Occupation laws for some time-nonhomogeneous Markov chains
Zach Dietz, Sunder Sethuraman
Abstract
We consider finite-state time-nonhomogeneous Markov chains where the probability of moving from state i to state j≠ i at time n is G(i,j)/nζ for a ``generator'' matrix G and strength parameter ζ>0. In these chains, as time grows, the positions are less and less likely to change, and so form simple models of age-dependent time-reinforcing behaviors. These chains, however, exhibit some different, perhaps unexpected, asymptotic occupation laws depending on parameters. Although on the one hand it is shown that the asymptotic position converges to a point-mixture for all ζ>0, on the other hand, the average position, when variously 0<ζ<1, ζ>1 or ζ=1, is shown to converges to a constant, a point-mixture, or a distribution μG with no atoms and full support on a certain simplex respectively. The last type of limit can be seen as a sort of ``spreading'' between the cases 0<ζ<1 and ζ>1. In particular, when G is appropriately chosen, μG is a Dirichlet distribution with certain parameters, reminiscent of results in Polya urns.
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