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.
Quantile coupling on the real line
Example
Assume AC. If real probability laws have CDFs ,F and generalized inverses , for 0<, then on Borel Lebesgue probability (0,1), and Q have those laws and almost surely.
Facts & Assumptions
Probability laws correspond to distribution functions: Assume the Axiom of Countable Choice.
- Let be a real random variable, let be its law, and let . Then is nondecreasing and right-continuous, satisfies and obeys
- Conversely, if is nondecreasing and right-continuous with then there is a unique Borel probability measure on such that equivalently
A box in with parameters is Lebesgue measurable of measure , whichever of its faces are included: Let , assume the Axiom of Countable Choice (def-countable-choice), and let be reals for . Write
(def-multidimensional-rectangle-and-volume). Then is open and is closed, so both are Borel and Lebesgue measurable, and every set with is Lebesgue measurable with
In particular this covers the four one-dimensional face conventions in each coordinate — the open box, the closed box , the half-open box of def-half-open-box, and every mixture of them, in any combination of coordinates — and it gives measure to all of them whenever for some . For a half-open box with infinite parameters the value is already (thm-lebesgue-measure-is-a-complete-measure).
Froda's theorem: the set of discontinuities of a monotone function on an interval is at most countable, the injection into being built from one fixed enumeration of the rationals by least index, so no choice principle is used: Let be order-convex (def-interval) and let be monotone (def-monotone-function). Then the set
(def-classification-of-discontinuities) is at most countable (def-countable).
More precisely, the proof exhibits an injection (def-injection-surjection-bijection) built from one fixed enumeration of the rationals: at a discontinuity interior to the value is read off the least index of a rational lying in the gap , which is a nonempty open interval by thm-monotone-discontinuities-are-jumps. The map is therefore determined by and by the fixed enumeration, and no choice principle is used: least indices are canonical by thm-well-ordering-principle, and nothing anywhere in the proof is selected without being determined.
Portmanteau theorem: For Borel probabilities on a metric space S, the following are equivalent: (i) ; (ii) integrals converge for all bounded uniformly continuous real tests; (iii) for every closed F; (iv) for every open G; (v) for every Borel A with .
Every at most countable subset of is Lebesgue null; in particular : Let and assume the Axiom of Countable Choice (def-countable-choice). Every at most countable subset (def-countable) is Lebesgue measurable with
so is a -null set (def-measure-null-set-and-almost-everywhere). In particular every singleton is null, and on the real line the set of rational reals (lem-rat-embeds-dense) satisfies .
Verification
Given: The objects, hypotheses and definitions in the statement. Its conclusions are to be established below.
AC implies CC by restriction to any countable family. F1 gives right-continuity, monotonicity and the CDF endpoint limits. For 0<, the set defining Q(u) is nonempty and bounded below by those limits. For any x, if u<=F(x) then Q(u)<=x. Conversely if Q(u)<=x, for each the infimum property supplies y<x+h with F(y)>=u; thus F(x+h)>=u and right-continuity gives F(x)>=u. Therefore , and the same holds for .
The sublevel identity in step 1.1 proves measurability. F2 gives the length of as F(x), including values zero and one. Thus the CDF of Q on this probability interval equals F; the uniqueness clause of F1 identifies its law as , and likewise for every .
Fix a continuity point u of the nondecreasing Q and >0. Choose v with u< and Q(v)<Q(u)+, using continuity at u. Choose a continuity point a of F between Q(u)- and Q(u), and a continuity point b of F between max(Q(u),Q(v)) and Q(u)+. Such choices exist because a monotone CDF has only countably many discontinuities by F3. Step 1.1 gives F(a)<u and F(b)>=v>u. F4 at the half-lines with endpoints a,b gives (a)->F(a) and (b)->F(b). Eventually (a)<u<(b), whence by step 1.1. Thus eventually.
Q is nondecreasing, since increasing u shrinks the defining set. F3 makes its discontinuity set on (0,1) countable. F5, under CC from step 1.1, makes this set null. Step 2.2 proves convergence elsewhere, so the coupling has the stated almost-sure limit. The excluded ,1 need no inverse values.
Depends on
- Probability laws correspond to distribution functions
- Portmanteau theorem
- Froda's theorem: the set of discontinuities of a monotone function on an interval is at most countable, the injection into $\mathbb{N}$ being built from one fixed enumeration of the rationals by least index, so no choice principle is used
- A box in $\mathbb{R}^n$ with parameters $a_i\le b_i$ is Lebesgue measurable of measure $\prod_{i<n}(b_i-a_i)$, whichever of its faces are included
- Every at most countable subset of $\mathbb{R}^n$ is Lebesgue null; in particular $\lambda_1(\mathbb{Q})=0$
- The Axiom of Countable Choice ($\mathrm{AC}_\omega$)
- The Axiom of Choice
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
50 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, Theorem 3.2.8, pp. 118–119 (standard reference, not scraped)