Iterated random functions are used to draw pictures or simulate large Ising models, among other applications. They offer a method for studying the steady state distribution of a Markov chain, and give useful bounds on rates of convergence in a variety of examples. The present paper surveys the field and presents some new examples. There is a simple unifying idea: the iterates of random Lipschitz functions converge if the functions are contracting on the average.
No takes yet. Share an insight, caveat, or question.
Diaconis et al. (1999) studied this question.
Synapse has enriched 4 closely related papers on similar clinical questions. Consider them for comparative context: