Some high-dimensional one-sample tests based on functions of interpoint distances

JOURNAL OF MULTIVARIATE ANALYSIS

卷:161

Article

Saha, Enakshi¹  Sarkar, Soham²  Ghosh, Anil K.² 

[1] Univ Chicago, Dept Stat, 5747 South Ellis Ave, Chicago, IL 60637 USA

[2] Indian Stat Inst, Theoret Stat & Math Unit, 203,BT Rd, Kolkata 700108, India

关键词: High-dimensional consistency;    HDLSS data;    Rotation invariance;    Scale invariance;   

DOI  :  10.1016/j.jmva.2017.07.006

来源: Elsevier

【 摘 要 】

The multivariate one-sample location problem is well studied in the literature, and several tests are available for it. But most of the existing one-sample tests perform poorly for high dimensional data, and many of them are not even applicable when the dimension of the data exceeds the sample size. In this article, we develop and investigate some nonparametric one-sample tests based on functions of interpoint distances. These proposed tests can be conveniently used in high dimension, low sample size (HDLSS) situations, and good power properties of these tests for HDLSS data have been established using theoretical as well as numerical results. (C) 2017 Elsevier Inc. All rights reserved.

【 授权许可】

Free