Alphabeta Math
DefinitionDefinition: AI-adaptedProof: Not applicablePipeline-generatedjudge pass (gpt-6-luna)
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.

Likelihood ratio as a Radon–Nikodym derivative

Definition

Let P0 and P1 be probability measures on the same measurable space. Assume AC. Their Lebesgue decomposition relative to P0 is the unique decomposition P1=P1,ac+P1,s with P1,ac≪P0 and P1,s⊥P0 (Every sigma-finite signed measure admits a Lebesgue decomposition relative to a sigma-finite positive measure, The Lebesgue decomposition of a sigma-finite signed measure is unique). Both components are positive by Lebesgue components of a positive finite measure are positive, and P1,ac is finite because their sum has mass one. Define the likelihood-ratio density of P1 against P0 to be the P0-almost-everywhere class

dP1,acdP0

of The Radon-Nikodym derivative as an almost-everywhere equivalence class. Under AC this class has a nonnegative measurable representative by A sigma-finite positive measure has a nonnegative Radon–Nikodym density version.

This is a full density of P1 with respect to P0 only in the absolutely continuous case P1≪P0. If that condition fails, the singular component remains separate. A displayed representative is not a canonical pointwise function: its values are determined only P0-almost everywhere.

Depends on

Used by

Dependency tree · two levels

38 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