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.
A dominated differentiable-in-quadratic-mean submodel
Definition
Let be a model of probability measures on a measurable space , let , and let be a path for with . It is dominated by a common measure when one supplied sigma-finite positive measure satisfies for every (Dominated statistical experiments). Write and for simultaneously supplied nonnegative density versions; the existence and normalization of each density are the Radon–Nikodym properties in Likelihood densities and A sigma-finite signed measure that is absolutely continuous with respect to a sigma-finite positive measure has a unique almost-everywhere density. The Axiom of Choice is the library convention for selecting such a family of versions along a path (The Axiom of Choice). The DQM property below is unchanged by replacing any by another version, since each norm is unchanged by a -null modification.
The path is differentiable in quadratic mean at , with score , when
Here means that the displayed norm divided by tends to as ; and are quotient spaces modulo almost-everywhere equality (The space as the quotient by null functions). The definition is directional. A two-sided regular submodel qualifies by restricting it to . No mean-zero condition is assumed in this definition.
Depends on
- Dominated statistical experiments
- Likelihood densities
- A sigma-finite signed measure that is absolutely continuous with respect to a sigma-finite positive measure has a unique almost-everywhere density
- A sigma-finite positive measure has a nonnegative Radon–Nikodym density version
- The space $L^p(\mu)$ as the quotient by null functions
- The $L^p$ norm descends to the quotient and makes $L^p$ a normed space for $1 \le p \le \infty$
- The Axiom of Choice
Used by
- A finite-mean functional without a square-integrable influence curve Counterexample
- Pathwise differentiability and parameter influence curves Definition
- Tangent set of a statistical model at a law Definition
- A boundary score cone differs from its tangent space Example
- A regular Bernoulli submodel and its score Example
- Bounded mean-zero scores generate the unrestricted tangent space Example
- The sample mean attains the unrestricted mean bound Example
- A one-sided DQM path yields an iid LAN proxy Lemma
- A DQM score has mean zero and is unique Theorem
Dependency tree · two levels
31 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
- A. W. van der Vaart, Semiparametric Statistics, Lecture 1 §1.2, Definition 1.6 (standard reference, not scraped)
- Edward H. Kennedy, Semiparametric theory, §4 (standard reference, not scraped)