Expected values in Probability space

  • Thread starter Thread starter Lily@pie
  • Start date Start date
  • Tags Tags
    Probability Space
Click For Summary
The discussion revolves around finding 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. Participants clarify that the limit inferior of a sequence is defined pointwise and suggest creating a nonconvergent sequence of random variables with constant expected values. One user provides a specific example using a probability space defined on natural numbers, where the random variables are not convergent. There is uncertainty about evaluating the integrals involved in the calculations, particularly regarding the limit inferior concept. The conversation emphasizes the need for further guidance on integral evaluation and the properties of the defined sequence.
Lily@pie
Messages
108
Reaction score
0

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.
 
Physics news on Phys.org
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.
 
Question: A clock's minute hand has length 4 and its hour hand has length 3. What is the distance between the tips at the moment when it is increasing most rapidly?(Putnam Exam Question) Answer: Making assumption that both the hands moves at constant angular velocities, the answer is ## \sqrt{7} .## But don't you think this assumption is somewhat doubtful and wrong?

Similar threads

  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 8 ·
Replies
8
Views
2K
Replies
2
Views
1K
Replies
1
Views
3K
Replies
1
Views
2K
  • · Replies 4 ·
Replies
4
Views
3K
  • · Replies 1 ·
Replies
1
Views
1K
  • · Replies 12 ·
Replies
12
Views
2K
Replies
3
Views
1K
  • · Replies 4 ·
Replies
4
Views
2K