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Nonnegative test supermartingales
Definition
Assume the Axiom of Choice (AC) The Axiom of Choice. Let be a discrete filtration on a measurable space, and let be a family of probability laws on . A real-valued process is a nonnegative test supermartingale for if, for every , it is adapted and integrable under Filtration and filtered probability space Martingale submartingale and supermartingale, satisfies for every , and has .
The same process must satisfy the supermartingale condition under every law in the null family; that is what makes the definition uniform over a composite null. The initial value may be random and need not be bounded by one pointwise. Time starts at zero.
Remarks
A nonnegative test supermartingale is a standard sufficient process for anytime-valid testing. Some literature uses e-process for a broader class, allowing a process dominated under each null law by a different test martingale. This item defines the planned common test-supermartingale class; it does not assert that every e-process is itself a supermartingale.
Depends on
Used by
- A supermartingale supremum threshold need not be attained Counterexample
- Validity under one null law does not give a composite-null test supermartingale Counterexample
- A data-dependent threshold crossing Example
- A finite-horizon likelihood-ratio test supermartingale Example
- Conditional sub-Gaussian increments generate exponential test supermartingales Lemma
- Finite-horizon crossing bound for a nonnegative test supermartingale Lemma
- A test supermartingale gives anytime-valid p-values Theorem
- Confidence sequences by test-supermartingale inversion Theorem
- Discrete Ville inequality and anytime threshold validity Theorem
- Mixtures of null test supermartingales Theorem
- Terminal error bounds for a sequential likelihood-ratio test Theorem
- Ville's inequality for nonnegative test supermartingales Theorem
Dependency tree · two levels
8 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- Aaditya Ramdas, Peter Grunwald, Vladimir Vovk and Glenn Shafer, Game-Theoretic Statistics and Safe Anytime-Valid Inference, §§2.2-2.4 (standard reference, not scraped)