question about the expected recurrence times to states












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  1. Consider a finite Markov Chain $R$ on the state space ${0,1,2,cdots, N}$ with transition probability matrix $P=|P_{ij}|_{i,j=0}^N$ consisting of three classes ${0,1,2,cdots,N-1}$ and ${N}$ where $0$ and $N$ are absorbing states, both accessible from $k=1,cdots,N-1$ and ${1,2,cdots,N-1}$ is a transient class. Let $k$ be a state satisfying $0<k<N$. We define a auxiliary process $R$ called "the return process" by altering the first and last row of $P$ so that $P_{0k}=P_{Nk}=1$ and leave the other rows unchanged. The return process $R$ is clearly irreducible. Prove that the expected time until absorption $u_k$ with initial state k in the $R$ process equals $1/(pi_0+pi_N)-1$ where $pi_0+pi_N$ is the stationary probability of being in state $0$ or $N$ for the R process.


Hint: Use the relation between stationary probabilities and expected recurrence times or states










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    1. Consider a finite Markov Chain $R$ on the state space ${0,1,2,cdots, N}$ with transition probability matrix $P=|P_{ij}|_{i,j=0}^N$ consisting of three classes ${0,1,2,cdots,N-1}$ and ${N}$ where $0$ and $N$ are absorbing states, both accessible from $k=1,cdots,N-1$ and ${1,2,cdots,N-1}$ is a transient class. Let $k$ be a state satisfying $0<k<N$. We define a auxiliary process $R$ called "the return process" by altering the first and last row of $P$ so that $P_{0k}=P_{Nk}=1$ and leave the other rows unchanged. The return process $R$ is clearly irreducible. Prove that the expected time until absorption $u_k$ with initial state k in the $R$ process equals $1/(pi_0+pi_N)-1$ where $pi_0+pi_N$ is the stationary probability of being in state $0$ or $N$ for the R process.


    Hint: Use the relation between stationary probabilities and expected recurrence times or states










    share|cite|improve this question











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      1. Consider a finite Markov Chain $R$ on the state space ${0,1,2,cdots, N}$ with transition probability matrix $P=|P_{ij}|_{i,j=0}^N$ consisting of three classes ${0,1,2,cdots,N-1}$ and ${N}$ where $0$ and $N$ are absorbing states, both accessible from $k=1,cdots,N-1$ and ${1,2,cdots,N-1}$ is a transient class. Let $k$ be a state satisfying $0<k<N$. We define a auxiliary process $R$ called "the return process" by altering the first and last row of $P$ so that $P_{0k}=P_{Nk}=1$ and leave the other rows unchanged. The return process $R$ is clearly irreducible. Prove that the expected time until absorption $u_k$ with initial state k in the $R$ process equals $1/(pi_0+pi_N)-1$ where $pi_0+pi_N$ is the stationary probability of being in state $0$ or $N$ for the R process.


      Hint: Use the relation between stationary probabilities and expected recurrence times or states










      share|cite|improve this question











      $endgroup$





      1. Consider a finite Markov Chain $R$ on the state space ${0,1,2,cdots, N}$ with transition probability matrix $P=|P_{ij}|_{i,j=0}^N$ consisting of three classes ${0,1,2,cdots,N-1}$ and ${N}$ where $0$ and $N$ are absorbing states, both accessible from $k=1,cdots,N-1$ and ${1,2,cdots,N-1}$ is a transient class. Let $k$ be a state satisfying $0<k<N$. We define a auxiliary process $R$ called "the return process" by altering the first and last row of $P$ so that $P_{0k}=P_{Nk}=1$ and leave the other rows unchanged. The return process $R$ is clearly irreducible. Prove that the expected time until absorption $u_k$ with initial state k in the $R$ process equals $1/(pi_0+pi_N)-1$ where $pi_0+pi_N$ is the stationary probability of being in state $0$ or $N$ for the R process.


      Hint: Use the relation between stationary probabilities and expected recurrence times or states







      stochastic-processes






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      edited Dec 27 '18 at 7:51









      Sauhard Sharma

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      953318










      asked Dec 27 '18 at 7:36









      GloriaGloria

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