Martingale approximation and optimality of some conditions for the central limit theorem
Probability
2009-12-16 v1
Abstract
Let be a stationary and ergodic Markov chain with kernel , an function on its state space. If is a normal operator and (which is equivalent to the convergence of in ), we have the central limit theorem (cf\. \cite{D-L 1}, \cite{G-L 2}). Without assuming normality of , the CLT is implied by the convergence of , in particular by , by \cite{M-Wu} and \cite{Wu-Wo} respectively. We shall show that if is not normal and , or if the conditions of Maxwell and Woodroofe or of Wu and Woodroofe are weakened to for some sequence , or by , the CLT need not hold.
Keywords
Cite
@article{arxiv.0912.2864,
title = {Martingale approximation and optimality of some conditions for the central limit theorem},
author = {Dalibor Volný},
journal= {arXiv preprint arXiv:0912.2864},
year = {2009}
}
Comments
to appear in Journal of Theoretical Probability