Electronic Journal of Statistics

Spatial-sign based high-dimensional location test

Long Feng and Fasheng Sun

Full-text: Open access

Abstract

In this paper, we consider the problem of testing the mean vector in the high-dimensional settings. We proposed a new robust scalar transform invariant test based on spatial sign. The proposed test statistic is asymptotically normal under elliptical distributions. Simulation studies show that our test is very robust and efficient in a wide range of distributions.

Article information

Source
Electron. J. Statist., Volume 10, Number 2 (2016), 2420-2434.

Dates
Received: January 2015
First available in Project Euclid: 6 September 2016

Permanent link to this document
https://projecteuclid.org/euclid.ejs/1473187648

Digital Object Identifier
doi:10.1214/16-EJS1176

Mathematical Reviews number (MathSciNet)
MR3544292

Zentralblatt MATH identifier
1347.62091

Subjects
Primary: 62H15: Hypothesis testing
Secondary: 62H11: Directional data; spatial statistics 62G35: Robustness

Keywords
Asymptotic normality high-dimensional data large $p$, small $n$ spatial median spatial-sign test scalar-invariance

Citation

Feng, Long; Sun, Fasheng. Spatial-sign based high-dimensional location test. Electron. J. Statist. 10 (2016), no. 2, 2420--2434. doi:10.1214/16-EJS1176. https://projecteuclid.org/euclid.ejs/1473187648


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