On the Second-Order Asymptotics of the Hoeffding Test and Other Divergence Tests
<|reference_start|>On the Second-Order Asymptotics of the Hoeffding Test and Other Divergence Tests: Consider a binary statistical hypothesis testing problem, where $n$ independent and identically distributed random variables $Z^n$ are either distributed according to the null hypothesis $P$ or the alternative hypothesis $Q$, and only $P$ is known. A well-known test that is suitable for this case is the so-called Hoeffding test, which accepts $P$ if the Kullback-Leibler (KL) divergence between the empirical distribution of $Z^n$ and $P$ is below some threshold. This work characterizes the first and second-order terms of the type-II error probability for a fixed type-I error probability for the Hoeffding test as well as for divergence tests, where the KL divergence is replaced by a general divergence. It is demonstrated that, irrespective of the divergence, divergence tests achieve the first-order term of the Neyman-Pearson test, which is the optimal test when both $P$ and $Q$ are known. In contrast, the second-order term of divergence tests is strictly worse than that of the Neyman-Pearson test. It is further demonstrated that divergence tests with an invariant divergence achieve the same second-order term as the Hoeffding test, but divergence tests with a non-invariant divergence may outperform the Hoeffding test for some alternative hypotheses $Q$. Potentially, this behavior could be exploited by a composite hypothesis test with partial knowledge of the alternative hypothesis $Q$ by tailoring the divergence of the divergence test to the set of possible alternative hypotheses.<|reference_end|>
@article{harsha2024on,
    title={On the Second-Order Asymptotics of the Hoeffding Test and Other
  Divergence Tests},
    author={K. V. Harsha, Jithin Ravi, and Tobias Koch},
    journal={arXiv preprint arXiv:2403.03537},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.03537},
    primaryClass={cs.IT math.IT}
}