How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
Two-sample U-statistic parameter
Definition
Let be a measurable space, let be probability measures on it, and let be a fixed integer. Give the product sigma-algebra and the product probability measure . A two-sample order- kernel is a measurable function that is symmetric in its first arguments and separately symmetric in its last arguments. If is integrable under this product law, its two-sample U-statistic parameter is
The value is finite and real. This definition imposes no null hypothesis and no antisymmetry condition; those are hypotheses of later results.
Depends on
- Probability measures and probability spaces
- The product sigma-algebra and its finite iterates
- For sigma-finite factors, the product measure exists, has the rectangle formula, is sigma-finite, and is unique
- A measurable function between measurable spaces
- Expectation of a nonnegative or integrable random variable
Used by
- An extra square-root sample-size factor destroys standard-error studentization Counterexample
- The weak null does not center every mixed kernel assignment Counterexample
- Two-sample order-r U-statistic and first projections Definition
- A studentized rank U-statistic under a weak null Example
- Exact equality null versus weak parameter null Example
- Studentized difference of means with equal means and unequal variances Example
Dependency tree · two levels
23 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.