This problem will show why steady-state probabilities are sometimes referred to as stationary...

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This problem will show why steady-state probabilities are sometimes referred to as stationary probabilities. Let ?1, ? 2, . . . , ?s be the steady-state probabilities for an ergodic chain with transition matrix P. Also suppose that with probability ? i, the Markov chain begins in state i. a What is the probability that after one transition, the system will be in state i? (Hint: Use Equation (8).) b For any value of n(n = 1, 2, . . .), what is the probability that a Markov chain will be in state i after n transitions? c Why are steady-state probabilities sometimes called stationary probabilities? Aug 29 2014 11:56 AM

 

Solution ID:609224 | This paper was updated on 26-Nov-2015

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