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Benda, M. (1998). A central limit theorem for contractive stochastic dynamical systems. J. Appl. Prob.35, 200–205.CrossRefGoogle Scholar
Billingsley, P. (1968). Convergence of Probability Measures. John Wiley, New York.Google Scholar
Borkovec, M. and Klüppelberg, C. (2001). The tail of the stationary distribution of an autoregressive process with ARCH(1)-errors. Ann. Appl. Prob.11, 1220–1241.CrossRefGoogle Scholar
Diaconis, P., and Freedman, D. (1999). Iterated random functions. SIAM Rev.41, 45–76.CrossRefGoogle Scholar
Durrett, R., and Resnick, S. I. (1978). Functional limit theorems for dependent variables. Ann. Prob.6, 829–846.CrossRefGoogle Scholar
Elton, J. H. (1990). A multiplicative ergodic theorem for Lipschitz maps. Stoch. Process. Appl.34, 39–47.CrossRefGoogle Scholar
Herkenrath, U., Iosifescu, M., and Rudolph, A. (2003). Random systems with complete connections and iterated function systems. Math. Rep. (Bucur.)5, 127–140.Google Scholar
Heyde, C. C., and Scott, D. J. (1973). Invariance principles for the law of the iterated logarithm for martingales and processes with stationary increments. Ann. Prob.1, 428–436.CrossRefGoogle Scholar
Lasota, A., and Yorke, J. A. (1994). Lower bound technique for Markov operators and iterated function systems. Random Comput. Dynamics2, 41–77.Google Scholar
Scott, D. J. (1973). Central limit theorems for martingales and for processes with stationary increments, using a Skorokhod representation approach. Adv. Appl. Prob.5, 119–137.CrossRefGoogle Scholar
Szarek, T. (1997). Markov operators acting on Polish spaces. Ann. Polon. Math.67, 247–257.Google Scholar
Wu, W. B., and Woodroofe, M. (2000). A central limit theorem for iterated random functions. J. Appl. Prob.37, 748–755.CrossRefGoogle Scholar