Correlation coefficient of a WSS process
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Could someone please tell me why the correlation coefficient of a WSS process is :
$$rho_{XX}(tau) = frac{operatorname{K}_{XX}(tau)}{sigma^2} = frac{operatorname{E}[(X_t - mu)(X_{t+tau} - mu)]}{sigma^2}$$
Instead of :
$$rho_{XX}(tau) = frac{operatorname{K}_{XX}(tau)}{sigma_{t}sigma_{t+tau}} = frac{operatorname{E}[(X_t - mu)(X_{t+tau} - mu)]}{sigma_{t}sigma_{t+tau}} $$
?
Where :$~~~sigma_{t}^2=sigma^2=operatorname{E}[X^2(t)]-operatorname{E}^2[X(t)]$ .
Stated in another way , does a WSS process imply that :
$$operatorname{E}[X^2(t+tau)]=operatorname{E}[X^2(t)]$$ ?
(https://en.wikipedia.org/wiki/Autocovariance)
probability
$endgroup$
add a comment |
$begingroup$
Could someone please tell me why the correlation coefficient of a WSS process is :
$$rho_{XX}(tau) = frac{operatorname{K}_{XX}(tau)}{sigma^2} = frac{operatorname{E}[(X_t - mu)(X_{t+tau} - mu)]}{sigma^2}$$
Instead of :
$$rho_{XX}(tau) = frac{operatorname{K}_{XX}(tau)}{sigma_{t}sigma_{t+tau}} = frac{operatorname{E}[(X_t - mu)(X_{t+tau} - mu)]}{sigma_{t}sigma_{t+tau}} $$
?
Where :$~~~sigma_{t}^2=sigma^2=operatorname{E}[X^2(t)]-operatorname{E}^2[X(t)]$ .
Stated in another way , does a WSS process imply that :
$$operatorname{E}[X^2(t+tau)]=operatorname{E}[X^2(t)]$$ ?
(https://en.wikipedia.org/wiki/Autocovariance)
probability
$endgroup$
add a comment |
$begingroup$
Could someone please tell me why the correlation coefficient of a WSS process is :
$$rho_{XX}(tau) = frac{operatorname{K}_{XX}(tau)}{sigma^2} = frac{operatorname{E}[(X_t - mu)(X_{t+tau} - mu)]}{sigma^2}$$
Instead of :
$$rho_{XX}(tau) = frac{operatorname{K}_{XX}(tau)}{sigma_{t}sigma_{t+tau}} = frac{operatorname{E}[(X_t - mu)(X_{t+tau} - mu)]}{sigma_{t}sigma_{t+tau}} $$
?
Where :$~~~sigma_{t}^2=sigma^2=operatorname{E}[X^2(t)]-operatorname{E}^2[X(t)]$ .
Stated in another way , does a WSS process imply that :
$$operatorname{E}[X^2(t+tau)]=operatorname{E}[X^2(t)]$$ ?
(https://en.wikipedia.org/wiki/Autocovariance)
probability
$endgroup$
Could someone please tell me why the correlation coefficient of a WSS process is :
$$rho_{XX}(tau) = frac{operatorname{K}_{XX}(tau)}{sigma^2} = frac{operatorname{E}[(X_t - mu)(X_{t+tau} - mu)]}{sigma^2}$$
Instead of :
$$rho_{XX}(tau) = frac{operatorname{K}_{XX}(tau)}{sigma_{t}sigma_{t+tau}} = frac{operatorname{E}[(X_t - mu)(X_{t+tau} - mu)]}{sigma_{t}sigma_{t+tau}} $$
?
Where :$~~~sigma_{t}^2=sigma^2=operatorname{E}[X^2(t)]-operatorname{E}^2[X(t)]$ .
Stated in another way , does a WSS process imply that :
$$operatorname{E}[X^2(t+tau)]=operatorname{E}[X^2(t)]$$ ?
(https://en.wikipedia.org/wiki/Autocovariance)
probability
probability
asked Jan 4 at 16:37
HilbertHilbert
1769
1769
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1 Answer
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Weak stationary implies that for all fixed $tau$, the function $tmapsto mathbb Eleft[X_{t+tau}X_tright]$ is constant. In particular, choosing $tau=0$ shows that $mathbb Eleft[X_{t+0}X_tright]=mathbb Eleft[X_t^2right]=mathbb Eleft[X_0^2right]$. The other part of the definition of weakly stationary process implies that the expectation of $X_t$ does not depend on $t$ hence we can safely define $sigma^2:=operatorname{Var}left(X_tright)$.
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I do understand that part but the problem is why they've replaced $sigma_{t}sigma_{t+tau}$ by $sigma^2_{t}$ ?
$endgroup$
– Hilbert
Jan 4 at 17:21
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Because $sigma_{t+tau}=sigma_{t}$.
$endgroup$
– Davide Giraudo
Jan 4 at 17:24
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This is the very relation that I am trying to prove/understand , how is this equality justified : $$sigma(t+tau) =(operatorname{E}[X^2(t+tau)]-operatorname{E}^2[X(t+tau)])^frac{1}{2}~=~(operatorname{E}[X^2(t+tau)]-operatorname{E}^2[X(t)])^frac{1}{2}~ =? ~(operatorname{E}[X^2(t)]-operatorname{E}^2[X(t)])^frac{1}{2} $$ So basically why : $$operatorname{E}[X^2(t)]~ =~operatorname{E}[X^2(t+tau)]$$ ?
$endgroup$
– Hilbert
Jan 4 at 17:33
add a comment |
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1 Answer
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1 Answer
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active
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active
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active
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$begingroup$
Weak stationary implies that for all fixed $tau$, the function $tmapsto mathbb Eleft[X_{t+tau}X_tright]$ is constant. In particular, choosing $tau=0$ shows that $mathbb Eleft[X_{t+0}X_tright]=mathbb Eleft[X_t^2right]=mathbb Eleft[X_0^2right]$. The other part of the definition of weakly stationary process implies that the expectation of $X_t$ does not depend on $t$ hence we can safely define $sigma^2:=operatorname{Var}left(X_tright)$.
$endgroup$
$begingroup$
I do understand that part but the problem is why they've replaced $sigma_{t}sigma_{t+tau}$ by $sigma^2_{t}$ ?
$endgroup$
– Hilbert
Jan 4 at 17:21
$begingroup$
Because $sigma_{t+tau}=sigma_{t}$.
$endgroup$
– Davide Giraudo
Jan 4 at 17:24
$begingroup$
This is the very relation that I am trying to prove/understand , how is this equality justified : $$sigma(t+tau) =(operatorname{E}[X^2(t+tau)]-operatorname{E}^2[X(t+tau)])^frac{1}{2}~=~(operatorname{E}[X^2(t+tau)]-operatorname{E}^2[X(t)])^frac{1}{2}~ =? ~(operatorname{E}[X^2(t)]-operatorname{E}^2[X(t)])^frac{1}{2} $$ So basically why : $$operatorname{E}[X^2(t)]~ =~operatorname{E}[X^2(t+tau)]$$ ?
$endgroup$
– Hilbert
Jan 4 at 17:33
add a comment |
$begingroup$
Weak stationary implies that for all fixed $tau$, the function $tmapsto mathbb Eleft[X_{t+tau}X_tright]$ is constant. In particular, choosing $tau=0$ shows that $mathbb Eleft[X_{t+0}X_tright]=mathbb Eleft[X_t^2right]=mathbb Eleft[X_0^2right]$. The other part of the definition of weakly stationary process implies that the expectation of $X_t$ does not depend on $t$ hence we can safely define $sigma^2:=operatorname{Var}left(X_tright)$.
$endgroup$
$begingroup$
I do understand that part but the problem is why they've replaced $sigma_{t}sigma_{t+tau}$ by $sigma^2_{t}$ ?
$endgroup$
– Hilbert
Jan 4 at 17:21
$begingroup$
Because $sigma_{t+tau}=sigma_{t}$.
$endgroup$
– Davide Giraudo
Jan 4 at 17:24
$begingroup$
This is the very relation that I am trying to prove/understand , how is this equality justified : $$sigma(t+tau) =(operatorname{E}[X^2(t+tau)]-operatorname{E}^2[X(t+tau)])^frac{1}{2}~=~(operatorname{E}[X^2(t+tau)]-operatorname{E}^2[X(t)])^frac{1}{2}~ =? ~(operatorname{E}[X^2(t)]-operatorname{E}^2[X(t)])^frac{1}{2} $$ So basically why : $$operatorname{E}[X^2(t)]~ =~operatorname{E}[X^2(t+tau)]$$ ?
$endgroup$
– Hilbert
Jan 4 at 17:33
add a comment |
$begingroup$
Weak stationary implies that for all fixed $tau$, the function $tmapsto mathbb Eleft[X_{t+tau}X_tright]$ is constant. In particular, choosing $tau=0$ shows that $mathbb Eleft[X_{t+0}X_tright]=mathbb Eleft[X_t^2right]=mathbb Eleft[X_0^2right]$. The other part of the definition of weakly stationary process implies that the expectation of $X_t$ does not depend on $t$ hence we can safely define $sigma^2:=operatorname{Var}left(X_tright)$.
$endgroup$
Weak stationary implies that for all fixed $tau$, the function $tmapsto mathbb Eleft[X_{t+tau}X_tright]$ is constant. In particular, choosing $tau=0$ shows that $mathbb Eleft[X_{t+0}X_tright]=mathbb Eleft[X_t^2right]=mathbb Eleft[X_0^2right]$. The other part of the definition of weakly stationary process implies that the expectation of $X_t$ does not depend on $t$ hence we can safely define $sigma^2:=operatorname{Var}left(X_tright)$.
answered Jan 4 at 16:50
Davide GiraudoDavide Giraudo
128k17156268
128k17156268
$begingroup$
I do understand that part but the problem is why they've replaced $sigma_{t}sigma_{t+tau}$ by $sigma^2_{t}$ ?
$endgroup$
– Hilbert
Jan 4 at 17:21
$begingroup$
Because $sigma_{t+tau}=sigma_{t}$.
$endgroup$
– Davide Giraudo
Jan 4 at 17:24
$begingroup$
This is the very relation that I am trying to prove/understand , how is this equality justified : $$sigma(t+tau) =(operatorname{E}[X^2(t+tau)]-operatorname{E}^2[X(t+tau)])^frac{1}{2}~=~(operatorname{E}[X^2(t+tau)]-operatorname{E}^2[X(t)])^frac{1}{2}~ =? ~(operatorname{E}[X^2(t)]-operatorname{E}^2[X(t)])^frac{1}{2} $$ So basically why : $$operatorname{E}[X^2(t)]~ =~operatorname{E}[X^2(t+tau)]$$ ?
$endgroup$
– Hilbert
Jan 4 at 17:33
add a comment |
$begingroup$
I do understand that part but the problem is why they've replaced $sigma_{t}sigma_{t+tau}$ by $sigma^2_{t}$ ?
$endgroup$
– Hilbert
Jan 4 at 17:21
$begingroup$
Because $sigma_{t+tau}=sigma_{t}$.
$endgroup$
– Davide Giraudo
Jan 4 at 17:24
$begingroup$
This is the very relation that I am trying to prove/understand , how is this equality justified : $$sigma(t+tau) =(operatorname{E}[X^2(t+tau)]-operatorname{E}^2[X(t+tau)])^frac{1}{2}~=~(operatorname{E}[X^2(t+tau)]-operatorname{E}^2[X(t)])^frac{1}{2}~ =? ~(operatorname{E}[X^2(t)]-operatorname{E}^2[X(t)])^frac{1}{2} $$ So basically why : $$operatorname{E}[X^2(t)]~ =~operatorname{E}[X^2(t+tau)]$$ ?
$endgroup$
– Hilbert
Jan 4 at 17:33
$begingroup$
I do understand that part but the problem is why they've replaced $sigma_{t}sigma_{t+tau}$ by $sigma^2_{t}$ ?
$endgroup$
– Hilbert
Jan 4 at 17:21
$begingroup$
I do understand that part but the problem is why they've replaced $sigma_{t}sigma_{t+tau}$ by $sigma^2_{t}$ ?
$endgroup$
– Hilbert
Jan 4 at 17:21
$begingroup$
Because $sigma_{t+tau}=sigma_{t}$.
$endgroup$
– Davide Giraudo
Jan 4 at 17:24
$begingroup$
Because $sigma_{t+tau}=sigma_{t}$.
$endgroup$
– Davide Giraudo
Jan 4 at 17:24
$begingroup$
This is the very relation that I am trying to prove/understand , how is this equality justified : $$sigma(t+tau) =(operatorname{E}[X^2(t+tau)]-operatorname{E}^2[X(t+tau)])^frac{1}{2}~=~(operatorname{E}[X^2(t+tau)]-operatorname{E}^2[X(t)])^frac{1}{2}~ =? ~(operatorname{E}[X^2(t)]-operatorname{E}^2[X(t)])^frac{1}{2} $$ So basically why : $$operatorname{E}[X^2(t)]~ =~operatorname{E}[X^2(t+tau)]$$ ?
$endgroup$
– Hilbert
Jan 4 at 17:33
$begingroup$
This is the very relation that I am trying to prove/understand , how is this equality justified : $$sigma(t+tau) =(operatorname{E}[X^2(t+tau)]-operatorname{E}^2[X(t+tau)])^frac{1}{2}~=~(operatorname{E}[X^2(t+tau)]-operatorname{E}^2[X(t)])^frac{1}{2}~ =? ~(operatorname{E}[X^2(t)]-operatorname{E}^2[X(t)])^frac{1}{2} $$ So basically why : $$operatorname{E}[X^2(t)]~ =~operatorname{E}[X^2(t+tau)]$$ ?
$endgroup$
– Hilbert
Jan 4 at 17:33
add a comment |
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