Conditional expectation for a partition











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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










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    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










    share|cite|improve this question


























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      up vote
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      down vote

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      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










      share|cite|improve this question















      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






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      edited Nov 15 at 22:32

























      asked Nov 14 at 21:29









      user408858

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          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 $mathsf{E}|X|<infty$).






          share|cite|improve this answer























          • 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













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          up vote
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          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 $mathsf{E}|X|<infty$).






          share|cite|improve this answer























          • 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

















          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 $mathsf{E}|X|<infty$).






          share|cite|improve this answer























          • 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















          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 $mathsf{E}|X|<infty$).






          share|cite|improve this answer














          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 $mathsf{E}|X|<infty$).







          share|cite|improve this answer














          share|cite|improve this answer



          share|cite|improve this answer








          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




















          • 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




















           

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