Conditional expectation for a partition
up vote
2
down vote
favorite
Consider a probability space $(Omega,mathcal{F},P)$ and a bounded random variable $X$. Let $(A_n)_{nge 1}$ be a countable partition of $Omega$ and define $mathcal{A}:=sigma({A_n:nge 1})$. Then it holds:
$$E[X|mathcal{A}]=sum_{nge 1, P(A_n)>0}E[X|A_n]cdotmathbb{1}_{A_n}$$
One can prove it by using the uniqueness of $E[X|mathcal{A}]$, i.e. I should be done, if I can show that the expression on the right is $mathcal{A}$-measurable, and that for any $Binmathcal{A}$, it holds
$$EBig[E[X|mathcal{A}]cdot 1_BBig]=EBig[Big(sum_{nge 1, P(A_n)>0}E[X|A_n]cdotmathbb{1}_{A_n}Big)cdot 1_BBig]$$
EDIT:
First property: For any $nge 1$: $E[X|A_n]$ and $1_{A_n}$ are $sigma(1_{A_n})$-measurable, therefore $mathcal{A}$-measurable. Now using the fact that products and sums of measurable functions are measurable, we have that
$$sum_{nge 1, P(A_n)>0}E[X|A_n]cdotmathbb{1}_{A_n}$$
is $mathcal{A}$-measurable.
Second property:
Now let $A_ninmathcal{A}$ with $P(A_n)=0$. Then we know that
$$E[Xcdot1_{A_n}]=sum_{omegain A_n}X(omega)cdot underbrace{P({omega})}_{=0}=0.$$
Therefore we have for any $Binmathcal{A}$, i.e. $B=cup_{min M} A_m$ with a countable subset $Msubsetmathbb{N}$
begin{align}
EBig[E[X|mathcal{A}] 1_B Big]
&=E[X 1_B]\
&=E[Xsum_{min M}1_{A_m}]\
&=E[sum_{min M}X 1_{A_m}]\
&=sum_{min M}E[X 1_{A_m}],text{ since $X$ is bounded we can use Fubini here}\
&=sum_{min M,P(A_m)>0}E[X 1_{A_m}],text{ with the statement above}\
&=sum_{min M,P(A_m)>0}EBig[E[X|A_m] 1_{A_m}Big]\
&=sum_{min M,P(A_m)>0}EBig[E[X|A_m] 1_{A_m}1_BBig],text{ since }1_Bcdot 1_{A_m}=1_{A_m}.\
&=sum_{nge 1,P(A_n)>0}EBig[E[X|A_n] 1_{A_n}1_BBig],text{ since }1_Bcdot 1_{A_n}=0text{ for }nnotin M.\
&=EBig[Big(sum_{nge 1,P(A_n)>0}E[X|A_n] 1_{A_n}Big)1_BBig],text{ again Fubini}\
end{align}
For the Fubini statement see here
real-analysis probability functional-analysis probability-theory stochastic-calculus
add a comment |
up vote
2
down vote
favorite
Consider a probability space $(Omega,mathcal{F},P)$ and a bounded random variable $X$. Let $(A_n)_{nge 1}$ be a countable partition of $Omega$ and define $mathcal{A}:=sigma({A_n:nge 1})$. Then it holds:
$$E[X|mathcal{A}]=sum_{nge 1, P(A_n)>0}E[X|A_n]cdotmathbb{1}_{A_n}$$
One can prove it by using the uniqueness of $E[X|mathcal{A}]$, i.e. I should be done, if I can show that the expression on the right is $mathcal{A}$-measurable, and that for any $Binmathcal{A}$, it holds
$$EBig[E[X|mathcal{A}]cdot 1_BBig]=EBig[Big(sum_{nge 1, P(A_n)>0}E[X|A_n]cdotmathbb{1}_{A_n}Big)cdot 1_BBig]$$
EDIT:
First property: For any $nge 1$: $E[X|A_n]$ and $1_{A_n}$ are $sigma(1_{A_n})$-measurable, therefore $mathcal{A}$-measurable. Now using the fact that products and sums of measurable functions are measurable, we have that
$$sum_{nge 1, P(A_n)>0}E[X|A_n]cdotmathbb{1}_{A_n}$$
is $mathcal{A}$-measurable.
Second property:
Now let $A_ninmathcal{A}$ with $P(A_n)=0$. Then we know that
$$E[Xcdot1_{A_n}]=sum_{omegain A_n}X(omega)cdot underbrace{P({omega})}_{=0}=0.$$
Therefore we have for any $Binmathcal{A}$, i.e. $B=cup_{min M} A_m$ with a countable subset $Msubsetmathbb{N}$
begin{align}
EBig[E[X|mathcal{A}] 1_B Big]
&=E[X 1_B]\
&=E[Xsum_{min M}1_{A_m}]\
&=E[sum_{min M}X 1_{A_m}]\
&=sum_{min M}E[X 1_{A_m}],text{ since $X$ is bounded we can use Fubini here}\
&=sum_{min M,P(A_m)>0}E[X 1_{A_m}],text{ with the statement above}\
&=sum_{min M,P(A_m)>0}EBig[E[X|A_m] 1_{A_m}Big]\
&=sum_{min M,P(A_m)>0}EBig[E[X|A_m] 1_{A_m}1_BBig],text{ since }1_Bcdot 1_{A_m}=1_{A_m}.\
&=sum_{nge 1,P(A_n)>0}EBig[E[X|A_n] 1_{A_n}1_BBig],text{ since }1_Bcdot 1_{A_n}=0text{ for }nnotin M.\
&=EBig[Big(sum_{nge 1,P(A_n)>0}E[X|A_n] 1_{A_n}Big)1_BBig],text{ again Fubini}\
end{align}
For the Fubini statement see here
real-analysis probability functional-analysis probability-theory stochastic-calculus
add a comment |
up vote
2
down vote
favorite
up vote
2
down vote
favorite
Consider a probability space $(Omega,mathcal{F},P)$ and a bounded random variable $X$. Let $(A_n)_{nge 1}$ be a countable partition of $Omega$ and define $mathcal{A}:=sigma({A_n:nge 1})$. Then it holds:
$$E[X|mathcal{A}]=sum_{nge 1, P(A_n)>0}E[X|A_n]cdotmathbb{1}_{A_n}$$
One can prove it by using the uniqueness of $E[X|mathcal{A}]$, i.e. I should be done, if I can show that the expression on the right is $mathcal{A}$-measurable, and that for any $Binmathcal{A}$, it holds
$$EBig[E[X|mathcal{A}]cdot 1_BBig]=EBig[Big(sum_{nge 1, P(A_n)>0}E[X|A_n]cdotmathbb{1}_{A_n}Big)cdot 1_BBig]$$
EDIT:
First property: For any $nge 1$: $E[X|A_n]$ and $1_{A_n}$ are $sigma(1_{A_n})$-measurable, therefore $mathcal{A}$-measurable. Now using the fact that products and sums of measurable functions are measurable, we have that
$$sum_{nge 1, P(A_n)>0}E[X|A_n]cdotmathbb{1}_{A_n}$$
is $mathcal{A}$-measurable.
Second property:
Now let $A_ninmathcal{A}$ with $P(A_n)=0$. Then we know that
$$E[Xcdot1_{A_n}]=sum_{omegain A_n}X(omega)cdot underbrace{P({omega})}_{=0}=0.$$
Therefore we have for any $Binmathcal{A}$, i.e. $B=cup_{min M} A_m$ with a countable subset $Msubsetmathbb{N}$
begin{align}
EBig[E[X|mathcal{A}] 1_B Big]
&=E[X 1_B]\
&=E[Xsum_{min M}1_{A_m}]\
&=E[sum_{min M}X 1_{A_m}]\
&=sum_{min M}E[X 1_{A_m}],text{ since $X$ is bounded we can use Fubini here}\
&=sum_{min M,P(A_m)>0}E[X 1_{A_m}],text{ with the statement above}\
&=sum_{min M,P(A_m)>0}EBig[E[X|A_m] 1_{A_m}Big]\
&=sum_{min M,P(A_m)>0}EBig[E[X|A_m] 1_{A_m}1_BBig],text{ since }1_Bcdot 1_{A_m}=1_{A_m}.\
&=sum_{nge 1,P(A_n)>0}EBig[E[X|A_n] 1_{A_n}1_BBig],text{ since }1_Bcdot 1_{A_n}=0text{ for }nnotin M.\
&=EBig[Big(sum_{nge 1,P(A_n)>0}E[X|A_n] 1_{A_n}Big)1_BBig],text{ again Fubini}\
end{align}
For the Fubini statement see here
real-analysis probability functional-analysis probability-theory stochastic-calculus
Consider a probability space $(Omega,mathcal{F},P)$ and a bounded random variable $X$. Let $(A_n)_{nge 1}$ be a countable partition of $Omega$ and define $mathcal{A}:=sigma({A_n:nge 1})$. Then it holds:
$$E[X|mathcal{A}]=sum_{nge 1, P(A_n)>0}E[X|A_n]cdotmathbb{1}_{A_n}$$
One can prove it by using the uniqueness of $E[X|mathcal{A}]$, i.e. I should be done, if I can show that the expression on the right is $mathcal{A}$-measurable, and that for any $Binmathcal{A}$, it holds
$$EBig[E[X|mathcal{A}]cdot 1_BBig]=EBig[Big(sum_{nge 1, P(A_n)>0}E[X|A_n]cdotmathbb{1}_{A_n}Big)cdot 1_BBig]$$
EDIT:
First property: For any $nge 1$: $E[X|A_n]$ and $1_{A_n}$ are $sigma(1_{A_n})$-measurable, therefore $mathcal{A}$-measurable. Now using the fact that products and sums of measurable functions are measurable, we have that
$$sum_{nge 1, P(A_n)>0}E[X|A_n]cdotmathbb{1}_{A_n}$$
is $mathcal{A}$-measurable.
Second property:
Now let $A_ninmathcal{A}$ with $P(A_n)=0$. Then we know that
$$E[Xcdot1_{A_n}]=sum_{omegain A_n}X(omega)cdot underbrace{P({omega})}_{=0}=0.$$
Therefore we have for any $Binmathcal{A}$, i.e. $B=cup_{min M} A_m$ with a countable subset $Msubsetmathbb{N}$
begin{align}
EBig[E[X|mathcal{A}] 1_B Big]
&=E[X 1_B]\
&=E[Xsum_{min M}1_{A_m}]\
&=E[sum_{min M}X 1_{A_m}]\
&=sum_{min M}E[X 1_{A_m}],text{ since $X$ is bounded we can use Fubini here}\
&=sum_{min M,P(A_m)>0}E[X 1_{A_m}],text{ with the statement above}\
&=sum_{min M,P(A_m)>0}EBig[E[X|A_m] 1_{A_m}Big]\
&=sum_{min M,P(A_m)>0}EBig[E[X|A_m] 1_{A_m}1_BBig],text{ since }1_Bcdot 1_{A_m}=1_{A_m}.\
&=sum_{nge 1,P(A_n)>0}EBig[E[X|A_n] 1_{A_n}1_BBig],text{ since }1_Bcdot 1_{A_n}=0text{ for }nnotin M.\
&=EBig[Big(sum_{nge 1,P(A_n)>0}E[X|A_n] 1_{A_n}Big)1_BBig],text{ again Fubini}\
end{align}
For the Fubini statement see here
real-analysis probability functional-analysis probability-theory stochastic-calculus
real-analysis probability functional-analysis probability-theory stochastic-calculus
edited Nov 15 at 22:32
asked Nov 14 at 21:29
user408858
19510
19510
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
up vote
2
down vote
accepted
Assume for simplicity that $mathsf{P}(A_i)>0$ for all $i$. Every element of $mathcal{A}$ is an at most countable union of sets in $(A_n)$. Thus, for $B=bigcup_{i}A_i$,
$$
mathsf{E}X1_B=sum_{i}mathsf{E}[X1_{A_i}]=sum_{i}mathsf{E}[mathsf{E}[Xmid A_i]1_{A_i}]=mathsf{E}left[sum_imathsf{E}[Xmid A_i]1_{A_i}1_Bright]
$$
because $(A_n)$ are disjoint and $X$ is bounded (although, it suffices to assume that $mathsf{E}|X|<infty$).
Ok, I see, this is exactly that calculation I was missing in my edit. Still, I have to figure out, where I need that $X$ is bounded. I will give it a try tomorrow. Thank you already for your reply! :-)
– user408858
Nov 14 at 22:43
add a comment |
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
2
down vote
accepted
Assume for simplicity that $mathsf{P}(A_i)>0$ for all $i$. Every element of $mathcal{A}$ is an at most countable union of sets in $(A_n)$. Thus, for $B=bigcup_{i}A_i$,
$$
mathsf{E}X1_B=sum_{i}mathsf{E}[X1_{A_i}]=sum_{i}mathsf{E}[mathsf{E}[Xmid A_i]1_{A_i}]=mathsf{E}left[sum_imathsf{E}[Xmid A_i]1_{A_i}1_Bright]
$$
because $(A_n)$ are disjoint and $X$ is bounded (although, it suffices to assume that $mathsf{E}|X|<infty$).
Ok, I see, this is exactly that calculation I was missing in my edit. Still, I have to figure out, where I need that $X$ is bounded. I will give it a try tomorrow. Thank you already for your reply! :-)
– user408858
Nov 14 at 22:43
add a comment |
up vote
2
down vote
accepted
Assume for simplicity that $mathsf{P}(A_i)>0$ for all $i$. Every element of $mathcal{A}$ is an at most countable union of sets in $(A_n)$. Thus, for $B=bigcup_{i}A_i$,
$$
mathsf{E}X1_B=sum_{i}mathsf{E}[X1_{A_i}]=sum_{i}mathsf{E}[mathsf{E}[Xmid A_i]1_{A_i}]=mathsf{E}left[sum_imathsf{E}[Xmid A_i]1_{A_i}1_Bright]
$$
because $(A_n)$ are disjoint and $X$ is bounded (although, it suffices to assume that $mathsf{E}|X|<infty$).
Ok, I see, this is exactly that calculation I was missing in my edit. Still, I have to figure out, where I need that $X$ is bounded. I will give it a try tomorrow. Thank you already for your reply! :-)
– user408858
Nov 14 at 22:43
add a comment |
up vote
2
down vote
accepted
up vote
2
down vote
accepted
Assume for simplicity that $mathsf{P}(A_i)>0$ for all $i$. Every element of $mathcal{A}$ is an at most countable union of sets in $(A_n)$. Thus, for $B=bigcup_{i}A_i$,
$$
mathsf{E}X1_B=sum_{i}mathsf{E}[X1_{A_i}]=sum_{i}mathsf{E}[mathsf{E}[Xmid A_i]1_{A_i}]=mathsf{E}left[sum_imathsf{E}[Xmid A_i]1_{A_i}1_Bright]
$$
because $(A_n)$ are disjoint and $X$ is bounded (although, it suffices to assume that $mathsf{E}|X|<infty$).
Assume for simplicity that $mathsf{P}(A_i)>0$ for all $i$. Every element of $mathcal{A}$ is an at most countable union of sets in $(A_n)$. Thus, for $B=bigcup_{i}A_i$,
$$
mathsf{E}X1_B=sum_{i}mathsf{E}[X1_{A_i}]=sum_{i}mathsf{E}[mathsf{E}[Xmid A_i]1_{A_i}]=mathsf{E}left[sum_imathsf{E}[Xmid A_i]1_{A_i}1_Bright]
$$
because $(A_n)$ are disjoint and $X$ is bounded (although, it suffices to assume that $mathsf{E}|X|<infty$).
edited Nov 15 at 9:51
answered Nov 14 at 22:36
d.k.o.
8,089527
8,089527
Ok, I see, this is exactly that calculation I was missing in my edit. Still, I have to figure out, where I need that $X$ is bounded. I will give it a try tomorrow. Thank you already for your reply! :-)
– user408858
Nov 14 at 22:43
add a comment |
Ok, I see, this is exactly that calculation I was missing in my edit. Still, I have to figure out, where I need that $X$ is bounded. I will give it a try tomorrow. Thank you already for your reply! :-)
– user408858
Nov 14 at 22:43
Ok, I see, this is exactly that calculation I was missing in my edit. Still, I have to figure out, where I need that $X$ is bounded. I will give it a try tomorrow. Thank you already for your reply! :-)
– user408858
Nov 14 at 22:43
Ok, I see, this is exactly that calculation I was missing in my edit. Still, I have to figure out, where I need that $X$ is bounded. I will give it a try tomorrow. Thank you already for your reply! :-)
– user408858
Nov 14 at 22:43
add a comment |
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f2998838%2fconditional-expectation-for-a-partition%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown