High-Dimensional Hettmansperger-Randles Estimator and its Applications
Methodology
2025-05-06 v1
Abstract
The classic Hettmansperger-Randles Estimator has found extensive use in robust statistical inference. However, it cannot be directly applied to high-dimensional data. In this paper, we propose a high-dimensional Hettmansperger-Randles Estimator for the location parameter and scatter matrix of elliptical distributions in high-dimensional scenarios. Subsequently, we apply these estimators to two prominent problems: the one-sample location test problem and quadratic discriminant analysis. We discover that the corresponding new methods exhibit high effectiveness across a broad range of distributions. Both simulation studies and real-data applications further illustrate the superiority of the newly proposed methods.
Cite
@article{arxiv.2505.01669,
title = {High-Dimensional Hettmansperger-Randles Estimator and its Applications},
author = {Guowei Yan and Long Feng and Xiaoxu Zhang},
journal= {arXiv preprint arXiv:2505.01669},
year = {2025}
}