Expected values in Probability space

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Homework Help Overview

The discussion revolves around a probability space defined by (Ω, ε, P) and a set of random variables X1,...,Xn. The original poster seeks an example where the expected value of the limit inferior of a sequence of random variables is less than the limit inferior of their expected values.

Discussion Character

  • Exploratory, Assumption checking, Mathematical reasoning

Approaches and Questions Raised

  • The original poster attempts to understand the relationship between the expected values and the limit inferior of a sequence of random variables. They express uncertainty about how to proceed with their example. Other participants question the definition of limit inferior and suggest exploring nonconvergent sequences of random variables. There is a discussion about the conditions under which equality holds, referencing the dominated convergence theorem.

Discussion Status

Participants are actively engaging with the problem, offering insights and clarifications about the concepts involved. Some guidance has been provided regarding the construction of nonconvergent sequences, but there is no explicit consensus on the approach to take. The original poster has shared their attempts at evaluating integrals related to their example, indicating ongoing exploration.

Contextual Notes

There are indications of confusion regarding the evaluation of limit inferior and expected values, as well as the need for clarification on the integral computations involved. The original poster expresses difficulty with the lim inf concept, which may affect their progress.

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Homework Statement



Let a probability space be (Ω, \epsilon, P). A set of random variables X1,...,Xn

Give an example where I_{p}(lim inf_{n -&gt; ∞}X_{n}) < lim inf_{n -&gt; ∞}I_{p}(X_{n})


The attempt at a solution

I know that I_{p}(lim inf_{n -&gt; ∞}X_{n})=E[lim inf_{n -&gt; ∞}X_{n}]
and lim inf_{n -&gt; ∞}I_{p}(X_{n}) = lim inf_{n -&gt; ∞}E[X_{n}]

I think I need to find a sequence of Xn such that lim inf Xn will have a smaller value than all the individual expected value, E[Xn].

Am I on the correct path? I'm kind of stuck here and not sure how to proceed.

Would be really really thankful for the help.
 
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How is ##\displaystyle \liminf_{n \to \infty} X_n## defined? The limit of the "smallest value" of those random variables?
In that case, I don't see how both can be equal apart from trivial Xi.
 
Equality actually holds for surprisingly many cases. See for example, the dominated convergence theorem. So you'll need to look at sequences of random variables which fail that theorem.
Without giving away too much, try to make a nonconvergent sequence ##X_n## such that ##E[X_n]## are all constant.
 
Okay, then I don't understand how to evaluate ##\displaystyle \liminf_{n \to \infty} X_n##.
 
If ##X = \liminf_n X_n##, and ##\omega## is an outcome, then it is defined by
X(\omega) = \liminf_n X_n(\omega)

So it's just the pointswise inferior limit.
 
micromass said:
try to make a nonconvergent sequence ##X_n## such that ##E[X_n]## are all constant.

I saw this example...

Ω=N
P(ω)=2, ω in Ω
Xn(ω)=2nδω,n

I can see that Xn is not convergent.

But I'm not quite sure in computing the integrals... I'm very bad with the lim inf concept >_< So, I have written my attempt on evaluating the integrals and reasoning that I've used.

My attempt,
lim inf Xn
=lim inf [2nδω,n]
Since this takes in values 0 or 2n
=0

E[Xn]
=IP[2nδω,n]
= ∫2nδω,n2
When ω=n, this reduces to ∫δω,n
ω,n

I'm not very sure about the way I evaluate the integral. Would be very helpful for some guidance.
 

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