generating function of numbers of visits up to time n
I want to determine the generating function of the numbers of visits up to a specific time. Formally: let ${X_{n}}_{n geq 0}$ be a markov chain on the state space $S = {1,ldots,r}$ with transition matrix $P = (p_{i,j})_{1 leq i,j leq r}$ and initial probability vector $alpha = (alpha_{i} : i in S)$ with $alpha_{i} = mathbb{P}(X_{0} = i)$. Let $q(n_{1},ldots,n_{r})$ be the probability that up to time $n-1$ the state $1$ is visited $n_{1}$-times,$ldots$,state $r$ is visited $n_{r}$-times and $F_{n}(x_{1},ldots,x_{r}) = sum_{n_{1}+ cdots +n_{r} = n}q(n_{1},ldots,n_{r})x_{1}^{n_{1}}cdots x_{r}^{n_{r}}$ be the corresponding generating function of $q(n_{1},ldots,n_{r})$. Now I want to show that
$$
F_{n}(x_{1},ldots,x_{r}) = (alpha_{1}x_{1},ldots,alpha_{r}x_{r}) left( P D_{r}right)^{n-1} e,
$$
where $e = (1,ldots,1)^{intercal}$ and $D$ is given by
$$
D =
begin{bmatrix}
x_{1} && \
& ddots &\
& & x_{r}
end{bmatrix}.
$$
Here is my solution:
$$
begin{align*}
sum_{n_{1} + cdots + n_{r} = n}q(n_{1},ldots,n_{r}) &= sum_{j in I}mathbb{P}(X_{n-1} = j) \
&= sum_{j in I}sum_{i in I}alpha_{i}p_{i,j}^{n-1} \
&= left(sum_{i in I}alpha_{i}p_{i,1}^{n-1},ldots,sum_{i in I}alpha_{i}p_{i,r}^{n-1} right) e \
&= alpha P^{(n-1)} e.
end{align*}
$$
Does this suffice as a proof and is it correct? Thanks for any help!
probability probability-theory proof-verification markov-chains generating-functions
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I want to determine the generating function of the numbers of visits up to a specific time. Formally: let ${X_{n}}_{n geq 0}$ be a markov chain on the state space $S = {1,ldots,r}$ with transition matrix $P = (p_{i,j})_{1 leq i,j leq r}$ and initial probability vector $alpha = (alpha_{i} : i in S)$ with $alpha_{i} = mathbb{P}(X_{0} = i)$. Let $q(n_{1},ldots,n_{r})$ be the probability that up to time $n-1$ the state $1$ is visited $n_{1}$-times,$ldots$,state $r$ is visited $n_{r}$-times and $F_{n}(x_{1},ldots,x_{r}) = sum_{n_{1}+ cdots +n_{r} = n}q(n_{1},ldots,n_{r})x_{1}^{n_{1}}cdots x_{r}^{n_{r}}$ be the corresponding generating function of $q(n_{1},ldots,n_{r})$. Now I want to show that
$$
F_{n}(x_{1},ldots,x_{r}) = (alpha_{1}x_{1},ldots,alpha_{r}x_{r}) left( P D_{r}right)^{n-1} e,
$$
where $e = (1,ldots,1)^{intercal}$ and $D$ is given by
$$
D =
begin{bmatrix}
x_{1} && \
& ddots &\
& & x_{r}
end{bmatrix}.
$$
Here is my solution:
$$
begin{align*}
sum_{n_{1} + cdots + n_{r} = n}q(n_{1},ldots,n_{r}) &= sum_{j in I}mathbb{P}(X_{n-1} = j) \
&= sum_{j in I}sum_{i in I}alpha_{i}p_{i,j}^{n-1} \
&= left(sum_{i in I}alpha_{i}p_{i,1}^{n-1},ldots,sum_{i in I}alpha_{i}p_{i,r}^{n-1} right) e \
&= alpha P^{(n-1)} e.
end{align*}
$$
Does this suffice as a proof and is it correct? Thanks for any help!
probability probability-theory proof-verification markov-chains generating-functions
add a comment |
I want to determine the generating function of the numbers of visits up to a specific time. Formally: let ${X_{n}}_{n geq 0}$ be a markov chain on the state space $S = {1,ldots,r}$ with transition matrix $P = (p_{i,j})_{1 leq i,j leq r}$ and initial probability vector $alpha = (alpha_{i} : i in S)$ with $alpha_{i} = mathbb{P}(X_{0} = i)$. Let $q(n_{1},ldots,n_{r})$ be the probability that up to time $n-1$ the state $1$ is visited $n_{1}$-times,$ldots$,state $r$ is visited $n_{r}$-times and $F_{n}(x_{1},ldots,x_{r}) = sum_{n_{1}+ cdots +n_{r} = n}q(n_{1},ldots,n_{r})x_{1}^{n_{1}}cdots x_{r}^{n_{r}}$ be the corresponding generating function of $q(n_{1},ldots,n_{r})$. Now I want to show that
$$
F_{n}(x_{1},ldots,x_{r}) = (alpha_{1}x_{1},ldots,alpha_{r}x_{r}) left( P D_{r}right)^{n-1} e,
$$
where $e = (1,ldots,1)^{intercal}$ and $D$ is given by
$$
D =
begin{bmatrix}
x_{1} && \
& ddots &\
& & x_{r}
end{bmatrix}.
$$
Here is my solution:
$$
begin{align*}
sum_{n_{1} + cdots + n_{r} = n}q(n_{1},ldots,n_{r}) &= sum_{j in I}mathbb{P}(X_{n-1} = j) \
&= sum_{j in I}sum_{i in I}alpha_{i}p_{i,j}^{n-1} \
&= left(sum_{i in I}alpha_{i}p_{i,1}^{n-1},ldots,sum_{i in I}alpha_{i}p_{i,r}^{n-1} right) e \
&= alpha P^{(n-1)} e.
end{align*}
$$
Does this suffice as a proof and is it correct? Thanks for any help!
probability probability-theory proof-verification markov-chains generating-functions
I want to determine the generating function of the numbers of visits up to a specific time. Formally: let ${X_{n}}_{n geq 0}$ be a markov chain on the state space $S = {1,ldots,r}$ with transition matrix $P = (p_{i,j})_{1 leq i,j leq r}$ and initial probability vector $alpha = (alpha_{i} : i in S)$ with $alpha_{i} = mathbb{P}(X_{0} = i)$. Let $q(n_{1},ldots,n_{r})$ be the probability that up to time $n-1$ the state $1$ is visited $n_{1}$-times,$ldots$,state $r$ is visited $n_{r}$-times and $F_{n}(x_{1},ldots,x_{r}) = sum_{n_{1}+ cdots +n_{r} = n}q(n_{1},ldots,n_{r})x_{1}^{n_{1}}cdots x_{r}^{n_{r}}$ be the corresponding generating function of $q(n_{1},ldots,n_{r})$. Now I want to show that
$$
F_{n}(x_{1},ldots,x_{r}) = (alpha_{1}x_{1},ldots,alpha_{r}x_{r}) left( P D_{r}right)^{n-1} e,
$$
where $e = (1,ldots,1)^{intercal}$ and $D$ is given by
$$
D =
begin{bmatrix}
x_{1} && \
& ddots &\
& & x_{r}
end{bmatrix}.
$$
Here is my solution:
$$
begin{align*}
sum_{n_{1} + cdots + n_{r} = n}q(n_{1},ldots,n_{r}) &= sum_{j in I}mathbb{P}(X_{n-1} = j) \
&= sum_{j in I}sum_{i in I}alpha_{i}p_{i,j}^{n-1} \
&= left(sum_{i in I}alpha_{i}p_{i,1}^{n-1},ldots,sum_{i in I}alpha_{i}p_{i,r}^{n-1} right) e \
&= alpha P^{(n-1)} e.
end{align*}
$$
Does this suffice as a proof and is it correct? Thanks for any help!
probability probability-theory proof-verification markov-chains generating-functions
probability probability-theory proof-verification markov-chains generating-functions
edited 17 hours ago
Scientifica
6,37641335
6,37641335
asked 17 hours ago
wayne
492113
492113
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