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Weak law does not imply strong law

Statement refuted

A weak sample-mean law need not be a centered strong law. Assuming AC, there are integrable real (Xn) with Sn/n0 in probability but (SnESn)/n not tending to zero almost surely.

Facts & Assumptions

[F1]

The recursion theorem: Let (N,0,σ) be a Peano system (def-peano-system), in particular the natural numbers N (def-natural-numbers). For any set A, any element aA, and any function f:AA, there is a unique function g:NA such that g(0)=a and g(σ(n))=f(g(n)) for all nN.

[F2]

A box in Rn with parameters aibi is Lebesgue measurable of measure i<n(biai), whichever of its faces are included: Let n1, assume the Axiom of Countable Choice (def-countable-choice), and let aibi be reals for i<n. Write

R:={xRn:ai<xi<bi for every i<n},R:=[a,b]={xRn:aixibi for every i<n}

(def-multidimensional-rectangle-and-volume). Then R is open and R is closed, so both are Borel and Lebesgue measurable, and every set R with RRR is Lebesgue measurable with

λn(R)  =  i<n(biai).

In particular this covers the four one-dimensional face conventions in each coordinate — the open box, the closed box [a,b], the half-open box B(a,b)=i<n(ai,bi] of def-half-open-box, and every mixture of them, in any combination of coordinates — and it gives measure 0 to all of them whenever ai=bi for some i<n. For a half-open box with infinite parameters the value is already λn(B)=vol(B) (thm-lebesgue-measure-is-a-complete-measure).

[F3]

Countably many independent copies of a prescribed law exist: Assume countable choice and dependent choice. Every probability measure ν on (S,Σ) is the common law of a countable independent family of S-valued random elements.

[F4]

Measurable coordinatewise functions preserve independence: Let (Xi)iI be an independent family of random elements Xi:(Ω,F,P)(Si,Σi). For each i, let gi:(Si,Σi)(Ti,Ti) be measurable. Then the family (giXi)iI is independent.

[F5]

Second Borel-Cantelli lemma under pairwise independence: Let (An)nN be pairwise independent events with n=0P(An)=+. Then P(An i.o.)=1.

Counterexample

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

1.1

AC restricted to a countable family gives CC; choosing a successor for each point of an entire relation and using F1 gives DC. On ((0,1),B,λ) the identity U has P(Ut)=t for 0<t<1 by F2. F3 supplies IID copies Un. Let Bn=1{Un1/(n+1)}, which are independent by F4.

F1F2F3F4
1.2

Set B0=0 and Xn=nBn(n1)Bn1. These finite-valued variables are integrable; telescoping gives Sn=nBn. Thus P(Sn/n>ε)1/(n+1)0 for every ε>0, and ESn/n=1/(n+1)0.

givenalgebra
2.1

The sum of 1/(n+1) diverges: each block 2jn+1<2j+1 contributes at least 1/2. The complementary probabilities n/(n+1) also have divergent sum. Apply F5 to the independent events Bn=1 and separately to Bn=0. Both occur infinitely often on a common conull event. Hence the centered averages Bn1/(n+1) have limsup 1 and liminf 0 there, refuting the centered strong law while step 1.2 establishes the weak law.

F5step 1.2

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