What is the limit of this (complicated) set?

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In summary, the conversation discusses almost sure convergence relations for a doubly infinite sequence of random variables. The question is whether the sequence of sets A_j has a limit of A, which represents the set of outcomes for which the sequence of sums of all the random variables does not converge to the sum of all the corresponding a_i values. The conversation also mentions the use of decreasing sequence of deltas and increasing sequence of their corresponding I's to show that the probability of A_j is zero.
  • #1
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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  • #2
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:
\forall M\in\mathbb N\ \exists n\ge M\ :\
\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?
 

1. What is the meaning of "limit" in terms of a complicated set?

The limit of a complicated set refers to the maximum or minimum value that the set can approach as its variables or parameters change. It represents the boundary or endpoint of the set's behavior.

2. How is the limit of a complicated set determined?

The limit of a complicated set is determined by evaluating the behavior of the set as its variables or parameters approach a specific value. This can be done through mathematical calculations or by observing the trend of the set's values.

3. Can the limit of a complicated set change?

Yes, the limit of a complicated set can change if the set's variables or parameters change. It can also change if the set is redefined or if new data is added to the set.

4. What factors can affect the limit of a complicated set?

The limit of a complicated set can be affected by the set's initial conditions, the behavior of its variables or parameters, and any external factors that may influence the set's behavior. It can also be affected by the accuracy and precision of the data used to define the set.

5. Why is it important to understand the limit of a complicated set?

Understanding the limit of a complicated set is important because it helps us predict the behavior of the set and make informed decisions based on that behavior. It also allows us to identify any potential issues or limitations of the set and find ways to improve or optimize its performance.

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