Random iteration of Euclidean isometries

Nonlinearity 16 (2003) 977-987

Markus Ådahl, Ian Melbourne and Matthew Nicol


Abstract

We consider the statistical behaviour of i.i.d. compositions of a finite set of Euclidean isometries of Rn$. We give a new proof of the central limit theorem and weak invariance principles, and we obtain the law of the iterated logarithm. Our results generalise immediately to Markov chains. We also give simple geometric criteria for orbits to grow linearly or sublinearly with probability one and for nondegeneracy (nonsingular covariance matrix) in the statistical limit theorems. Our proofs are based on dynamical systems theory rather than a purely probabilistic approach.


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