
AbstractWe study the properties of finite ergodic Markov Chains whose transition probability matrix P is singular. The results establish bounds on the convergence time of Pm to a matrix where all the rows are equal to the stationary distribution of P. The results suggest a simple rule for identifying the singular matrices which do not have a finite convergence time. We next study finite convergence to the stationary distribution independent of the initial distribution. The results establish the connection between the convergence time and the order of the minimal polynomial of the transition probability matrix. A queuing problem and a maintenance Markovian decision problem which possess the property of rapid convergence are presented.
Statistics and Probability, null space, Markov chains, Applied Mathematics, eigenvalues, Markov decision problem, Markov chains (discrete-time Markov processes on discrete state spaces), Queueing theory (aspects of probability theory), convergence time, accessibility, minimal polynomial, leading vectors, Modelling and Simulation
Statistics and Probability, null space, Markov chains, Applied Mathematics, eigenvalues, Markov decision problem, Markov chains (discrete-time Markov processes on discrete state spaces), Queueing theory (aspects of probability theory), convergence time, accessibility, minimal polynomial, leading vectors, Modelling and Simulation
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