Abstract
We consider random iterated function systems giving rise to Markov chains in random (stationary) environments. Conditions ensuring unique ergodicity and a “pure type” characterization of the limiting “randomly invariant” probability measure are provided. We also give a dimension formula and an algorithm for simulating exact samples from the limiting probability measure.
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