Central limit theorems for iterated random Lipschitz mappings

Details Central limit theorems for iterated random Lipschitz mappings Central limit theorems for iterated random Lipschitz mappings

2004-10-05

arxiv.org/abs/math/0410103v1

Annals of Probability 2004, Vol. 32, No. 3A, 1934-1984

Mathematics

Probability

Published by the Institute of Mathematical Statistics (http://www.imstat.org) in the Annals of Probability (http://www.imsta

Scientific paper

10.1214/009117904000000469

Let M be a noncompact metric space in which every closed ball is compact, and let G be a semigroup of Lipschitz mappings of M. Denote by (Y_n)_{n\geq1} a sequence of independent G-valued, identically distributed random variables (r.v.'s), and by Z an M-valued r.v. which is independent of the r.v. Y_n, n\geq1. We consider the Markov chain (Z_n)_{n\geq0} with state space M which is defined recursively by Z_0=Z and Z_{n+1}=Y_{n+1}Z_n for n\geq0. Let \xi be a real-valued function on G\times M. The aim of this paper is to prove central limit theorems for the sequence of r.v.'s (\xi(Y_n,Z_{n-1}))_{n\geq1}. The main hypothesis is a condition of contraction in the mean for the action on M of the mappings Y_n; we use a spectral method based on a quasi-compactness property of the transition probability of the chain mentioned above, and on a special perturbation theorem.

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