A proper definition of recurrent event in probability
I am having hard time understanding the definition of a recurrent event in probability context.
At our lecture it was defined as follows:
Let $X^{[i,n]} = {X_i, ldots, X_n}$ be a random sequence. The random variables $X_j$ can attain countably many values. An event $epsilon$ that appears on the $n$-th and the $m+n$-th place of sequence $X^{[1,m+n]}$ is called recurrent if and only if it occurs on the last place of the sequence $X^{[1,n]}$ and on the last place of the sequence $X^{[n+1,n+m]}$.
Then $Prob(X^{[1,n+m]}) = Prob(X^{[1,n]})cdot Prob(X^{[n+1,n+m]})$.
An event $epsilon$ could be for example the event when $S_n = sum_{j=i}^nX_j = 0$.
The variables $X_i$ may be dependent in some way. It is clear that the multiplication rule holds if the events are independent. However, I do not understand, why the multiplication rule should apply in general.
Is it possible, that the event is recurrent if the multiplication rule applies?
The closest definition I could find online to what we defined in the lecture can be seen on this webpage. It is probably more exact, but I really struggle tu wrap my head around it.
Could anyone please explain, why the multiplication rule holds for recurrent events and potentialy elaborate on the definition from the link? Any help would be very appreciated!
probability probability-theory stochastic-processes recurrence-relations random-walk
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I am having hard time understanding the definition of a recurrent event in probability context.
At our lecture it was defined as follows:
Let $X^{[i,n]} = {X_i, ldots, X_n}$ be a random sequence. The random variables $X_j$ can attain countably many values. An event $epsilon$ that appears on the $n$-th and the $m+n$-th place of sequence $X^{[1,m+n]}$ is called recurrent if and only if it occurs on the last place of the sequence $X^{[1,n]}$ and on the last place of the sequence $X^{[n+1,n+m]}$.
Then $Prob(X^{[1,n+m]}) = Prob(X^{[1,n]})cdot Prob(X^{[n+1,n+m]})$.
An event $epsilon$ could be for example the event when $S_n = sum_{j=i}^nX_j = 0$.
The variables $X_i$ may be dependent in some way. It is clear that the multiplication rule holds if the events are independent. However, I do not understand, why the multiplication rule should apply in general.
Is it possible, that the event is recurrent if the multiplication rule applies?
The closest definition I could find online to what we defined in the lecture can be seen on this webpage. It is probably more exact, but I really struggle tu wrap my head around it.
Could anyone please explain, why the multiplication rule holds for recurrent events and potentialy elaborate on the definition from the link? Any help would be very appreciated!
probability probability-theory stochastic-processes recurrence-relations random-walk
add a comment |
I am having hard time understanding the definition of a recurrent event in probability context.
At our lecture it was defined as follows:
Let $X^{[i,n]} = {X_i, ldots, X_n}$ be a random sequence. The random variables $X_j$ can attain countably many values. An event $epsilon$ that appears on the $n$-th and the $m+n$-th place of sequence $X^{[1,m+n]}$ is called recurrent if and only if it occurs on the last place of the sequence $X^{[1,n]}$ and on the last place of the sequence $X^{[n+1,n+m]}$.
Then $Prob(X^{[1,n+m]}) = Prob(X^{[1,n]})cdot Prob(X^{[n+1,n+m]})$.
An event $epsilon$ could be for example the event when $S_n = sum_{j=i}^nX_j = 0$.
The variables $X_i$ may be dependent in some way. It is clear that the multiplication rule holds if the events are independent. However, I do not understand, why the multiplication rule should apply in general.
Is it possible, that the event is recurrent if the multiplication rule applies?
The closest definition I could find online to what we defined in the lecture can be seen on this webpage. It is probably more exact, but I really struggle tu wrap my head around it.
Could anyone please explain, why the multiplication rule holds for recurrent events and potentialy elaborate on the definition from the link? Any help would be very appreciated!
probability probability-theory stochastic-processes recurrence-relations random-walk
I am having hard time understanding the definition of a recurrent event in probability context.
At our lecture it was defined as follows:
Let $X^{[i,n]} = {X_i, ldots, X_n}$ be a random sequence. The random variables $X_j$ can attain countably many values. An event $epsilon$ that appears on the $n$-th and the $m+n$-th place of sequence $X^{[1,m+n]}$ is called recurrent if and only if it occurs on the last place of the sequence $X^{[1,n]}$ and on the last place of the sequence $X^{[n+1,n+m]}$.
Then $Prob(X^{[1,n+m]}) = Prob(X^{[1,n]})cdot Prob(X^{[n+1,n+m]})$.
An event $epsilon$ could be for example the event when $S_n = sum_{j=i}^nX_j = 0$.
The variables $X_i$ may be dependent in some way. It is clear that the multiplication rule holds if the events are independent. However, I do not understand, why the multiplication rule should apply in general.
Is it possible, that the event is recurrent if the multiplication rule applies?
The closest definition I could find online to what we defined in the lecture can be seen on this webpage. It is probably more exact, but I really struggle tu wrap my head around it.
Could anyone please explain, why the multiplication rule holds for recurrent events and potentialy elaborate on the definition from the link? Any help would be very appreciated!
probability probability-theory stochastic-processes recurrence-relations random-walk
probability probability-theory stochastic-processes recurrence-relations random-walk
edited Jan 4 at 19:20
Jan Vainer
asked Jan 4 at 18:39
Jan VainerJan Vainer
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