Publication | Open Access
On the Markov chain central limit theorem
363
Citations
50
References
2004
Year
Central Limit TheoremsEngineeringGibbs MeasureEntropyUncertainty QuantificationStochastic ProcessesMarkov KernelInteracting Particle SystemMixing ConditionsProbability TheoryComputer ScienceMarkov Chain Monte CarloPoisson BoundaryStochastic GeometryCentral Limit Theorem
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.
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