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Sub-Gaussian estimators of the mean of a random vector

1 February 2017
Gábor Lugosi
S. Mendelson
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Abstract

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

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