Half-Region Depth for Stochastic Processes
Statistics Theory
2014-01-24 v1 Statistics Theory
Abstract
We study the concept of half-region depth, introduced by Lopez-Pintado and Romo in 2011. We show that for a wide variety of standard stochastic processes, such as Brownian motion and other symmetric stable processes with stationary independent increments tied down at 0, half-region depth assigns depth zero to all sample functions. To alleviate this difficulty we introduce a method of smoothing, which often not only eliminates the problem of zero depth, but allows us to extend the theoretical results on consistency in that paper up to the level for many smoothed processes.
Cite
@article{arxiv.1401.5817,
title = {Half-Region Depth for Stochastic Processes},
author = {James Kuelbs and Joel Zinn},
journal= {arXiv preprint arXiv:1401.5817},
year = {2014}
}