On the Markov chain central limit theorem
Probability SurveysPublished 1 January 2004Open access
Galin L. Jones
Citations371
SJR quartileQ1
SJR score0.98
SNIP1.55
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Abstract
The goal of this expository paper is to describe conditions which guarantee a central limit theorem for functionals of general state space Markov chains. This is done with a view towards Markov chain Monte Carlo settings and hence the focus is on the connections between drift and mixing conditions and their implications. In particular, we consider three commonly cited central limit theorems and discuss their relationship to classical results for mixing processes. Several motivating examples are given which range from toy one-dimensional settings to complicated settings encountered in Markov chain Monte Carlo.
Keywords
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