Alphabeta Math
CounterexampleConstruction: AI-adaptedVerification: AI-adaptedPipeline-generatedaudited 2026-09-10
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Pointwise cdf convergence at a jump is not required

Statement refuted

Weak convergence does not require CDF convergence at a jump of the limiting CDF. For n1, the witness is μn=δ1/n, with μ=δ0 on the real line.

Facts & Assumptions

[F1]

Weak convergence of borel probability measures: For Borel probability measures μn,μ on a metric space S, write μnμ if fdμnfdμ for every bounded continuous real function f on S. Continuity is def-metric-continuity. Such f is Borel measurable (inverse images of open sets are open) and fdμfμ(S)<, so the integrals are finite in def-integrable-real-and-complex-functions-and-their-integrals. No completeness or coupling is required.

[F2]

Cumulative distribution function of a real random variable: Let X be a real random variable. Its cumulative distribution function is the function FX:R[0,1],FX(x):=P(Xx)=PX((,x]).

The second expression is the same quantity written in terms of the law def-law-or-distribution-of-a-random-element of X.

Counterexample

Given: The objects, hypotheses and definitions in the statement. Its conclusions are to be established below.

1.1

On Ω={} take F={,Ω} and P(Ω)=1, P()=0. This is a probability space: in any disjoint family at most one event is nonempty. For every integer n1 set Xn()=1/n and X()=0. Each map is measurable because every Borel preimage is either or Ω. Its law is respectively μn=δ1/n or μ=δ0: a Borel set has probability one exactly when it contains the specified value. Define Fn=FXn and F=FX using F2.

givenF2
2.1

For a point mass, fdδa=f(a) for bounded measurable f: this holds for simple functions by the definition of their integral, and then for nonnegative bounded functions by increasing simple approximation, and for real bounded functions by their positive and negative parts. For bounded continuous f, continuity at zero therefore gives fdμn=f(1/n)f(0)=fdμ. By F1 the laws converge weakly.

F1step 1.1
3.1

By F2 and step 1.1, Fn(t)=1{t1/n} and F(t)=1{t0}. Thus Fn(0)=0 for every n1 while F(0)=1. Moreover F(t)=0 for every t<0, so F has a jump from its left limit zero to its value one at zero. Hence weak convergence does not force CDF convergence at this jump.

F2step 1.1step 2.1

Depends on

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