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Convergence of iterates of a transfer operator, application to dynamical systems and to Markov chains

Jean-Pierre Conze, Albert Raugi (2010)

ESAIM: Probability and Statistics

We present a spectral theory for a class of operators satisfying a weak “Doeblin–Fortet" condition and apply it to a class of transition operators. This gives the convergence of the series ∑k≥0krPkƒ, r ∈ ℕ , under some regularity assumptions and implies the central limit theorem with a rate in n - 1 2 for the corresponding Markov chain. An application to a non uniformly hyperbolic transformation on the interval is also given.

Cutoff for samples of Markov chains

Bernard Ycart (2010)

ESAIM: Probability and Statistics

We study the convergence to equilibrium of n-samples of independent Markov chains in discrete and continuous time. They are defined as Markov chains on the n-fold Cartesian product of the initial state space by itself, and they converge to the direct product of n copies of the initial stationary distribution. Sharp estimates for the convergence speed are given in terms of the spectrum of the initial chain. A cutoff phenomenon occurs in the sense that as n tends to infinity, the total variation...

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