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assumed to be continuous, the corresponding Markov chain will have the weak Feller property. The fact that a process is topologically recurrent also implies that.. it has some
For instance, given simply an m -symmetric right process M on a Lusin topological space X , M automatically becomes m -tight and m -special standard, and consequently the
Abstract We consider Markov chains on the space of (countable) partitions of the interval [0 , 1], obtained first by size biased sampling twice (allowing repetitions) and then
We prove the CLT for a random walk in a dynamical environment where the states of the environ- ment at different sites are independent Markov chains..
To this end we introduce a comparison finite state Markov chain which will be “close” to the non-Markov process obtained by looking at the n sites to the left of the rightmost
A question of increasing importance in the Markov chain Monte Carlo literature (Gelfand and Smith, 1990; Smith and Roberts, 1993) is the issue of geometric ergodicity of Markov
A Markov chain is considered whose states are orderings of an underlying fixed tree and whose transitions are local “random-to-front” reorderings, driven by a probability
In the case of a Markov chain over an infinite state space with a unique stationary distribution, the notion of a mixing time depends on the state of origination of the
