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Sub-Gaussian estimators of the mean of a random vector

Annals of Statistics (Ann. Stat.), 2017
Gábor Lugosi
Abstract

We study the problem of estimating the mean of a random vector XX given a sample of NN 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 XX exists. The estimator is based on a novel concept of a multivariate median.

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