On Markov Chains with Continuous State Space


In this expository paper, we p r o ve the following theorem, which m a y be of some use in studying Markov chain Monte Carlo methods like hit and run, the Metropolis algorithm, or the Gibbs sampler. Suppose a discrete-time Markov c hain is aperiodic, irreducible, and there is a stationary probability distribution. Then from almost all starting points the… (More)


Figures and Tables

Sorry, we couldn't extract any figures or tables for this paper.

Slides referencing similar topics