Regression Depth and Center Points

Nina Amenta, Marshall W. Bern, David Eppstein, Shang-Hua Teng

Abstract: We show that, for any set of n points in d dimensions, there exists a hyperplane with regression depth at least \(\lceil n/(d+1)\rceil\) , as had been conjectured by Rousseeuw and Hubert. Dually, for any arrangement of n hyperplanes in d dimensions there exists a point that cannot escape to infinity without crossing at least \(\lceil n/(d+1)\rceil\) hyperplanes. We also apply our approach to related questions on the existence of partitions of the data into subsets such that a common plane has nonzero regression depth in each subset, and to the computational complexity of regression depth problems.