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.
Conjugate-form prior for an exponential family
Definition
Let be a sigma-finite measure space. Let be measurable, where has the trace Borel sigma-algebra and is the parameter set in Exponential families and full rank. Let be its log-partition function. For and , define When , the conjugate-form prior is the probability measure with density relative to . If this finite-positive condition fails, this notation does not designate a probability prior.
Remarks
Log-partition measurability. The log-partition function is Borel on its natural-parameter domain . On the product measurable space (The product sigma-algebra and its finite iterates), the coordinate functions of and are measurable. Finite sums and products preserve measurability (Arithmetic and lattice operations preserve measurability whenever they are defined), and composition with the continuous exponential is measurable (A continuous map has Borel preimages of Borel sets, The exponential function is smooth and ); hence is product-measurable. Regard as the constant kernel from to (Measure kernel and probability kernel). Choose a measurable exhaustion with , supplied by sigma-finiteness; then for every , so this is a uniformly sigma-finite kernel. The parameterized-integral measurability theorem (Measurability of integration against a kernel) therefore makes a Borel map into . Consequently is Borel, and is Borel on because logarithm is differentiable, hence continuous, on (The natural logarithm has derivative 1/x and equals the integral from 1 to x of 1/t, A function differentiable at is continuous at , A continuous map has Borel preimages of Borel sets). Thus and are measurable. Since is sigma-finite, the integral defining is a well-defined extended nonnegative integral; under its stated finite-positive condition the displayed density is measurable and normalizes to one.
Depends on
- Exponential families and full rank
- Finite, sigma-finite, and semifinite measures
- Measure kernel and probability kernel
- The product sigma-algebra and its finite iterates
- Arithmetic and lattice operations preserve measurability whenever they are defined
- A continuous map has Borel preimages of Borel sets
- The exponential function is smooth and $(\exp)'=\exp$
- The natural logarithm has derivative 1/x and equals the integral from 1 to x of 1/t
- A function differentiable at $c$ is continuous at $c$
- Measurability of integration against a kernel
Used by
Dependency tree · two levels
53 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
- Gelman et al., Bayesian Data Analysis, 3rd ed., §2.4 (standard reference, not scraped)
- Charles J. Geyer, Stat 5421 Lecture Notes: Exponential Families, 2020 (standard reference, not scraped)