Conditioning on an union of sigma algebras
$begingroup$
Let $Omega = [0,1]$, $mathcal{F} = mathcal{B}(0,1)$, P=Lebesgue measure.
Let $X(w)=
begin{cases}
1 quad w in [0,1/2] \
0 quad w notin [0,1/2]
end{cases}$
Let $Y(w)=
begin{cases}
1 quad w in [0,3/4] \
0 quad w notin [0,3/4]
end{cases}$
Let $Z(w)=
begin{cases}
1 quad w in [1/4,3/4] \
0 quad w notin [1/4,3/4]
end{cases}$
I succeeded in proving that X is independent from Z and E(X|Y=1)=2/3 conditioning on the sub-sigma algebras generated by Z and Y, respectively.
Now my aim is discovering the value of E{X|(Y,Z)} but I don't know how to condition X on an union of sigma algebras.
measure-theory lebesgue-measure conditional-expectation
$endgroup$
add a comment |
$begingroup$
Let $Omega = [0,1]$, $mathcal{F} = mathcal{B}(0,1)$, P=Lebesgue measure.
Let $X(w)=
begin{cases}
1 quad w in [0,1/2] \
0 quad w notin [0,1/2]
end{cases}$
Let $Y(w)=
begin{cases}
1 quad w in [0,3/4] \
0 quad w notin [0,3/4]
end{cases}$
Let $Z(w)=
begin{cases}
1 quad w in [1/4,3/4] \
0 quad w notin [1/4,3/4]
end{cases}$
I succeeded in proving that X is independent from Z and E(X|Y=1)=2/3 conditioning on the sub-sigma algebras generated by Z and Y, respectively.
Now my aim is discovering the value of E{X|(Y,Z)} but I don't know how to condition X on an union of sigma algebras.
measure-theory lebesgue-measure conditional-expectation
$endgroup$
add a comment |
$begingroup$
Let $Omega = [0,1]$, $mathcal{F} = mathcal{B}(0,1)$, P=Lebesgue measure.
Let $X(w)=
begin{cases}
1 quad w in [0,1/2] \
0 quad w notin [0,1/2]
end{cases}$
Let $Y(w)=
begin{cases}
1 quad w in [0,3/4] \
0 quad w notin [0,3/4]
end{cases}$
Let $Z(w)=
begin{cases}
1 quad w in [1/4,3/4] \
0 quad w notin [1/4,3/4]
end{cases}$
I succeeded in proving that X is independent from Z and E(X|Y=1)=2/3 conditioning on the sub-sigma algebras generated by Z and Y, respectively.
Now my aim is discovering the value of E{X|(Y,Z)} but I don't know how to condition X on an union of sigma algebras.
measure-theory lebesgue-measure conditional-expectation
$endgroup$
Let $Omega = [0,1]$, $mathcal{F} = mathcal{B}(0,1)$, P=Lebesgue measure.
Let $X(w)=
begin{cases}
1 quad w in [0,1/2] \
0 quad w notin [0,1/2]
end{cases}$
Let $Y(w)=
begin{cases}
1 quad w in [0,3/4] \
0 quad w notin [0,3/4]
end{cases}$
Let $Z(w)=
begin{cases}
1 quad w in [1/4,3/4] \
0 quad w notin [1/4,3/4]
end{cases}$
I succeeded in proving that X is independent from Z and E(X|Y=1)=2/3 conditioning on the sub-sigma algebras generated by Z and Y, respectively.
Now my aim is discovering the value of E{X|(Y,Z)} but I don't know how to condition X on an union of sigma algebras.
measure-theory lebesgue-measure conditional-expectation
measure-theory lebesgue-measure conditional-expectation
edited Jan 18 at 11:58
ank13
asked Jan 18 at 11:46
ank13ank13
255
255
add a comment |
add a comment |
3 Answers
3
active
oldest
votes
$begingroup$
- $mathbb E[Xmid Y=1,Z=1]=P(win[0,frac12]mid win[frac14,frac34])=P(win[frac14,frac12]/P(win[frac14,frac34])=frac12$
- $mathbb E[Xmid Y=1,Z=0]=P(win[0,frac12]mid win[0,frac14))=P(win[0,frac14)/P(win[0,frac14))=1$
- $mathbb E[Xmid Y=0,Z=0]=P(win[0,frac12]mid win(frac34,1])=P(winvarnothing)/P(win(frac34,1])=0$
Observe that ${Y=0,Z=1}=varnothing$ so conditioning on that event can be left out.
This shows that: $$mathbb E[Xmid (Y,Z)]=Y-frac12Z$$
$endgroup$
add a comment |
$begingroup$
Hint: Note that $$
Y^{-1}({1})=[0,frac{3}{4}],
$$
$$
Z^{-1}({1})=[frac{1}{4},frac{3}{4}].
$$ It says that the $sigma$-algebra generated by $(Y,Z)$ is also generated by
$
[0,frac{1}{4}]=Y^{-1}({1})setminus Z^{-1}({1})
$ and $[frac{1}{4},frac{3}{4}]$.
$endgroup$
add a comment |
$begingroup$
For whatever it is worth, let me describe a general procedure for answering such questions. It is easy to write $sigma(Y,Z)$ as the sigma algebra generated by a partition ${A_1,A_2,cdots ,A_n}$. Once you identify the sets $A_i$ you can compute $E(X|Y,Z)$ by the formula $E(X|Y,Z)=sum c_iI_{A_i}$ where $c_i=frac {int_{A_i} XdP} {P(A_i)}$.
$endgroup$
add a comment |
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3 Answers
3
active
oldest
votes
3 Answers
3
active
oldest
votes
active
oldest
votes
active
oldest
votes
$begingroup$
- $mathbb E[Xmid Y=1,Z=1]=P(win[0,frac12]mid win[frac14,frac34])=P(win[frac14,frac12]/P(win[frac14,frac34])=frac12$
- $mathbb E[Xmid Y=1,Z=0]=P(win[0,frac12]mid win[0,frac14))=P(win[0,frac14)/P(win[0,frac14))=1$
- $mathbb E[Xmid Y=0,Z=0]=P(win[0,frac12]mid win(frac34,1])=P(winvarnothing)/P(win(frac34,1])=0$
Observe that ${Y=0,Z=1}=varnothing$ so conditioning on that event can be left out.
This shows that: $$mathbb E[Xmid (Y,Z)]=Y-frac12Z$$
$endgroup$
add a comment |
$begingroup$
- $mathbb E[Xmid Y=1,Z=1]=P(win[0,frac12]mid win[frac14,frac34])=P(win[frac14,frac12]/P(win[frac14,frac34])=frac12$
- $mathbb E[Xmid Y=1,Z=0]=P(win[0,frac12]mid win[0,frac14))=P(win[0,frac14)/P(win[0,frac14))=1$
- $mathbb E[Xmid Y=0,Z=0]=P(win[0,frac12]mid win(frac34,1])=P(winvarnothing)/P(win(frac34,1])=0$
Observe that ${Y=0,Z=1}=varnothing$ so conditioning on that event can be left out.
This shows that: $$mathbb E[Xmid (Y,Z)]=Y-frac12Z$$
$endgroup$
add a comment |
$begingroup$
- $mathbb E[Xmid Y=1,Z=1]=P(win[0,frac12]mid win[frac14,frac34])=P(win[frac14,frac12]/P(win[frac14,frac34])=frac12$
- $mathbb E[Xmid Y=1,Z=0]=P(win[0,frac12]mid win[0,frac14))=P(win[0,frac14)/P(win[0,frac14))=1$
- $mathbb E[Xmid Y=0,Z=0]=P(win[0,frac12]mid win(frac34,1])=P(winvarnothing)/P(win(frac34,1])=0$
Observe that ${Y=0,Z=1}=varnothing$ so conditioning on that event can be left out.
This shows that: $$mathbb E[Xmid (Y,Z)]=Y-frac12Z$$
$endgroup$
- $mathbb E[Xmid Y=1,Z=1]=P(win[0,frac12]mid win[frac14,frac34])=P(win[frac14,frac12]/P(win[frac14,frac34])=frac12$
- $mathbb E[Xmid Y=1,Z=0]=P(win[0,frac12]mid win[0,frac14))=P(win[0,frac14)/P(win[0,frac14))=1$
- $mathbb E[Xmid Y=0,Z=0]=P(win[0,frac12]mid win(frac34,1])=P(winvarnothing)/P(win(frac34,1])=0$
Observe that ${Y=0,Z=1}=varnothing$ so conditioning on that event can be left out.
This shows that: $$mathbb E[Xmid (Y,Z)]=Y-frac12Z$$
answered Jan 18 at 12:22


drhabdrhab
102k545136
102k545136
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$begingroup$
Hint: Note that $$
Y^{-1}({1})=[0,frac{3}{4}],
$$
$$
Z^{-1}({1})=[frac{1}{4},frac{3}{4}].
$$ It says that the $sigma$-algebra generated by $(Y,Z)$ is also generated by
$
[0,frac{1}{4}]=Y^{-1}({1})setminus Z^{-1}({1})
$ and $[frac{1}{4},frac{3}{4}]$.
$endgroup$
add a comment |
$begingroup$
Hint: Note that $$
Y^{-1}({1})=[0,frac{3}{4}],
$$
$$
Z^{-1}({1})=[frac{1}{4},frac{3}{4}].
$$ It says that the $sigma$-algebra generated by $(Y,Z)$ is also generated by
$
[0,frac{1}{4}]=Y^{-1}({1})setminus Z^{-1}({1})
$ and $[frac{1}{4},frac{3}{4}]$.
$endgroup$
add a comment |
$begingroup$
Hint: Note that $$
Y^{-1}({1})=[0,frac{3}{4}],
$$
$$
Z^{-1}({1})=[frac{1}{4},frac{3}{4}].
$$ It says that the $sigma$-algebra generated by $(Y,Z)$ is also generated by
$
[0,frac{1}{4}]=Y^{-1}({1})setminus Z^{-1}({1})
$ and $[frac{1}{4},frac{3}{4}]$.
$endgroup$
Hint: Note that $$
Y^{-1}({1})=[0,frac{3}{4}],
$$
$$
Z^{-1}({1})=[frac{1}{4},frac{3}{4}].
$$ It says that the $sigma$-algebra generated by $(Y,Z)$ is also generated by
$
[0,frac{1}{4}]=Y^{-1}({1})setminus Z^{-1}({1})
$ and $[frac{1}{4},frac{3}{4}]$.
answered Jan 18 at 12:24
SongSong
15.6k1736
15.6k1736
add a comment |
add a comment |
$begingroup$
For whatever it is worth, let me describe a general procedure for answering such questions. It is easy to write $sigma(Y,Z)$ as the sigma algebra generated by a partition ${A_1,A_2,cdots ,A_n}$. Once you identify the sets $A_i$ you can compute $E(X|Y,Z)$ by the formula $E(X|Y,Z)=sum c_iI_{A_i}$ where $c_i=frac {int_{A_i} XdP} {P(A_i)}$.
$endgroup$
add a comment |
$begingroup$
For whatever it is worth, let me describe a general procedure for answering such questions. It is easy to write $sigma(Y,Z)$ as the sigma algebra generated by a partition ${A_1,A_2,cdots ,A_n}$. Once you identify the sets $A_i$ you can compute $E(X|Y,Z)$ by the formula $E(X|Y,Z)=sum c_iI_{A_i}$ where $c_i=frac {int_{A_i} XdP} {P(A_i)}$.
$endgroup$
add a comment |
$begingroup$
For whatever it is worth, let me describe a general procedure for answering such questions. It is easy to write $sigma(Y,Z)$ as the sigma algebra generated by a partition ${A_1,A_2,cdots ,A_n}$. Once you identify the sets $A_i$ you can compute $E(X|Y,Z)$ by the formula $E(X|Y,Z)=sum c_iI_{A_i}$ where $c_i=frac {int_{A_i} XdP} {P(A_i)}$.
$endgroup$
For whatever it is worth, let me describe a general procedure for answering such questions. It is easy to write $sigma(Y,Z)$ as the sigma algebra generated by a partition ${A_1,A_2,cdots ,A_n}$. Once you identify the sets $A_i$ you can compute $E(X|Y,Z)$ by the formula $E(X|Y,Z)=sum c_iI_{A_i}$ where $c_i=frac {int_{A_i} XdP} {P(A_i)}$.
answered Jan 18 at 12:30


Kavi Rama MurthyKavi Rama Murthy
63.2k42362
63.2k42362
add a comment |
add a comment |
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