Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10327426 | Computational Geometry | 2013 | 8 Pages |
Abstract
Oja depth (Oja 1983) is a generalization of the median to multivariate data that measures the centrality of a point x with respect to a set S of points in such a way that points with smaller Oja depth are more central with respect to S. Two relationships involving Oja depth and centers of mass are presented. The first is a form of Centerpoint Theorem which shows that the center of mass of the convex hull of a point set has low Oja depth. The second is an approximation result which shows that the center of mass of a point set approximates a point of minimum Oja depth.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Dan Chen, Olivier Devillers, John Iacono, Stefan Langerman, Pat Morin,