Concept of data depth and its applications. (English) Zbl 1244.62048

Summary: Data depth is an important concept of nonparametric approaches to multivariate data analysis. The main aim of the paper is to review possible applications of the data depth, including outlier detection, robust and affine-equivariant estimates of location, rank tests for multivariate scale difference, control charts for multivariate processes, and depth-based classifiers solving discrimination problems.


62G05 Nonparametric estimation
62G10 Nonparametric hypothesis testing
62H05 Characterization and structure theory for multivariate probability distributions; copulas
62G35 Nonparametric robustness
62H30 Classification and discrimination; cluster analysis (statistical aspects)
62P30 Applications of statistics in engineering and industry; control charts
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