High-Dimensional Hettmansperger-Randles Estimator and its Applications

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autori principali: Yan, Guowei, Feng, Long, Zhang, Xiaoxu
Natura: Preprint
Pubblicazione: 2025
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866913817138561024
author Yan, Guowei
Feng, Long
Zhang, Xiaoxu
author_facet Yan, Guowei
Feng, Long
Zhang, Xiaoxu
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2505_01669
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle High-Dimensional Hettmansperger-Randles Estimator and its Applications
Yan, Guowei
Feng, Long
Zhang, Xiaoxu
Methodology
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.
title High-Dimensional Hettmansperger-Randles Estimator and its Applications
topic Methodology
url https://arxiv.org/abs/2505.01669