Random walk with zero reflection derivations












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Problem image



Does anyone know how to derive the proof that if p < 1/2, then all states are positive recurrent? I've tried using this formula: $q*1 + p*(T_1*q + p*(2T_1*q + ...$
where $T_1$ is the expected time to revisit the first state. This doesn't seem to work and reduces to a finite value for any $p < 1$, so I'm assuming the logic is flawed. I've attached a picture of the problem










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    0














    Problem image



    Does anyone know how to derive the proof that if p < 1/2, then all states are positive recurrent? I've tried using this formula: $q*1 + p*(T_1*q + p*(2T_1*q + ...$
    where $T_1$ is the expected time to revisit the first state. This doesn't seem to work and reduces to a finite value for any $p < 1$, so I'm assuming the logic is flawed. I've attached a picture of the problem










    share|cite|improve this question

























      0












      0








      0







      Problem image



      Does anyone know how to derive the proof that if p < 1/2, then all states are positive recurrent? I've tried using this formula: $q*1 + p*(T_1*q + p*(2T_1*q + ...$
      where $T_1$ is the expected time to revisit the first state. This doesn't seem to work and reduces to a finite value for any $p < 1$, so I'm assuming the logic is flawed. I've attached a picture of the problem










      share|cite|improve this question













      Problem image



      Does anyone know how to derive the proof that if p < 1/2, then all states are positive recurrent? I've tried using this formula: $q*1 + p*(T_1*q + p*(2T_1*q + ...$
      where $T_1$ is the expected time to revisit the first state. This doesn't seem to work and reduces to a finite value for any $p < 1$, so I'm assuming the logic is flawed. I've attached a picture of the problem







      markov-chains random-walk






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      share|cite|improve this question




      share|cite|improve this question










      asked Nov 27 at 5:08









      Brian Sun

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