Adv Prob Theory: Set X(w) where the limit does not exist
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Let ${X_n}_{n=1}^{infty}$ be a equence of random variables defined on $(Omega, mathcal{S}, mathcal{P})$
Let $E = {omega: lim_{n rightarrow infty} X_n(omega)$ exists }$
Let $F = {omega: lim_{n rightarrow infty} frac{1}{n} sum_{i=1}^{n} X_i(omega)$ does not exist $}$
Prove:
Prove that $Ein mathcal{S}$ and $Fin mathcal{S}$
Here are my thoughts. If the sequence is all defined on the same probability space they all must be identically distributed.
If we let $A_n$ = ${omega: X_n(omega) = c$, where c is any real number $}$
and since $X_n$ is a set function that maps to the reals, $A_n$ = $Omega$ for all n, and $lim_{n rightarrow infty} A_n$ = $bigcap_{n=1}^{infty}A_n = E=Omega$
Similarly let $B_n= {omega: frac{X_i(omega)}{n} = c$, where c is any real number $}$.
$bigcap_{i=1}^n B_n subset B_n$, thus $bigcap_{i=1}^n B_n in mathcal{S}$
Because $sigma$-algebras are closed under countable unions:
$bigcup_{n=1}^{infty} bigcap_{i=1}^{n} B_n in mathcal{S} $
And by DeMorgans Laws:
$bigcap_{n=1}^{infty}bigcup_{i=1}^nB_n^c in mathcal{S}$
Note:
$bigcap_{n=1}^{infty}bigcup_{i=1}^nB_n^c$
= $bigcap_{n=1}^{infty}bigcup_{i=1}^n {omega: frac{X_i(omega)}{n} neq c$, where c is any real number $}$
= $bigcap_{n=1}^{infty}{omega: sum_{i=1}^n frac{X_i(omega)}{n} neq c$, where c is any real number $}$
= ${omega: lim_{n rightarrow infty} sum_{i=1}^n frac{X_i(omega)}{n} neq c$, where c is any real number $}$
= $F$
Hence $F in mathcal{S}$
I feel like I used a lot of tricks, and assumptions, but am having trouble finding a better arguement.
limits probability-theory measure-theory
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Let ${X_n}_{n=1}^{infty}$ be a equence of random variables defined on $(Omega, mathcal{S}, mathcal{P})$
Let $E = {omega: lim_{n rightarrow infty} X_n(omega)$ exists }$
Let $F = {omega: lim_{n rightarrow infty} frac{1}{n} sum_{i=1}^{n} X_i(omega)$ does not exist $}$
Prove:
Prove that $Ein mathcal{S}$ and $Fin mathcal{S}$
Here are my thoughts. If the sequence is all defined on the same probability space they all must be identically distributed.
If we let $A_n$ = ${omega: X_n(omega) = c$, where c is any real number $}$
and since $X_n$ is a set function that maps to the reals, $A_n$ = $Omega$ for all n, and $lim_{n rightarrow infty} A_n$ = $bigcap_{n=1}^{infty}A_n = E=Omega$
Similarly let $B_n= {omega: frac{X_i(omega)}{n} = c$, where c is any real number $}$.
$bigcap_{i=1}^n B_n subset B_n$, thus $bigcap_{i=1}^n B_n in mathcal{S}$
Because $sigma$-algebras are closed under countable unions:
$bigcup_{n=1}^{infty} bigcap_{i=1}^{n} B_n in mathcal{S} $
And by DeMorgans Laws:
$bigcap_{n=1}^{infty}bigcup_{i=1}^nB_n^c in mathcal{S}$
Note:
$bigcap_{n=1}^{infty}bigcup_{i=1}^nB_n^c$
= $bigcap_{n=1}^{infty}bigcup_{i=1}^n {omega: frac{X_i(omega)}{n} neq c$, where c is any real number $}$
= $bigcap_{n=1}^{infty}{omega: sum_{i=1}^n frac{X_i(omega)}{n} neq c$, where c is any real number $}$
= ${omega: lim_{n rightarrow infty} sum_{i=1}^n frac{X_i(omega)}{n} neq c$, where c is any real number $}$
= $F$
Hence $F in mathcal{S}$
I feel like I used a lot of tricks, and assumptions, but am having trouble finding a better arguement.
limits probability-theory measure-theory
Hint: if the limit of $x_n$ doesn't exist, then the difference $|limsup x_n - liminf x_n|$ is bigger than some rational number.
– user25959
Dec 3 at 1:50
add a comment |
up vote
0
down vote
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up vote
0
down vote
favorite
Let ${X_n}_{n=1}^{infty}$ be a equence of random variables defined on $(Omega, mathcal{S}, mathcal{P})$
Let $E = {omega: lim_{n rightarrow infty} X_n(omega)$ exists }$
Let $F = {omega: lim_{n rightarrow infty} frac{1}{n} sum_{i=1}^{n} X_i(omega)$ does not exist $}$
Prove:
Prove that $Ein mathcal{S}$ and $Fin mathcal{S}$
Here are my thoughts. If the sequence is all defined on the same probability space they all must be identically distributed.
If we let $A_n$ = ${omega: X_n(omega) = c$, where c is any real number $}$
and since $X_n$ is a set function that maps to the reals, $A_n$ = $Omega$ for all n, and $lim_{n rightarrow infty} A_n$ = $bigcap_{n=1}^{infty}A_n = E=Omega$
Similarly let $B_n= {omega: frac{X_i(omega)}{n} = c$, where c is any real number $}$.
$bigcap_{i=1}^n B_n subset B_n$, thus $bigcap_{i=1}^n B_n in mathcal{S}$
Because $sigma$-algebras are closed under countable unions:
$bigcup_{n=1}^{infty} bigcap_{i=1}^{n} B_n in mathcal{S} $
And by DeMorgans Laws:
$bigcap_{n=1}^{infty}bigcup_{i=1}^nB_n^c in mathcal{S}$
Note:
$bigcap_{n=1}^{infty}bigcup_{i=1}^nB_n^c$
= $bigcap_{n=1}^{infty}bigcup_{i=1}^n {omega: frac{X_i(omega)}{n} neq c$, where c is any real number $}$
= $bigcap_{n=1}^{infty}{omega: sum_{i=1}^n frac{X_i(omega)}{n} neq c$, where c is any real number $}$
= ${omega: lim_{n rightarrow infty} sum_{i=1}^n frac{X_i(omega)}{n} neq c$, where c is any real number $}$
= $F$
Hence $F in mathcal{S}$
I feel like I used a lot of tricks, and assumptions, but am having trouble finding a better arguement.
limits probability-theory measure-theory
Let ${X_n}_{n=1}^{infty}$ be a equence of random variables defined on $(Omega, mathcal{S}, mathcal{P})$
Let $E = {omega: lim_{n rightarrow infty} X_n(omega)$ exists }$
Let $F = {omega: lim_{n rightarrow infty} frac{1}{n} sum_{i=1}^{n} X_i(omega)$ does not exist $}$
Prove:
Prove that $Ein mathcal{S}$ and $Fin mathcal{S}$
Here are my thoughts. If the sequence is all defined on the same probability space they all must be identically distributed.
If we let $A_n$ = ${omega: X_n(omega) = c$, where c is any real number $}$
and since $X_n$ is a set function that maps to the reals, $A_n$ = $Omega$ for all n, and $lim_{n rightarrow infty} A_n$ = $bigcap_{n=1}^{infty}A_n = E=Omega$
Similarly let $B_n= {omega: frac{X_i(omega)}{n} = c$, where c is any real number $}$.
$bigcap_{i=1}^n B_n subset B_n$, thus $bigcap_{i=1}^n B_n in mathcal{S}$
Because $sigma$-algebras are closed under countable unions:
$bigcup_{n=1}^{infty} bigcap_{i=1}^{n} B_n in mathcal{S} $
And by DeMorgans Laws:
$bigcap_{n=1}^{infty}bigcup_{i=1}^nB_n^c in mathcal{S}$
Note:
$bigcap_{n=1}^{infty}bigcup_{i=1}^nB_n^c$
= $bigcap_{n=1}^{infty}bigcup_{i=1}^n {omega: frac{X_i(omega)}{n} neq c$, where c is any real number $}$
= $bigcap_{n=1}^{infty}{omega: sum_{i=1}^n frac{X_i(omega)}{n} neq c$, where c is any real number $}$
= ${omega: lim_{n rightarrow infty} sum_{i=1}^n frac{X_i(omega)}{n} neq c$, where c is any real number $}$
= $F$
Hence $F in mathcal{S}$
I feel like I used a lot of tricks, and assumptions, but am having trouble finding a better arguement.
limits probability-theory measure-theory
limits probability-theory measure-theory
edited Dec 3 at 7:32
asked Dec 2 at 20:32
kpr62
254
254
Hint: if the limit of $x_n$ doesn't exist, then the difference $|limsup x_n - liminf x_n|$ is bigger than some rational number.
– user25959
Dec 3 at 1:50
add a comment |
Hint: if the limit of $x_n$ doesn't exist, then the difference $|limsup x_n - liminf x_n|$ is bigger than some rational number.
– user25959
Dec 3 at 1:50
Hint: if the limit of $x_n$ doesn't exist, then the difference $|limsup x_n - liminf x_n|$ is bigger than some rational number.
– user25959
Dec 3 at 1:50
Hint: if the limit of $x_n$ doesn't exist, then the difference $|limsup x_n - liminf x_n|$ is bigger than some rational number.
– user25959
Dec 3 at 1:50
add a comment |
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Hint: if the limit of $x_n$ doesn't exist, then the difference $|limsup x_n - liminf x_n|$ is bigger than some rational number.
– user25959
Dec 3 at 1:50