What is the limit of this (complicated) set?

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Adeimantus
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This is going to take a while to set up, so I apologize for that. This came up in the course of thinking about the Strong Law of Large Numbers. It's not homework.

Suppose you have a doubly infinite sequence of random variables [itex]X_{i,n}[/itex] that obey the following almost sure convergence relations. For each [itex]i = 1,2,3,...[/itex],

[tex]X_{i,n} \xrightarrow{a.s} a_i \quad \mbox{ as } \quad n\xrightarrow{} \infty[/tex].

Further, we have that [itex]\sum_{i=1}^\infty a_i = \mu < \infty[/itex]. Since this series converges, for any [itex]\delta > 0[/itex], there is some smallest [itex]I[/itex] such that [itex]\left| \sum_{i=1}^m a_i - \mu \right | < \delta[/itex] for all [itex]m \geq I[/itex]. Consider a sequence of deltas decreasing to zero, and the increasing sequence of their corresponding [itex]I[/itex]'s.

[tex]\delta_1 > \delta_2 > ... \xrightarrow{} 0 \quad \mbox{and} \quad I_1 < I_2 < ...[/tex]

Consider some particular pair [itex](\delta_j, I_j)[/itex]. Since almost sure convergence is linear,

[tex]\sum_{i=1}^{I_j}X_{i,n} \xrightarrow{a.s} \sum_{i=1}^{I_j} a_i \quad \mbox{ as } \quad n\xrightarrow{} \infty[/tex]

This is the same thing as saying the set

[tex]\{ \omega: \left| \sum_{i=1}^{I_j}X_{i,n}(\omega) - \sum_{i=1}^{I_j} a_i \right| > \epsilon \quad i.o. \quad n\xrightarrow{} \infty \}[/tex]

has probability zero for any choice of [itex]\epsilon > 0[/itex]. From the definition of the deltas and I's, the set

[tex]A_j = \{ \omega: \left| \sum_{i=1}^{I_j}X_{i,n}(\omega) - \mu \right| > \epsilon + \delta_j \quad i.o. \quad n\xrightarrow{} \infty \}[/tex]

also probability zero. My question is, does the sequence of sets [itex]A_j[/itex] have a limit of

[tex]A = \{ \omega: \left| \sum_{i=1}^{\infty}X_{i,n}(\omega) - \mu \right| > \epsilon \quad i.o. \quad n\xrightarrow{} \infty \}[/tex]

Thanks for wading through that!
 
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I waded some of the way, then got stuck here:
Adeimantus said:
[tex]\left\{ \omega: \left| \sum_{i=1}^{I_j}X_{i,n}(\omega) - \sum_{i=1}^{I_j} a_i \right| > \epsilon \quad i.o. \quad n\xrightarrow{} \infty \right\}[/tex]
I have not come across the initials ##i.o.## before. What do they mean?

I feel that perhaps the set is
[tex]\left\{ \omega:<br /> \forall M\in\mathbb N\ \exists n\ge M\ :\<br /> \left| \sum_{i=1}^{I_j}X_{i,n}(\omega) - \sum_{i=1}^{I_j} a_i \right| > \epsilon \right\}[/tex]
in which case the statement is that the set of ##\omega## for which the ##n##-indexed sequence of sums of the first ##I_j## RVs does not converge to the sum of the first ##I_j## ##a_i##s, has probability measure zero.

Is that what you meant?