Saved in:
Bibliographic Details
Main Authors: Grootveld, Arick, Chen, Biao, Gandikota, Venkata
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2601.11727
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866917416708079616
author Grootveld, Arick
Chen, Biao
Gandikota, Venkata
author_facet Grootveld, Arick
Chen, Biao
Gandikota, Venkata
contents In this work, we revisit the one- and two-sample testing problems: binary hypothesis testing in which one or both distributions are unknown. For the one-sample test, we provide a more streamlined proof of the asymptotic optimality of Hoeffding's likelihood ratio test, which is equivalent to the threshold test of the relative entropy between the empirical distribution and the nominal distribution. The new proof offers an intuitive interpretation and naturally extends to the two-sample test where we show that a similar form of Hoeffding's test, namely a threshold test of the relative entropy between the two empirical distributions is also asymptotically optimal. A strong converse for the two-sample test is also obtained.
format Preprint
id arxiv_https___arxiv_org_abs_2601_11727
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Asymptotically Optimal Tests for One- and Two-Sample Problems
Grootveld, Arick
Chen, Biao
Gandikota, Venkata
Information Theory
In this work, we revisit the one- and two-sample testing problems: binary hypothesis testing in which one or both distributions are unknown. For the one-sample test, we provide a more streamlined proof of the asymptotic optimality of Hoeffding's likelihood ratio test, which is equivalent to the threshold test of the relative entropy between the empirical distribution and the nominal distribution. The new proof offers an intuitive interpretation and naturally extends to the two-sample test where we show that a similar form of Hoeffding's test, namely a threshold test of the relative entropy between the two empirical distributions is also asymptotically optimal. A strong converse for the two-sample test is also obtained.
title Asymptotically Optimal Tests for One- and Two-Sample Problems
topic Information Theory
url https://arxiv.org/abs/2601.11727