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Research Article
Vol. 31, Issue 1
The Application of Runge-Kutta and Backward Differentiation Methods for Solving Transient Distribution in Markov Chain
The computation of state probability distributions at an arbitrary point in time, which in the case of a discrete-time Markov chain means finding the distribution at some arbitrary time step n de noted π(n), a row vector whose ith component is the probability that the Markov chain is in state i at time step n, is the iterative solution methods for ...
