
• 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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