Data depth and floating body
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Abstract (arXiv)
Little known relations of the renown concept of the halfspace depth for multivariate data with notions from convex and affine geometry are discussed. Halfspace depth may be regarded as a measure of symmetry for random vectors. As such, the depth stands as a generalization of a measure of symmetry for convex sets, well studied in geometry. Under a mild assumption, the upper level sets of the halfspace depth coincide with the convex floating bodies used in the definition of the affine surface area for convex bodies in Euclidean spaces. These connections enable us to partially resolve some persistent open problems regarding theoretical properties of the depth.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Sep 2018.
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Citing papers per year: 2021: 2; 2022: 1; 2023: 1.
4 papers.
- 2021A Pseudo-Metric between Probability Distributions based on Depth-Trimmed Regionscited by 17
- 2021Tukey Depths and Hamilton-Jacobi Differential Equationscited by 3
- 2023On the quality of randomized approximations of Tukey's depthcited by 2
- 2022Eikonal depth: an optimal control approach to statistical depthscited by 1
- 2023On the quality of randomized approximations of Tukey's depth11 Sep 2023
- 2022Eikonal depth: an optimal control approach to statistical depths14 Jan 2022
- 2021Tukey Depths and Hamilton-Jacobi Differential Equations4 Apr 2021
- 2021A Pseudo-Metric between Probability Distributions based on Depth-Trimmed Regions23 Mar 2021