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 -dimensional random vector, and multivariate composite alternatives represented as a set of -dimensional means . These include, among others, the set of all distributions with mean in , and the exponential family generated by the null restricted to means in . We show how these optimal e-variables are related to Csisz\'ar-Sanov-Chernoff bounds, first for the case that is convex (these results are not new; we merely reformulate them) and then for the case that `surrounds' the null hypothesis (these results are new).
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}
}
Comments
28 pages