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Ville's inequality for nonnegative test supermartingales
Statement
Assume AC. Let be a family of probability laws on a common discrete filtered measurable space and let be a nonnegative test supermartingale for Nonnegative test supermartingales. For every and every ,
Facts & Assumptions
Given: Assume AC. If is empty the conclusion is vacuous; otherwise fix , , and the nonnegative test supermartingale . All stopping times below use the discrete filtration and time starts at zero.
Nonnegative test supermartingales: under every null law , is adapted, integrable, nonnegative almost surely at each time, a supermartingale, and .
Discrete stopping time: a map into is a stopping time when for each , and it is bounded if some deterministic satisfies almost surely.
Optional sampling for bounded stopping times: under AC, for bounded stopping times and a supermartingale the expectation inequality points downward.
Continuity from below for measures: for an increasing sequence of measurable events, the measure of the union is the limit of their measures.
The Axiom of Choice: AC supplies the conditional-expectation clauses used by the supermartingale definition and bounded optional-sampling theorem.
Proof
Fix any and define , with . For every , , so is a stopping time. Also for and is the whole space for , so each is a bounded stopping time.
The constant time is a stopping time bounded by , and step 1.1 shows is a bounded stopping time. Bounded optional sampling therefore gives .
On , ; on its complement the stopped value is almost surely. Hence , and step 2.1 yields .
The events increase with and their union is . Continuity from below and step 3.1 therefore give .
Let and suppose . Since , lies in , so . If every , then , contrary to ; hence even if the supremum is not attained. Step 4.1 with gives , a contradiction. Therefore , and since was arbitrary, the bound holds under every null law.
Depends on
Used by
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Sources
- Aaditya Ramdas, Peter Grunwald, Vladimir Vovk and Glenn Shafer, Game-Theoretic Statistics and Safe Anytime-Valid Inference, §2.5 (standard reference, not scraped)
- Steven R. Howard, Aaditya Ramdas, Jon McAuliffe and Jasjeet Sekhon, Time-Uniform, Nonparametric, Nonasymptotic Confidence Sequences, Lemma 2 and Appendix A.3 (standard reference, not scraped)
- Robert L. Wolpert, STA 711 Martingales lecture notes, §1 (standard reference, not scraped)