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Growth-Optimal E-Variables and an extension to the multivariate Csisz\'ar-Sanov-Chernoff Theorem

Information Theory 2024-12-30 v2 math.IT Statistics Theory Statistics Theory

Abstract

We consider growth-optimal e-variables with maximal e-power, both in an absolute and relative sense, for simple null hypotheses for a dd-dimensional random vector, and multivariate composite alternatives represented as a set of dd-dimensional means \meanspace1\meanspace_1. These include, among others, the set of all distributions with mean in \meanspace1\meanspace_1, and the exponential family generated by the null restricted to means in \meanspace1\meanspace_1. We show how these optimal e-variables are related to Csisz\'ar-Sanov-Chernoff bounds, first for the case that \meanspace1\meanspace_1 is convex (these results are not new; we merely reformulate them) and then for the case that \meanspace1\meanspace_1 `surrounds' the null hypothesis (these results are new).

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Cite

@article{arxiv.2412.17554,
  title  = {Growth-Optimal E-Variables and an extension to the multivariate Csisz\'ar-Sanov-Chernoff Theorem},
  author = {Peter Grünwald and Yunda Hao and Akshay Balsubramani},
  journal= {arXiv preprint arXiv:2412.17554},
  year   = {2024}
}

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28 pages