A Revisit of Block Power Methods for Finite State Markov Chain Applications
Hao Ji,
Seth H. Weinberg,
Yaohang Li
Abstract:According to the fundamental theory of Markov chains, under a simple connectedness condition, iteration of a Markov transition matrix P , on any random initial state probability vector, will converge to a unique stationary distribution, whose probability vector corresponds to the left eigenvector associated with the dominant eigenvalue λ 1 = 1. The corresponding convergence speed is governed by the magnitude of the second dominant eigenvalue λ 2 of P . Due to the simplicity to implement, this approach by using… Show more
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