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.
Regular conditional law of one coordinate given another
Example
Assume AC for the compact Riemann–Lebesgue integration bridge. On take joint density . For the coordinate random variables X,Y, a conditional law of X given Y=y is uniform on when , with the fixed filler otherwise:
Facts & Assumptions
Given: The hypotheses and conventions in the example.
The density ratio on finite positive marginal fibres, with fixed probability filling, gives a conditional kernel. Conditional density formula.
Continuous polynomial primitives compute the compact integrals. The second fundamental theorem: if is differentiable on with and is integrable, then .
Bounded Riemann integrals equal Lebesgue integrals under countable choice. A bounded Riemann integrable function on a closed bounded interval is Lebesgue measurable and has the same integral.
AC supplies countable choice for the compact integral bridge. The Axiom of Choice.
Tonelli gives measurable marginal section integrals and the joint total mass. Tonelli's theorem for nonnegative measurable functions on a sigma-finite product.
The nonnegative density defines the joint measure. The indefinite integral of a nonnegative measurable function is a measure.
Verification
The triangle is product-measurable, since its defining strict inequalities between coordinates are open conditions (or countable rational rectangle unions). For the section integral is , and it is zero for all other y. The constant primitive 2x computes this integral by [F2] and [F3]; finite endpoints are Lebesgue-null, as follows from containment in intervals of arbitrarily small length. Likewise . Thus [F5] shows the nonnegative joint density has total mass one, and [F6] constructs the probability. The bridge uses the countable choice supplied by [F4].
On , and . Dividing gives the displayed uniform kernel. Off this interval the marginal is zero, so [F1] allows the supplied point-mass probability . Its event value is and it is countably additive because at most one member of a disjoint event sequence contains 0. For any Borel A,B, the conditional rectangle calculation is the joint probability by [F5]. In particular , while under the specified filler. The latter is not a value of a density ratio.
Depends on
- Conditional density formula
- The second fundamental theorem: if $G$ is differentiable on $[a,b]$ with $G' = f$ and $f$ is integrable, then $\int_a^b f = G(b)-G(a)$
- A bounded Riemann integrable function on a closed bounded interval is Lebesgue measurable and has the same integral
- The Axiom of Choice
- Tonelli's theorem for nonnegative measurable functions on a sigma-finite product
- The indefinite integral of a nonnegative measurable function is a measure
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
44 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
- Durrett, Probability: Theory and Examples, fifth edition (standard reference, not scraped)
- Varadhan, Probability Theory, Chapter 4 (standard reference, not scraped)