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.
Weak convergence of borel probability measures
Definition
For Borel probability measures on a metric space S, write if for every bounded continuous real function f on S. Continuity is Continuity of a map between metric spaces, at a point and globally, in the - form. Such f is Borel measurable (inverse images of open sets are open) and , so the integrals are finite in Integrable real and complex functions, and their integrals. No completeness or coupling is required.
Depends on
Used by
- Deterministic Ito integrals are Gaussian Corollary
- Fixed negative-axis directional resolvent integrals converge Corollary
- Isotropic minimum-norm risk limits under a positive spectral gap Corollary
- Studentized RQMC replicate means are asymptotically normal as R→∞ Corollary
- The scaled posterior converges weakly on the negative Sobolev space Corollary
- Bounded continuous cannot be replaced by all bounded measurable functions Counterexample
- Boundedness of first moments alone does not give uniform integrability Counterexample
- Pointwise cdf convergence at a jump is not required Counterexample
- Asymptotic distribution Definition
- Conditional weak convergence in probability Definition
- Convergence in distribution of random elements Definition
- Relative sequential compactness for weak convergence Definition
- Sample covariance matrices and their empirical spectral distributions Definition
- A degenerate weak limit with persistent expectation Example
- A singular Brownian data law forces positive-time score truncation Example
- At aspect one the reciprocal-spectrum limit diverges Example
- Chebyshev extremal nodes converge to the arcsine equilibrium measure Example
- Chebyshev extremals and the exact disk Fekete polynomial Example
- Dirac laws converge weakly exactly when their points converge Example
- Empirical laws of a finite valued iid sample Example
- Uniform laws on expanding finite grids converge to uniform zero one Example
- Weak convergence of gaussian laws by parameters Example
- Weakly close root laws can still give failed uniform coverage Example
- Weakly convergent finite-step output laws need not be exact Example
- Compact capacity-zero sets and subharmonic minus-infinity loci Lemma
- Countable compactly supported tests determine euclidean weak convergence Lemma
- Finite-horizon bootstrap particle filters are weakly consistent Lemma
- Probability laws on a compact metric space have weakly convergent subsequences Lemma
- Relative property (T) for SL2(R) semidirect R2 Lemma
- The bounded-Lipschitz metric characterizes weak convergence on Polish spaces Lemma
- Optimal quadratic couplings exist and their cost is weakly lower semicontinuous Proposition
- Almost-sure Marchenko–Pastur law for finite-fourth-moment sample covariance matrices Theorem
- Conditional K-sample block-bootstrap validity under a joint CLT Theorem
- Cramer wold device Theorem
- Directional deterministic equivalent for bounded sample-covariance entries Theorem
- Existence and uniqueness of the equilibrium measure Theorem
- Fekete–Szegő equality of logarithmic capacity, transfinite diameter, and Chebyshev constant Theorem
- Fixed-horizon particle backward smoothing is consistent under stated conditions Theorem
- Gaussian smoothing converges weakly at the endpoint Theorem
- Gaussian smoothing density and forward equation Theorem
…and 13 more results.
Dependency tree · two levels
15 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
- van Gaans, Definition 3.1, pp. 6–7 (standard reference, not scraped)