On Stopping Times of Power-one Sequential Tests: Tight Lower and Upper Bounds
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Abstract (arXiv)
We present two general lower bounds for stopping times of sequential tests between arbitrary composite nulls mathcal P and alternatives mathcal Q. The first lower bound is for the ``Wald setting'' where the type-1 error level α approaches zero for a fixed alternative Q ∈ mathcal Q, and equals log(1/α) divided by a certain infimum KL divergence between mathcal P and Q, termed operatornameKLinf. The second lower bound applies to the ``Farrell setting'', where α is fixed and operatornameKLinf approaches 0 along a sequence of alternatives such that the required expected sample size along that sequence is of order at least operatornameKL-1inf log log operatornameKL-1inf. Our main contribution is the generality of these bounds, which hold in non-parametric, composite settings, without requiring a dominating reference measure, substantially generalizing the known parametric results. We also provide sufficient conditions for matching upper bounds and show that these are met in several nontrivial non-parametric cases.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 13 of its 38 references that are in the map. First posted on arXiv 28 Apr 2025.
Builds on
13 of 38 references.
References · 13
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Citing papers per year: 2025: 1; 2026: 4.
5 papers.
- 2026Multi-Armed Sequential Hypothesis Testing by Bettingcited by 1
- 2025Optimal Anytime-Valid Tests for Composite Nullscited by 0
- 2026GAAVI: Global Asymptotic Anytime Valid Inference for the Conditional Mean Functioncited by 0
- 2026Asymptotically Optimal Sequential Testing with Markovian Datacited by 0
- 2026A complete characterization of sequential testability and change detectability in i.i.d. modelscited by 0
- 2026A complete characterization of sequential testability and change detectability in i.i.d. models4 Sep 2026
- 2026Multi-Armed Sequential Hypothesis Testing by Betting18 Mar 2026
- 2026Asymptotically Optimal Sequential Testing with Markovian Data19 Feb 2026
- 2026GAAVI: Global Asymptotic Anytime Valid Inference for the Conditional Mean Function8 Feb 2026
- 2025Optimal Anytime-Valid Tests for Composite Nulls23 Dec 2025