Open Access
April 2019 Sub-Gaussian estimators of the mean of a random vector
Gábor Lugosi, Shahar Mendelson
Ann. Statist. 47(2): 783-794 (April 2019). DOI: 10.1214/17-AOS1639

Abstract

We study the problem of estimating the mean of a random vector $X$ given a sample of $N$ independent, identically distributed points. We introduce a new estimator that achieves a purely sub-Gaussian performance under the only condition that the second moment of $X$ exists. The estimator is based on a novel concept of a multivariate median.

Citation

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Gábor Lugosi. Shahar Mendelson. "Sub-Gaussian estimators of the mean of a random vector." Ann. Statist. 47 (2) 783 - 794, April 2019. https://doi.org/10.1214/17-AOS1639

Information

Received: 1 February 2017; Revised: 1 July 2017; Published: April 2019
First available in Project Euclid: 11 January 2019

zbMATH: 07033151
MathSciNet: MR3909950
Digital Object Identifier: 10.1214/17-AOS1639

Subjects:
Primary: 62G08 , 62J02
Secondary: 60G25

Keywords: Mean estimation , robust estimation , sub-Gaussian inequalities

Rights: Copyright © 2019 Institute of Mathematical Statistics

Vol.47 • No. 2 • April 2019
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