Open Access
2016 Spatial-sign based high-dimensional location test
Long Feng, Fasheng Sun
Electron. J. Statist. 10(2): 2420-2434 (2016). DOI: 10.1214/16-EJS1176

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.

Citation

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Long Feng. Fasheng Sun. "Spatial-sign based high-dimensional location test." Electron. J. Statist. 10 (2) 2420 - 2434, 2016. https://doi.org/10.1214/16-EJS1176

Information

Received: 1 January 2015; Published: 2016
First available in Project Euclid: 6 September 2016

zbMATH: 1347.62091
MathSciNet: MR3544292
Digital Object Identifier: 10.1214/16-EJS1176

Subjects:
Primary: 62H15
Secondary: 62G35 , 62H11

Keywords: asymptotic normality , High-dimensional data , large $p$, small $n$ , scalar-invariance , spatial median , spatial-sign test

Rights: Copyright © 2016 The Institute of Mathematical Statistics and the Bernoulli Society

Vol.10 • No. 2 • 2016
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