Abstract
The aim of the paper is to show that for data-driven Neyman's statistic large deviation theorem does not hold. We derive an explicit estimate from below for probabilities of large and moderate deviations. The main tool is a version of a lower exponential inequality recently obtained by Mogulskii.
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