generating function of numbers of visits up to time n












3














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!










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    3














    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!










    share|cite|improve this question



























      3












      3








      3







      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!










      share|cite|improve this question















      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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      edited 17 hours ago









      Scientifica

      6,37641335




      6,37641335










      asked 17 hours ago









      wayne

      492113




      492113






















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