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One can obtain a new proof of the homogenization result (1.4) from proposition 2.1 by using the fact that Ψ is square integrable on Ω and applying the von Neumann ergodic theorem..
Central limit theorems for Markov chains are considered, and in particular the relationships between various expressions for asymptotic variance known from the literature.. These
Dobrushin proved in his thesis [2] an important central limit theorem (CLT) for Markov chains in discrete time that are not necessarily homogeneous in time. Previously,
Key words: Multivariate and functional central limit theorems, random fields, martingale limit theorems, self-interacting Markov chains, Markov chain Monte Carlo methods,
The most successful techniques in the quantitative study of (time homogeneous) finite Markov chains include: coupling, strong stationary time, spectral methods, and
A question of increasing importance in the Markov chain Monte Carlo literature (Gelfand and Smith, 1990; Smith and Roberts, 1993) is the issue of geometric ergodicity of Markov
Central limit theorems for functionals of general state space Markov chains are of crucial importance in sensible implementation of Markov chain Monte Carlo algorithms as well as
For a given ordinary differential equation we propose a method consisting in a sequence of Markov chains to approximate its solution, where each of these chains minus its
