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Data Depth Contours - a Computational Geometry Perspective
Authors: Rafalin, Eynat; Souvaine, Diane L.
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Data depth is a statistical analysis method that is based on the shape of the data. Depth contours are nested contours that enclose regions with increasing depth. They provide powerful tools to visualize and compare data sets. Several contradicting definitions for depth contours exist in the statistical community. We provide a framework to analyze the competing notions which we term cover and rank. The important contribution of this paper is in analyzing inconsistencies and highlighting the open computational questions raised by the two approaches.

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